{"id":1928,"date":"2016-06-02T14:59:17","date_gmt":"2016-06-02T14:59:17","guid":{"rendered":"https:\/\/www.eng.ufl.edu\/graduate\/?page_id=1928"},"modified":"2025-09-10T09:25:22","modified_gmt":"2025-09-10T14:25:22","slug":"electrical-and-computer-engineering","status":"publish","type":"page","link":"https:\/\/www.eng.ufl.edu\/graduate\/current-students\/undergraduate-research\/research-projects\/electrical-and-computer-engineering\/","title":{"rendered":"Electrical and Computer Engineering"},"content":{"rendered":"\n
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Project Title: <\/strong>Magnetic Microsystems
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor:<\/strong> David Arnold, darnold@ufl.edu<\/u><\/a>
Ph.D. Student Mentor(s):<\/strong> Various
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong> Sophomore, Junior, Senior, Number of Students per Semester Varies
Prerequisites:<\/strong>  Varies by project. No background in magnetics required. Just a strong curiosity and willingness to learn!
Credit:<\/strong>  0-3 credits via EGN 4912
Stipend:<\/strong> Paid positions are available based on qualifications.
Application Requirements:<\/strong> Resume, UF unofficial transcripts, Statement of research interest, Email Professor Arnold (darnold@ufl.edu<\/u><\/a>) with application materials. Priority for students considering graduate research.
Application Deadline:<\/strong> none
Website:<\/strong> https:\/\/www.img.ufl.edu\/research-groups\/david-arnolds-research-group<\/a>
Project Description:<\/strong> Research interests include -Micro\/nanostructured magnetic materials -Magnetic microsystems and electromechanical transducers -Biomedical applications of magnetic systems -Compact (<100 W) power\/energy systems (wireless power, energy harvesting, circuits). We are an experimental research group. Research duties may involve microfabrication, chemical\/thermal processing, simulation\/modeling, circuit design, system design, testing & characterization.  Please visit website for descriptions of specific openings<\/p>\n\n\n\n

Project Title #1: <\/strong>Food, Medicine and Supplements Safety Analysis Using Handheld Spectroscopy
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor: <\/strong>Swarup Bhunia, swarup@ece.ufl.edu<\/a>
Ph.D. Student Mentor(s):<\/strong> Naren Vikram Raj Masna
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong> Freshman, Sophomore, Junior, Senior, 2 students per semester
Prerequisites:<\/strong>  Basic knowledge of physics, chemistry, mathematics, electrical and magnetic fields, signals and systems. Interest in practical experimental works.
Credit:<\/strong>  Contact Dr. Swarup Bhunia
Stipend:<\/strong> Contact Dr. Swarup Bhunia
Application Requirements:<\/strong> Basic Online Application, Resume, Statement of research interest, Faculty Interview, Email Dr. Swarup Bhunia, swarup@ece.ufl.edu<\/a>, with application requirements.
Application Deadline:<\/strong> None
Website: <\/strong>None
Project Description:<\/strong> The supply chain for food and dietary supplements has become more complex, distributed, and also less secure over time. As a result, different types of fraudulent activities – e.g. adding harmful substances, re-branding of inferior products, etc., leading to integrity issues in these products have emerged as a serious concern. Every year, consumers are cheated of billions of dollars, and the monetary value of fraud in food and dietary or nutritional supplements is estimated to be over $40 billion annually. Existing solutions for analysis often require extensive sample preparation or are limited in terms of detecting different types of integrity issues. We are working on a novel authentication method based on Nuclear Quadrupole Resonance (NQR) spectroscopy, which is quantitative, non-invasive, and non-destructive. It is sensitive to small deviation in the solid-state chemical structure of a product, which changes the NQR signal properties. These characteristics are unique for different manufacturers, resulting in manufacturer-specific watermarks. We use a machine learning-based classification called support vector machines (SVMs) to verify the authenticity of products under test. This approach has been evaluated using semi-custom hardware. We are also working on making a portable setup of the entire setup.<\/p>\n\n\n\n

Project Title #2: <\/strong>Machine Learning for Verifying Trustworthiness of Electronics
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor: <\/strong>Swarup Bhunia, swarup@ece.ufl.edu<\/a>
Ph.D. Student Mentor(s):<\/strong> Tamzidul Hoque and Prabuddha Chakraborty
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong> Junior, Senior, 2 students per semester
Prerequisites:<\/strong>  Required: digital logic, digital design; Recommended: programming experience and machine learning
Credit:<\/strong>  0-3 credits via EGN 4912
Stipend:<\/strong> Contact Dr. Swarup Bhunia
Application Requirements:<\/strong> Basic Online Application, Resume, Statement of research interest, Faculty Interview, Email Dr. Swarup Bhunia, swarup@ece.ufl.edu<\/a>, with application requirements.
Application Deadline:<\/strong> none
Website:<\/strong> N\/A
Project Description:<\/strong> Malicious modification of integrated circuits known as hardware Trojans have become a serious concern today with the globalization of the IC supply chain. In this project, we are looking to apply machine learning techniques to help in verifying trustworthiness by identifying potential malicious structures in electronics procured from untrusted companies. Students interested in hardware security and cybersecurity with programming background are strongly encouraged to apply. Students will become familiar with several commercial CAD tools used in industry today.<\/p>\n\n\n\n

Project Title #3: <\/strong>Hardware Trojan Detection through Self-Referencing
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor: <\/strong>Swarup Bhunia, swarup@ece.ufl.edu<\/a>
Ph.D. Student Mentor(s):<\/strong> Tamzidul Hoque and Jonathan Cruz
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong> Junior, Senior, 2 students per semester
Prerequisites:<\/strong>  Required: digital logic, digital design; Recommended: basic circuits and programming knowledge.
Credit:<\/strong>  0-3 credits via EGN 4912
Stipend:<\/strong> Contact Dr. Swarup Bhunia
Application Requirements:<\/strong> Basic Online Application, Resume, Statement of research interest, Faculty Interview, Email Dr. Swarup Bhunia, swarup@ece.ufl.edu<\/a>, with application requirements.
Application Deadline:<\/strong> none
Website:<\/strong> N\/A
Project Description:<\/strong> The fabrication process of integrated circuits (ICs) is often outsourced to foreign countries for economic advantages. In an untrusted foundry, the original design could be maliciously modified prior to fabrication also known as hardware Trojan insertion. In this project, we are looking to apply a novel “self-referencing” based technique that allows us to compare the fingerprint of an untrusted IC with itself, which eliminates the need of acquiring a golden signature to detect the presence of hardware Trojans. Students interested in hardware security and cybersecurity with programming and basic knowledge of electronics are strongly encouraged to apply. Students will get the experience of using various CAD tools and doing hands-on hardware experiments that are very useful in industry.<\/p>\n\n\n\n

Project Title #4: <\/strong>Secure and Reliable FPGAs
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor: <\/strong>Swarup Bhunia, swarup@ece.ufl.edu<\/a>
Ph.D. Student Mentor(s):<\/strong> Abdulrahman Alaql, alaql89@ufl.edu<\/a>
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong> Junior, Senior, 2 students per semester
Prerequisites:<\/strong>  Required: digital logic, digital design, familiarity with reconfigurable devices (FPGAs); Recommended: basic circuits and programming knowledge.
Credit:<\/strong>  0-3 credits via EGN 4912
Stipend:<\/strong> Contact Dr. Swarup Bhunia
Application Requirements:<\/strong> Basic Online Application, Resume, Statement of research interest, Faculty Interview, Email Dr. Swarup Bhunia, swarup@ece.ufl.edu<\/a>, with application requirements.
Application Deadline:<\/strong> none
Website:<\/strong> N\/A
Project Description:<\/strong> Field Programmable Gate Arrays (FPGA) are increasingly utilized in diverse applications, such as military, health-care, automotive systems, and the Internet of Things (IoT). The security of FPGA-based designs has emerged as a critical concern due to the FPGA design files (bitstreams) being vulnerable to attacks. Bitstream obfuscation has been recently studied as a potential solution that provides the necessary protection to designs mapped onto FPGA. This approach relies on a key generation function, such as Physical Unclonable Function (PUF) to alter a mapped function both structurally and functionally. However, a fundamental problem with PUF-based key generators is that the key bits are unstable and therefore cannot provide the same desired key at all times. In this project, we will implement a robust obfuscation approach that is capable of tolerating bit-flips in the generated key. We will develop an algorithm that applies the obfuscation to designs mapped to any FPGA. Finally, we will demonstrate the robustness against bit-flips on several digital signal processing (DSP) intellectual property (IP) blocks and observed the performance under various percentages of bit-flips in the key.<\/p>\n\n\n\n

Project Title #5: <\/strong>Wearable Carotid Ultrasound for Early Detection of Cardiovascular Diseases (CVDs)
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor: <\/strong>Swarup Bhunia, swarup@ece.ufl.edu<\/a>
Ph.D. Student Mentor(s):<\/strong> Sumaiya Shomaji
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong> Freshman, Sophomore, Junior, 1 – 2 students per semester
Prerequisites:<\/strong>  Programming Skills (Python or MATLAB preferred) and\/or Circuit Design Experience
Credit:<\/strong>  0-3 credits via EGN 4912
Stipend:<\/strong> N\/A
Application Requirements:<\/strong> Basic Online Application, Resume, Statement of research interest, Faculty Interview, Email one pdf file with all application requirements to Dr. Swarup Bhunia, swarup@ece.ufl.edu<\/a>, to request an interview.
Application Deadline:<\/strong> none
Website:<\/strong> N\/A
Project Description:<\/strong> Cardiovascular disease is currently responsible for a major portion of all global deaths. Fortunately, early detection of its symptoms can greatly contribute to effective prevention. Although various methods for cardiac diagnosis exist, most of them are clinic-based, and therefore time-consuming and costly. In this project, we are working on a novel wearable ultrasonic imaging assembly for routine, easy-to-use, and economical monitoring of the carotid artery as this is a proven marker for diagnosis of cardiovascular disease. Students interested in healthcare innovations with programming and\/or circuit design background are strongly encouraged to apply.<\/p>\n\n\n\n

Project Title #6: <\/strong>Remote Authentication of Internet of Things (IoT) devices
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor: <\/strong>Swarup Bhunia, swarup@ece.ufl.edu<\/a>
Ph.D. Student Mentor(s):<\/strong> N\/A
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong>  Junior, Senior; 2 students per term
Prerequisites:<\/strong> Required: digital logic, digital design, familiarity with reconfigurable devices (FPGAs); Recommended: basic circuits and programming knowledge.
Credit:<\/strong>  0-3 credits via EGN 4912
Stipend:<\/strong> N\/A
Application Requirements:<\/strong> Basic Online Application, Resume, Statement of research interest, Faculty Interview, Email one pdf file with all application requirements to Dr. Swarup Bhunia, swarup@ece.ufl.edu<\/a>, to request an interview.
Application Deadline:<\/strong> none
Website:<\/strong> http:\/\/swarup.ece.ufl.edu\/<\/a>
Project Description:<\/strong> Internet of Things (IoT) has become a novel and popular paradigm in the scenario of communication, sensing, security, etc. and they have greatly impacted our lives in multiple application domains, including transportation and logistics, health care, personal, social, smart environment, and so on. The heterogeneous array of such devices in an infrastructure can greatly benefit from a hardware difficult-to-clone and a set of tamper-immune identifiers, which can be used to check the authenticity or integrity of a device. However, IoT entities are extremely vulnerable to attacks including physical tampering attacks since they are exposed and unattended in the environment for a long period of time. So, we are focusing on developing an intrinsic device identifier that captures the state of an IoT device and it can effectively reflect any physical tampering by transforming the intrinsic delay\/transient current variations of boundary scan cell (BSC) paths into unique and robust signatures. This approach utilizes the boundary scan chain architecture (BSA) in integrated circuits (ICs) and printed circuit boards (PCB) – a prevalent design-for-test (DFT) structure used in majority of PCBs today. Based on a standard DFT structure, this method works for heterogeneous devices and can be conducted during runtime of the device. We will generate signatures from devices under test and evaluate their security parameters in terms of uniqueness, robustness, randomness, etc. We will also explore a protocol for the cloud server, owner, or other IoT devices in a network to verify the identity of an IoT device using the proposed approach. This policy should be able prevent attacks to extract the secret keys of a device using an efficient moving target defense mechanism that periodically shifts the challenge vectors.<\/p>\n\n\n\n

Project Title #7: <\/strong>Developing a smart connected system for detecting and mitigating air-borne pathogens
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor: <\/strong>Swarup Bhunia, swarup@ece.ufl.edu<\/a>
Ph.D. Student Mentor(s):<\/strong> Naren V. Masna
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong>  Sophomore, Junior, Senior; 2 students per term
Prerequisites:<\/strong> Experience with digital electronics (for hardware development) and Experience with programming (for software development)
Credit:<\/strong>  1
Stipend:<\/strong> $1,000 a semester
Application Requirements:<\/strong> Basic Online Application, Resume, Faculty Interview, Email one pdf file with all application requirements to Dr. Swarup Bhunia, swarup@ece.ufl.edu<\/a>, to request an interview.
Application Deadline:<\/strong> none
Website:<\/strong> http:\/\/swarup.ece.ufl.edu\/<\/a>
Project Description:<\/strong> In this project, we focus on developing a closed-loop internet of things (IoT) system for sensing of air-borne pathogens and mitigating their health impact. The project will specifically focus on detecting respiratory droplets in air, potentially laden with deadly viruses, such as the novel coronavirus causing the COVID-19 disease, and then mitigating them through various mechanisms, so as to drastically reduce their infectious capability. The students will get opportunity for developing the hardware-software components of a smart wearable system in this project and testing it in the field.<\/p>\n\n\n\n

Project Title: <\/strong>IoT devices for Human Health and Safety
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor:<\/strong> William Eisenstadt, wre@tec.ufl.edu<\/u><\/a>
Ph.D. Student Mentor(s):<\/strong> N\/A
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong> Sophomore, Junior, Senior, Up to 4 students a semester
Prerequisites:<\/strong>  Courses in one of the following areas: (1) Digital Design (2) Analog Design or Power Electronics (3) Microprocessor Systems and Embedded Programming (4) Programming
Credit:<\/strong>  0-3 credits via EGN 4912
Stipend:<\/strong> none unless selected for University Scholars
Application Requirements:<\/strong> Basic online application, Resume, UF unofficial transcripts, statement of research interest; email a pdf file with all application requirements to Prof. Bill Eisenstadt, wre@tec.ufl.edu<\/u><\/a>
Application Deadline:<\/strong> none
Website:<\/strong> None
Project Description:<\/strong> Building hardware, software, apps and web sites for wireless sensor platforms for agriculture, mosquito control and food chain safety. Existing projects include wireless WiFi solar weather stations for agriculture in Haiti and US mosquito control, bluetooth-based temperature posts for fly control for animal breeding facilities. New projects will be defined to develop wireless sensor platforms for flood and river drainage, for soil moisture, soil salinity, bluetooth-based weather stations, and water salinity measurements. Wireless mosquito traps are also a project. Also, embedded programming, custom phone apps and web software are needed for all applications.<\/p>\n\n\n\n

Project Title: <\/strong>EdgeVPN Overlay Networks for Edge Computing
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor:<\/strong> Renato Figueiredo, renato@acis.ufl.edu<\/a>
Ph.D. Student Mentor(s):<\/strong> Several students in the lab
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong> Sophomore, Junior; 1-2 students per term
Prerequisites:<\/strong>  Ideal candidates will: (1) have strong computer programming skills, in particular Python and C++; (2) be able to work independently to solve problems; (3) have good foundation on computer networks and distributed computing; (4) be proficient in UNIX environments; and (5) have excellent writing and communication skills.
Credit:<\/strong>  0-3 credits via EGN 4912
Stipend:<\/strong> TBD depending on qualifications
Application Requirements:<\/strong> Basic online application; resume; mail one pdf file with all application requirements to Renato Figueiredo, renato@acis.ufl.edu<\/a>
Application Deadline:<\/strong> March 1 for Summer and Fall terms; November 1 for Spring term
Website:<\/strong> https:\/\/edgevpn.io<\/a>
Project Description: <\/strong>Projects are available to conduct research and software development on EdgeVPN, currently funded by the National Science Foundation. EdgeVPN is an open-source software-defined virtual private network (VPN) allowing end users to define seamlessly create a virtual Ethernet atop Internet tunnels setup and managed through a network of distributed controllers. These are applied computer systems research projects with broad applications in edge computing (computing near IoT devices), container deployment and orchestration (Docker, Kubernetes), AI applications for edge computing, and user-centric software-defined networking (SDN). The projects have an active open-source code base, collaborations with researchers in the US and abroad, and students will have opportunities to collaborate with researchers and software developers.<\/p>\n\n\n\n

Project Title:<\/strong> EM-Activated Hardware Trojan
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor: <\/strong>Farimah Farahmandi; farimah@ece.ufl.edu<\/a> 
Ph.D. Student Mentor(s):<\/strong>Md Rafid Muttaki (m.muttaki@ufl.edu<\/a>)
Terms Available: <\/strong>Summer
Student Level: <\/strong>Senior; 1 Student a Term
Prerequisites: <\/strong>Required: Electrical or Computer Engineering Major; Preferred: Coursework in Electromagnetic Fields, Analog Circuit Design, Digital Logic Design, Embedded Programming
Stipend: <\/strong>$5000
Application Requirements: <\/strong>Resume and UF Unofficial Transcripts; Email one pdf file with all application requirements to Farimah Farahmandi, farimah@ece.ufl.edu<\/a>.
Application Deadline: <\/strong>N\/A
Website: <\/strong>http:\/\/farimah.ece.ufl.edu\/<\/a>
Project Description: <\/strong>In this project, a Hardware Trojan was developed that can be activated by a specific and directed electromagnetic pulse chain. The solution uses an Antifuse and analog circuitry to drastically decrease the chance of detecting the Trojan, which makes it stealthy. Once activated, the maliciously-inserted analog circuitry delivers the Trojan payload, and the circuit is attacked. The attackers choice of Trojan placement within the circuit, as well as the design of the analog circuitry, determines the characteristics of the attack.<\/p>\n\n\n\n

Project Title: <\/strong>Automated Printed Circuit Board (PCB) Reverse Engineering via X-ray Tomography
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor:<\/strong> Domenic Forte, dforte@ece.ufl.edu<\/a>
Ph.D. Student Mentor(s):<\/strong> Kun Yang (k.yang@ufl.edu<\/a>)  and Joey Botero (jbot2016@ufl.edu<\/a>)
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong> Junior, Senior; 2 students per term
Prerequisites:<\/strong> Required: DIGITAL LOGIC & COMPUTER SYSTEMS, DIGITAL DESIGN; Recommended: Familiarity with any PCB design or CAD tool; familiarity with image processing, machine learning, and pattern recognition
Credit:<\/strong>  0-3 credits via EGN 4912
Stipend:<\/strong> none unless selected for University Scholars
Application Requirements:<\/strong>  Resume, unofficial transcripts, faculty interview, interest in graduate school encouraged; email all application requirements to Domenic Forte, dforte@ece.ufl.edu<\/a>, to request an interview
Application Deadline:<\/strong> none
Website:<\/strong>  dforte.ece.ufl.edu
Project Description:<\/strong> Reverse engineering (RE) of electronics can be both reassuring and concerning. globalization of IC and PCB industries has resulted in well-documented concerns such as counterfeiting and hardware Trojan insertion. For such instances, RE represents an important tool for validating the performance, quality, authenticity, and integrity of electronics. Similarly, many of the critical systems and infrastructures in use today are decades old. Maintaining them requires electronic components that are no longer available. Replacing or redesigning the entire system may be too time consuming or expensive. However, through RE one can study the particular component\/board in order to reproduce it and\/or replace it with an alternative in the legacy system. On the other hand, RE can be responsible for just as many threats as solutions. RE can also be exploited to generate unauthorized clones or find weaknesses in the system. As part of this project, students will analyze 3D images of PCBs and develop a tool that processes the image (assigns different pixel values to traces, vias, etc.), stiches together results, extracts the PCB netlist, and converts the resulting images\/netlist into a CAD file. Students should be able to program\/script in Matlab or similar language. Familiarity with PCB design tools and pattern recognition would be useful but is not required.<\/p>\n\n\n\n

Project Title:<\/strong>Hardware Security Primitive Design, Simulation, and Evaluation
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor:<\/strong> Domenic Forte, dforte@ece.ufl.edu<\/a>
Ph.D. Student Mentor(s):<\/strong> N\/A
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong> Junior, Senior; 2 students per term
Prerequisites:<\/strong> Digital Logic\/Computer Systems or Electronic Circuits 1
Credit:<\/strong>  0-3 credits via EGN 4912
Stipend:<\/strong> Depends on available resources unless selected for University Scholars
Application Requirements:<\/strong>  Resume, unofficial transcripts, faculty interview, interest in graduate school encouraged; email all application requirements to Domenic Forte, dforte@ece.ufl.edu<\/a>, to request an interview
Application Deadline:<\/strong> (preferred) March 1 for Summer, August 1 for Fall terms, and November 1 for the Spring term.
Website:<\/strong>  dforte.ece.ufl.edu
Project Description:<\/strong> Integrated circuits(ICs) have access to more sensitive information (i.e., assets) than ever before. Such assets should be protected because their leakage can lead to fraud, extortion, and blackmail. Physical attacks to extract assets from ICs are becoming more prevalent, but few countermeasures exist to prevent them. This project involves development of circuits and sensors to detect such attacks and destroy assets when they are under attack. Interested students should have interest or experience with one or more of the following: analog circuit design, digital circuit design, SPICE simulation, PCB design, VHDL\/Verilog, FPGA development and programming, Matlab or Python programming, machine learning and classification, and lab measurements. Students may learn how to use commercial CAD tools as part of this project, which can be helpful for future jobs.<\/p>\n\n\n\n

Project Title: <\/strong>Modeling of Monolayer Transistors for Flexible Electronics
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor:<\/strong> Jing Guo, guoj@ufl.edu<\/a>
Ph.D. Student Mentor(s):<\/strong> Runlai Wan, wanrunlai@ufl.edu<\/a>
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong> Junior, Senior, 1 student per semester
Prerequisites:<\/strong>  Circuit 1, computer programming, physics for electrical engineers
Credit:<\/strong>  0-3 credits via EGN 4912
Stipend:<\/strong> none unless selected for University Scholars
Application Requirements:<\/strong> Resume, UF unofficial transcripts, statement of research interest; email one pdf file with all application requirements to Jing Guo, guoj@ufl.edu<\/a>
Application Deadline:<\/strong> none
Website:<\/strong>  n\/a
Project Description:<\/strong> Two-dimensional (2D) monolayer semiconductor materials beyond graphene, such as layered transition metal dichalcogenides (TMDCs) like molybdenum disulfide (MoS2), are promising for many potential applications in nanoelectronics, flexible electronics, and optoelectronics due to their mechanical bendability, atomically thin thickness, and excellent intrinsic carrier transport properties. The student will be engaged on working together with the Ph.D. students in the PI’s group to develop computer-aided design (CAD) tools for electronics based on 2D monolayer materials. The CAD tools will be deployed and widely disseminated to users worldwide through the nanoHUB (www.nanohub.org)<\/p>\n\n\n\n

Project Title: <\/strong>Quantum Computing
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor:<\/strong> Jing Guo, guoj@ufl.edu<\/a>
Ph.D. Student Mentor(s):<\/strong> Tong Wu
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong> Junior, Senior, 2 students per semester
Prerequisites:<\/strong> Linear Algebra and Python programming
Credit:<\/strong>  0-3 credits via EGN 4912
Stipend:<\/strong> Paid position (NSF REU) available based on qualification and time of application
Application Requirements:<\/strong> Resume, UF unofficial transcripts, statement of research interest; email one pdf file with all application requirements to Jing Guo, guoj@ufl.edu<\/a>
Application Deadline:<\/strong> none
Website: <\/strong>N\/A
Project Description: <\/strong>The research project involves develop modeling, simulation, and visualization tools for quantum computing technologies. We are specifically interested in spin-based quantum computing. The project is supported by National Science Foundation.<\/p>\n\n\n\n

Project Title: <\/strong>Machine Learning and Wave Motion
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor:<\/strong> Joel Harley, joel.harley@ufl.edu<\/a>
Ph.D. Student Mentor(s)<\/strong>: N\/A
Terms Available:<\/strong> Fall, Spring
Student Level:<\/strong> Freshman, Sophomore, Junior, 2 student per semester
Prerequisites:<\/strong> None
Credit:<\/strong>  0-3 credits via EGN 4912
Stipend:<\/strong> none unless selected for University Scholars
Application Requirements:<\/strong> Basic online application, Resume, UF unofficial transcripts, Faculty Interview; email one pdf file with all application requirements to Prof. Harley, joel.harley@ufl.edu<\/a>, with the subject line: “Potential Undergraduate Researcher: Machine Learning and Wave Motion.”.
Application Deadline:<\/strong> December 1, 2018
Website:<\/strong> http:\/\/smartdata.ece.ufl.edu\/<\/a>
Project Description:<\/strong> In this research project, we learn to apply machine learning to physical problems that utilize waves. These may be acoustic waves, ultrasonic waves, or electromagnetic waves. Student researchers will learn to define problems, perform experiments, and design machine learning algorithms.<\/p>\n\n\n\n

Project Title: <\/strong>Validating the use of wearable technology and machine learning for exposure assessment of workers to uneven surfaces
Department:  <\/strong>Electrical and Computer Engineering, Industrial and Systems Engineering, & Computer and Information Science and Engineering,
Faculty Mentor:<\/strong> Boyi Hu, boyihu@ise.ufl.edu<\/a>
Ph.D. Student Mentor(s):<\/strong> TBD based on project and availability
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong> Junior, Senior, 1-2 students per semester.
Prerequisites:<\/strong>  Project details can be developed based on student\u2019s interest and background. Students considering graduate school are especially courage to apply. Prerequisite skills include: 1) at least 1 year of programming experience (Matlab or Python preferred); 2) signal processing fundamentals; 3) machine learning fundamentals
Credit:<\/strong>  0-3credits via EGN 4912
Stipend:<\/strong> $12\/hour up to 20 hours per week
Application Requirements:<\/strong> Resume, UF unofficial transcripts, statement of research interest, faculty interview, email one pdf file of requirements to Boyi Hu, boyihu@ise.ufl.edu<\/a> to request an interview
Application Deadline:<\/strong> N\/A
Website: <\/strong>N\/A
Project Description:<\/strong> The two main goals of this pilot project proposal are to: 1) determine if workers\u2019 gait behavior as measured by wearable sensors in real workplace differs significantly on different walking surfaces experienced by typical workers; and, 2) determine if artificial deep learning network algorithms can detect walking surface categories using signals from wearable sensors mounted on workers\u2019 body during typical walking tasks.<\/p>\n\n\n\n

Project Title:<\/strong> Low-light robot perception
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor: <\/strong>Md Jahidul Islam (jahid@ece.ufl.edu<\/a>)
Ph.D. Student Mentor(s): <\/strong>Boxiao Yu; (boxiao.yu@ufl.edu)Terms Available: <\/strong>Spring, Summer
Student Level: <\/strong>Junior, Senior
Number of Students: <\/strong>2 students a term
Prerequisites: <\/strong>Basic understanding on Python\/C++ programming, embedded systems, and\/or machine learning. Your curiosity and willingness to learn is the most important requirement!
Stipend: <\/strong>Contact Dr. Islam
Credits: <\/strong>0-3 credits via EGN 4912
Application Requirements: <\/strong>Basic online application, resume, and UF unofficial transcripts
Application Deadline: <\/strong>None
Application Process: <\/strong>Email one pdf file with all application requirements to jahid@ece.ufl.edu
Website: <\/strong>https:\/\/robopi.ece.ufl.edu\/research.html#LLP<\/a>
Project Description: <\/strong>We are working on developing robust sensing and estimation capabilities of on-device cameras in thermal, acoustic, and spectral domains. In particular, our focus is on low-power cameras used by autonomous underwater robots, firefighters wearables, and sky-quality-meters. We are launching projects with both hardware and software components as well as their domain implementations. The research areas intersect the fields of robotics, computer vision, and deep learning.<\/p>\n\n\n\n

Project Title:<\/strong> Low-light robot perception
Department:<\/strong>Long-term remote monitoring
Faculty Mentor: <\/strong>Md Jahidul Islam (jahid@ece.ufl.edu<\/a>)
Ph.D. Student Mentor(s):<\/strong> Catalina Murray; (catalinamurray@ufl.edu)Terms Available: <\/strong>Fall, Spring, Summer
Student Level: <\/strong>Junior, Senior
Number of Students: <\/strong>2 students a term
Prerequisites: <\/strong>Basic understanding on Python\/C++ programming, embedded systems, and\/or machine learning. Your curiosity and willingness to learn is the most important requirement!
Stipend: <\/strong>Contact Dr. Islam
Credits: <\/strong>0-3 credits via EGN 4912
Application Requirements: <\/strong>Basic online application, resume, and UF unofficial transcripts
Application Deadline: <\/strong>None
Application Process: <\/strong>Email one pdf file with all application requirements to jahid@ece.ufl.edu
Website: <\/strong>https:\/\/robopi.ece.ufl.edu\/research.html#LTRM<\/a>
Project Description: <\/strong>Focusing on the Florida coastlines, we are working toward developing technological solutions to address the practicalities of important subsea applications such as monitoring water quality, surveying seabed or seagrass habitats, and farming artificial reefs. We are exploring deployable systems for both passive sensing and prediction (of hazards or salient events) as well as coordinated active tracking by autonomous mobile robots. To achieve this, we are trying to solve several research problems in the domains of robot vision, deep visual perception algorithms, and thermal\/sonar imaging literature.<\/p>\n\n\n\n

Project Title:<\/strong> Electromechanical Energy Conversion, Power Electronics, and Renewable Energy
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor: <\/strong>Baoyun Ge (baoyun.ge@ece.ufl.edu<\/a>)
Ph.D. Student Mentor(s): <\/strong>N\/A
Terms Available:<\/strong> Fall, Spring, Summer
Student Level: <\/strong>Junior and Senior
Prerequisites: <\/strong>Varied by projects, circuits, electromagnetic field, signals and systems, power electronics
Credit: <\/strong>0-3 credits via EGN 4912
Stipend: <\/strong>Paid positions are available based on qualifications
Application Requirements: <\/strong>Resume, UF unofficial transcripts, and statement of research interest
Application Deadline: <\/strong>none
Website: <\/strong>https:\/\/gem.ece.ufl.edu<\/a>
Project Description: <\/strong>Research interests include electric machines, power electronics, and feedback control. Applications include electric vehicles, electric airplanes, space exploration, renewable energy, etc. Please visit the website for descriptions of specific openings.<\/p>\n\n\n\n

Project Title: <\/strong>Wireless Powering Brain Implants
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor: <\/strong>Adam Khalifa (a.khalifa@ufl.edu<\/a>)
Ph.D. Student Mentor(s): <\/strong>Various
Terms Available: <\/strong>Fall, Spring, Summer
Student Level: <\/strong>Sophomore, Junior, Senior
Prerequisites: <\/strong>Designing PCBs, Basic circuits, Electromagnetic field
Stipend: <\/strong>Paid positions are available based on qualifications
Credits: <\/strong>0-3 credits via EGN 4912
Application Requirements: <\/strong>Resume, Statement of Interest
Application Deadline: <\/strong>None
Application Process: <\/strong>Email Professor Khalifa (a.khalifa@ufl.edu<\/a>) with application materials. Priority for students considering graduate research.
Website: <\/strong>https:\/\/khalifa.ece.ufl.edu\/projects\/wireless-microdevices\/wireless-powering\/<\/a>
Project Description: <\/strong>The major goal of this project is to develop the next generation of brain stimulation devices for understanding and treating mental health illnesses and brain disorders. This project seeks to develop chronic ultra-small microdevices which are minimally-invasive, wireless, battery-less, and injectable. These devices are distributed across the brain to form a wireless network system for precise neural modulation. Since the harvested power is scarce for ultra-small receiver (Rx) coils, the efficiency of a 2-coil wireless link must be optimized. In this project the student will design a miniaturized flexible PCB to efficiently deliver power to the Tx coil. Students involved in this research project will learn about the field of neuroengineering, PCB design, and RF circuits. Please visit the website for more details.<\/p>\n\n\n\n

Project Title: <\/strong>Transcranial Magnetic Stimulation
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor: <\/strong>Adam Khalifa (a.khalifa@ufl.edu<\/a>)
Ph.D. Student Mentor(s): <\/strong>VariousTerms Available: <\/strong>Fall, Spring, Summer
Student Level: <\/strong>Sophomore, Junior, Senior
Prerequisites: <\/strong>Electromagnetic Field
Stipend: <\/strong>Paid positions are available based on qualifications.
Credits: <\/strong>0-3 credits via EGN 4912
Application Requirements: <\/strong>Resume, Statement of Interest
Application Deadline: <\/strong>None
Application Process: <\/strong>Email Professor Khalifa (a.khalifa@ufl.edu<\/a>) with application materials. Priority for students considering graduate research.
Website: <\/strong>https:\/\/khalifa.ece.ufl.edu\/projects\/magnetic-stimulation\/transcranial-magnetic-stimulation\/<\/a>
Project Description: <\/strong>The clinical use of transcranial magnetic stimulation (TMS) has been a prominent achievement in the field of neuroscience in the past two decades. In this research, to improve stimulation depth and focality, we propose a novel TMS technique which we call magnetic temporal interference (MTI). Students in this project will build a solenoid that will eventually be used to stimulate and target deep brain regions of large animal models (non-human primate, sheep, pigs).<\/p>\n\n\n\n

Project Title: <\/strong>Artificial Fovea Cameras and Sensors
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor:<\/strong> Sanjeev Koppal, sjkoopal@ece.ufl.edu<\/a>
Ph.D. Student Mentor(s):<\/strong> N\/A
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong> Sophomore, Junior, Senior, 3 students per semester
Prerequisites:<\/strong>  Calc 2, Python\/C\/C++ programming or equivalent, Matlab literacy, any hands-on experience (woodshop, metalshop, glass working, art studio, set design, etc.).
Credit:<\/strong>  0-3 credits via EGN 4912
Stipend:<\/strong> $10 per hour up to 10 hours per week
Application Requirements:<\/strong> Basic Online Application, Resume, Faculty Interview, email CV to Sanjeev Koppa, sjkoopal@ece.ufl.edu<\/a>, to request a meeting time
Application Deadline:<\/strong> none
Website:<\/strong> focus.ece.ufl.edu
Project Description:<\/strong> Our eyes “foveate” or place sensitivity of the highest resolution at important locations in a scene. I am interested in (a) Building cameras\/sensors that do the same, (b) Creating algorithms to control such cameras and (c) Demonstrating compelling applications.<\/p>\n\n\n\n

Project Title #1: <\/strong>All-Optical Naval Aircraft Networks
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor:<\/strong> Janise McNair, mcnair@ece.ufl.edu<\/u><\/a>
Ph.D. Student Mentor(s):<\/strong> TBD
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong> Junior, Senior; 2 students per term
Prerequisites:<\/strong>  One or more of these courses: EEL4598, EEL4599, CNT 4007C
Credit:<\/strong>  0-3 credits via EGN 4912
Stipend:<\/strong> $15 per hour up to 10 hours a week
Application Requirements:<\/strong> Resume, UF unofficial transcripts, faculty interview; email one pdf file with all application requirements to Dr. Janise McNair, mcnair@ece.ufl.edu<\/u><\/a>
Application Deadline:<\/strong> August 15 for fall; January 15 for spring; April 15 for summer
Website:<\/strong>  http:\/\/wam.ece.ufl.edu<\/u><\/a>
Project Description:<\/strong> We are designing high-speed fiber optic networks to replace current copper wire networks on navel aircraft (and later standardize the process for commercial aircraft). We need students to help us test different network designs by doing short-term research studies, hands-on hardware projects for proof-of-concept tests, or software\/programming projects for network simulations.<\/p>\n\n\n\n

Project Title #2: <\/strong>Distributed Space Networks
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor:<\/strong> Janise McNair, mcnair@ece.ufl.edu<\/u><\/a>
Ph.D. Student Mentor(s):<\/strong> Allen Starke
Terms Available:<\/strong> Summer
Student Level:<\/strong> Junior, Senior; 1 – 2 students in the summer
Prerequisites:<\/strong>  Junior or Senior level. Some programming in C\/C++
Credit:<\/strong>  3 credits via EGN 4912
Stipend:<\/strong> TBD
Application Requirements:<\/strong> Basic online application, Resume, UF unofficial transcripts, Letter(s) of recommendation, Statement of research interest, faculty interview; email one pdf file with all application requirements to Dr. Janise McNair, mcnair@ece.ufl.edu<\/u><\/a>
Application Deadline:<\/strong> April 15
Website:<\/strong>  http:\/\/wam.ece.ufl.edu<\/u><\/a>
Project Description:<\/strong> Space is the new frontier for data collection, processing and dissemination. In this project, researchers will study how to deliver data from a heterogeneous set of nodes (space craft, space station, satellites, etc.) to the appropriate destination with the requested bandwidth and quality of service. This project also allows the student to do multi-disciplinary research with astronomers, remote sensing engineers, aerospace engineers and physicists.<\/p>\n\n\n\n

Project Title #3: <\/strong>Distributed Cross Layer Networking for Smart Grid Security
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor:<\/strong> Janise McNair, mcnair@ece.ufl.edu<\/u><\/a>
Ph.D. Student Mentor(s):<\/strong> N\/A
Terms Available:<\/strong> Fall, Spring, and Summer
Student Level:<\/strong> Junior, Senior; 1 student
Prerequisites:<\/strong> EEL4598 or EEL5718 pre-requisite or co-requisite.
Credit:<\/strong>  3 credits via EGN 4912
Stipend:<\/strong> $500
Application Requirements:<\/strong> Basic online application, Resume, and apply to the University Scholars Program; email one pdf file with all application requirements to Dr. Janise McNair, mcnair@ece.ufl.edu<\/u><\/a>
Project Description:<\/strong> As the traditional power grid transitions into the use of smart grid technology, real-time system monitoring becomes more vulnerable to cyber-attacks like false data injection. This project pursues a cross-layer approach to smart grid security that includes power analysis, machine learning, and software defined networks. Students on this project will work on skills for developing network management policies using SDN, traffic monitoring and anomaly detection\/identification.<\/p>\n\n\n\n

Project Title: <\/strong>Distributed Control Design for Balancing the Grid Using Flexible Loads
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor:<\/strong> Sean Meyn, meyn@ece.ufl.edu<\/a>
Ph.D. Student Mentor(s):<\/strong> Neil Cammardella, ncammardella@ufl.edu<\/a>
Terms Available:<\/strong> Fall, Spring
Student Level:<\/strong> Sophomore, Junior, Senior, 1 or 2 per semester
Prerequisites:<\/strong>  Signals & Systems is essential, and some exposure to control desirable. Enrollment in ECE Smart Grid for Sustainable Energy is highly recommended!
Credit:<\/strong>  0-3 credits via EGN 4912, Negotiable
Stipend:<\/strong> NSF REU support is a possibility
Application Requirements:<\/strong> Resume, statement of research interest, faculty interview; email one pdf file with all application requirements to Sean Meyn, meyn@ece.ufl.edu<\/a>, and cc Neil Cammardella, ncammardella@ufl.edu<\/a>.
Application Deadline:<\/strong> N\/A
Website:<\/strong>  http:\/\/www.meyn.ece.ufl.edu\/publications\/current\/ancillary-service-to-the-grid-using-intelligent-deferrable-loads\/<\/a>
Project Description:<\/strong> Inexpensive energy from the wind and the sun comes with unwanted volatility, such as ramps with the setting sun or a gust of wind. Controllable generators have managed supply-demand balance of power in the past, but this is becoming increasingly costly with increasing penetration of renewable energy. The goal of this project is to create a science for “demand dispatch” that will create virtual energy storage from flexible loads. By design, the grid-level services from flexible loads will be as controllable and predictable as a generator or fleet of batteries. The potential economic impact of these new resources is enormous. California plans to spend billions of dollars on batteries that will provide only a small fraction of the balancing services that can be obtained using demand dispatch. The potential impact on society is enormous: a sustainable energy future is possible with the right mix of infrastructure and control systems.<\/p>\n\n\n\n

Project Title: <\/strong>High Power Radio Waves in the Ionosphere
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor:<\/strong> Robert Moore, moore@ece.ufl.edu<\/a>
Ph.D. Student Mentor(s):<\/strong> AJ Erdman, ajerdman@ufl.edu<\/a>
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong> Sophomore, Junior, Senior, 1 student per semester
Prerequisites:<\/strong>  Matlab programming exposure required.  Physics 2, Circuits 1, Signals and Systems, and Electromagnetic Fields & Waves are recommended.
Credit:<\/strong>  0-3 credits via EGN 4912
Stipend:<\/strong> none unless selected for University Scholars
Application Requirements:<\/strong> Resume, UF unofficial transcripts, statement of research interest, faculty interview; email one pdf file with all application requirements to Robb Moore, moore@ece.ufl.edu<\/a>, to request an interview.
Application Deadline:<\/strong> March 1 for Summer term; August 1 for Fall term; November 1 for Spring term
Website:<\/strong>  http:\/\/www.vlf.ece.ufl.edu<\/a>
Project Description:<\/strong> The HAARP observatory is located in Gakona, Alaska, and it operates a high power transmitter to perform ionopspheric heating experiments.  These high power radio waves interact with the lower ionosphere and produce interesting nonlinear effects that mimic natural activity.  A large number of high power heating experiments were performed between 2010 and 2014, and we are interested in searching our vast database for unexpected discoveries.<\/p>\n\n\n\n

Project Title: <\/strong>MIST Makers
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentors:<\/strong> Toshi Nishida (nishida@ufl.edu<\/a>), David Arnold (darnold@ufl.edu<\/a>), Y.K. Yoon (ykyoon@ece.ufl.edu<\/a>), Bill Eisenstadt (wre@tec.ufl.edu<\/a>)
Ph.D. Student Mentor(s):<\/strong> N\/A
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong> Sophomore, Junior, Senior; 3-10 students per term
Prerequisites:<\/strong>  Self-motivated; responsible; creative; team-oriented
Credit:<\/strong>  0-3 credits via EGN4912
Stipend:<\/strong> None unless selected for University Scholars
Application Requirements:<\/strong> Resume, UF unofficial transcripts, faculty interview; email one pdf file with all application requirements to Toshi Nishida, nishida@ufl.edu<\/a>
Application Deadline:<\/strong> Aug. 15 for Fall; Jan. 15 for Spring; April 15 for Summer
Website:<\/strong>  www.mist-center.org
Project Description:<\/strong> The MIST Makers is an undergraduate effort within the UF\u2019s Department of Electrical and Computer Engineering. Students volunteer to work in teams to develop creative smart systems that integrate sensors, computing, wireless connectivity and power management, commonly known as the Internet of Things. Now in its second year, students can develop practical, problem-solving and design skills while working on hardware projects to improve quality of life or address real-world problems. Students also gain exposure to the MIST Center\u2019s member companies looking to recruit top talent.<\/p>\n\n\n\n

Project Title: <\/strong>Development of Autonomous Mobile Agents (Robots)
Department: <\/strong>Electrical and Computer Engineering, Computer and Information Science and Engineering, Mechanical and Aerospace Engineering
Faculty Mentors:<\/strong> Eric Schwartz, ems@ufl.edu<\/a>
Ph.D. Student Mentor(s):<\/strong> N\/A
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong> Freshman, Sophomore, Junior, Senior; 15-50 students per term
Prerequisites:<\/strong>  A desire to learn and work with others.
Credit:<\/strong>  0-3 credits via EGN4912
Stipend:<\/strong> None unless selected for University Scholars or Emerging Scholars
Application Requirements:<\/strong> Faculty interview; send email to Dr. Schwartz at ems@ufl.edu<\/a> to set up an appointment
Application Deadline:<\/strong> ASAP<\/strong>
Website:<\/strong>   www.mil.ufl.edu<\/a>
Project Description:<\/strong> MIL provides a cross-disciplinary synergistic environment dedicated to the study and development of intelligent, autonomous robots. We conduct research in the theory and realization of autonomous mobile agents covering topics such as machine learning, real-time sensor integration (including computer vision, LADAR, sonar, radar, IMU, etc.), optimization, and control. Applications of MIL research (that have produced functioning robots) include autonomous underwater vehicles (AUVs), autonomous water surface vehicles (ASVs), autonomous land vehicles (ALVs), and autonomous aerial vehicles (AAVs). MIL regularly competes in international robot competitions (and has previously earned five world championships).<\/p>\n\n\n\n

Project Title: <\/strong>Visualization for Software Defined Radio
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor:<\/strong> John Shea, jshea@ece.ufl.edu<\/u><\/a>
Ph.D. Student Mentor(s):<\/strong> n\/a
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong> Sophomore, Junior, Senior; 2 students per term
Prerequisites:<\/strong>  Javascript programming, basic knowledge of HTML and\/or CSS
Credit:<\/strong>  0-3 credits via EGN 4912
Stipend:<\/strong> none at this point, but potential for pay beginning in spring
Application Requirements:<\/strong> Resume, faculty interview; email resume to John Shea, jshea@ece.ufl.edu<\/u><\/a>
Application Deadline:<\/strong> any time
Website:<\/strong>  n\/a
Project Description:<\/strong> Students will work with Javascript, CSS, HTML, and Python to build tools that help visualize the usage of spectrum and flow of information in wireless networks.<\/p>\n\n\n\n

Project Title: <\/strong>Measurement of Nanodevices
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor:<\/strong> Ant Ural, antural@ece.ufl.edu<\/u><\/a>
Ph.D. Student Mentor(s):<\/strong> N\/A
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong> Junior; Senior 1 student per semester
Prerequisites:<\/strong> N\/A
Stipend:<\/strong> none unless selected for University Scholars
Application Requirements:<\/strong> Resume, UF unofficial transcripts; email one pdf file with all application requirements to Ant Ural, antural@ece.ufl.edu<\/u><\/a>
Application Deadline:<\/strong> N\/A
Website:<\/strong>  https:\/\/faculty.eng.ufl.edu\/ant-ural\/<\/a>
Project Description:<\/strong> Set-up and perform electrical measurements on nanodevices<\/p>\n\n\n\n

Project Title: <\/strong>Variable Frequency Drive Systems EMI Modeling and Reduction
Department:<\/strong> Electrical and Computer Engineering
Faculty Mentor:<\/strong> Shuo Wang, SHUO.WANG@ECE.UFL.EDU<\/u><\/a>
Ph.D. Student Mentor(s):<\/strong> Le Yang (yangleMike@ufl.edu<\/u><\/a>) and Hui Zhao (zhaohui@ufl.edu<\/u><\/a>)
Terms Available:<\/strong> Summer
Student Level:<\/strong> Senior; 1 student per semester
Prerequisites:<\/strong>  1) Power electronics I, 2) One of the following circuit simulation softwares: Pspice, Saber, Ansys Maxwell, HFSS, Matlab
Credit:<\/strong>  3 credits via EGN 4912
Stipend:<\/strong> none unless selected for University Scholars
Application Requirements:<\/strong> Basic online application, Resume, UF unofficial transcripts, Faculty interview; email one pdf file with all application requirements to Dr. Shuo Wang (SHUO.WANG@ECE.UFL.EDU<\/u><\/a>) to request an interview
Application Deadline:<\/strong> March 1
Website:<\/strong>  N\/A
Project Description:<\/strong> Learn research skill with PhD students in ongoing research on the EMI Modeling and Reduction for Grid Tied Variable Frequency Motor Drive Systems.<\/p>\n\n\n\n

Project Title: <\/strong>FFT on GPU
Department<\/strong>: Electrical and Computer Engineering
Faculty Mentor:<\/strong> Tan Wong, twong@ece.ufl.edu<\/a>
Ph.D. Student Mentor(s):<\/strong> David Greene, djgreene@ufl.edu<\/a>
Terms Available:<\/strong> Fall, Spring
Student Level:<\/strong> Junior; 1 student per semester
Prerequisites:<\/strong>  none
Credit:<\/strong>  0-3 credits via EGN 4912
Stipend:<\/strong> none unless selected for University Scholars
Application Requirements:<\/strong> Faculty interview; email Tan Wong, twong@ece.ufl.edu<\/a> to request an interview
Application Deadline:<\/strong> March 1
Website:<\/strong>  none
Project Description:<\/strong> Develop and implement a FFT in C Cuda to run on a GPU. The FFT should provide a significant speed increase over CPU FFT applications.<\/p>\n\n\n\n

Project Title #1: <\/strong>Extracting Configuration Parameter Interactions using Static Analysis
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor:<\/strong> Tuba Yavuz, tuba@ece.ufl.edu<\/a>
Ph.D. Student Mentor(s):<\/strong> n\/a
Terms Available:<\/strong> Fall
Student Level:<\/strong> Senior; 1 student per term
Prerequisites:<\/strong>  Advanced programming skills
Credit:<\/strong>  0 credits via EGN 4912
Stipend:<\/strong> none unless selected for University Scholars
Application Requirements:<\/strong> Resume, faculty interview; email required documents to Tuba Yavuz, tuba@ece.ufl.edu<\/a>
Application Deadline:<\/strong> This project has terminated
Website:<\/strong>  http:\/\/www.tuba.ece.ufl.edu\/<\/a>
Project Description:<\/strong> This project involved using static program analysis to identify configuration parameters that interacted through on data-flow and\/or control-flow dependency. The static analysis has been implemented using the WALA analysis framework. As a case study we chose Apache Hadoop as tuning configuration parameters is a real challenge for this system. Experimental results showed that static analysis could infer some of the known interactions among performance related parameters.<\/p>\n\n\n\n

Project Title #2: <\/strong>GUI for SMACK Models
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor:<\/strong> Tuba Yavuz, tuba@ece.ufl.edu<\/u><\/a>
Ph.D. Student Mentor(s):<\/strong> Farhaan Fowze, farhaan104@ufl.edu<\/u><\/a>
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong> Junior, Senior; 1 student per term
Prerequisites:<\/strong>  Data Structures, Intermediate to Advanced GUI programming skills
Credit:<\/strong>  3 credits via EGN 4912
Stipend:<\/strong> none unless selected for University Scholars
Application Requirements:<\/strong> Basic online application, Resume, Faculty interview; email required documents to Tuba Yavuz, tuba@ece.ufl.edu<\/u><\/a>
Application Deadline:<\/strong> Open until filled
Website:<\/strong>  N\/A
Project Description:<\/strong> This project involves designing and implementing a GUI for a new modeling language, SMACK, that is based on state machines with callback mechanism. The GUI should facilitate creating new SMACK models and navigating existing ones. SMACK is integrated with automated verification and the GUI should also support navigation of counter-example paths that explain erroneous executions.<\/p>\n\n\n\n

Project Title: <\/strong>Health Monitoring and Biting Force Detection Using a Smart Mouthguard 
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor:<\/strong> YK Yoon, ykyoon@ece.ufl.edu<\/a>
Ph.D. Student Mentor(s):<\/strong> Todd Schumann, fhghfjk@ufl.edu<\/a>
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong> Junior, Senior; 2-4 students per term
Prerequisites:<\/strong>  Electronic Circuit and ECE Junior Design
Credit:<\/strong>  0-2 credits via EGN 4912
Stipend:<\/strong> none unless selected for University Scholars
Application Requirements:<\/strong> Basic online application, Resume, UF unofficial transcripts; email one pdf with all application requirements to Prof. Yoon at ykyoon@ece.ufl.edu<\/a>
Application Deadline:<\/strong> March 1 for Summer term, August 1 for the Fall terms and November 1 for the Spring term
Website:<\/strong>  http:\/\/www.img.ufl.edu\/mnm<\/a>
Project Description:<\/strong> A smart mouthguard integrated with multiple sensors is utilized for multiple purposes such as dental protection from nocturnal Bruxism and during sports and fitness, which is its original function, and health monitoring via integrated sensors, which is an advanced function. The sensing module is integrated with a microprocessor, a Bluetooth wireless module, and a battery. A prototype module has been demonstrated while sensor refinements for a strain gauge sensor for biting force detection and an infrared (IR) sensor for vital sign monitoring are under investigation. A strain gauge sensor can be used. Biting during Bruxism produces a pressure of about 100lbs to 200lbs i.e, 2000kPa. Hence, the sensor should be able to withstand this pressure level with a reasonable resolution.
For IR sensing, a commercial product is accommodated. Efforts for signal processing will be needed.<\/p>\n\n\n\n

Project Title: <\/strong>Machine Learning and Pattern Recognition
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor:<\/strong> Alina Zare, azare@ece.ufl.edu<\/a>
Ph.D. Student Mentor(s):<\/strong> N\/A
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong> Junior, Senior, number needed per semester varies
Prerequisites:<\/strong>  Strong programming background (with preference for Python and\/or Matlab), Calculus, Linear Algebra, Statistics
Credit:<\/strong>  0-3 credits via EGN 4912
Stipend:<\/strong> Paid positions available based on background and qualifications
Application Requirements:<\/strong> Basic online application, resume, UF unofficial transcripts, Statement of research interest, email one pdf with all application requirements to Aline Zare at azare@ece.ufl.edu<\/a>. Priority for students considering Graduate Research at UF.
Application Deadline:<\/strong> N\/A
Website:<\/strong> https:\/\/faculty.eng.ufl.edu\/alina-zare\/<\/a>
Project Description:<\/strong> The Machine Learning and Sensing Laboratory develops machine learning methods for autonomously analyzing and understanding sensor data. We investigate and develop machine learning, pattern recognition, computational intelligence, signal processing, and information fusion methods for application to sensing. Applications we have studied include landmine and explosive object detection, automated plant phenotyping, sub-pixel target detection, and underwater scene understanding. We have developed algorithms for ground-penetrating radar, hyperspectral imagery, electromagnetic induction data, synthetic aperture SONAR, and minirhizotron imagery. Our specific projects vary from semester to semester. Please see our website for a listing of current projects: https:\/\/faculty.eng.ufl.edu\/alina-zare\/machine-learning-sensing-lab\/<\/a><\/p>\n\n\n\n

Project Title #1: <\/strong>Biomedical Applications of Magnetic Nanoparticles
Department: <\/strong>Biomedical Engineering, Chemical Engineering, Electrical Engineering, Computer Science and Engineering, Materials Science and Engineering, Mechanical Engineering
Faculty Mentor:<\/strong> Carlos Rinaldi-Ramos, carlos.rinaldi@ufl.edu<\/a>
Ph.D. Student Mentor(s):<\/strong> varies
Terms Available:<\/strong> Fall, Spring, Summer
Student Level:<\/strong> Sophomore, Junior, 2-5 students per term (new students when positions open)
Prerequisites:<\/strong>  Passion for science and engineering, interest in research and in advancing technology, self-driven. Students from Biomedical Engineering, Chemical Engineering, Electrical Engineering, Computer Science and Engineering, Materials Science and Engineering, and Mechanical Engineering encouraged to apply.
Credit:<\/strong>  0-3 credits via EGN 4912
Stipend:<\/strong> none unless selected for University Scholars
Application Requirements:<\/strong> Resume and statement of research interest; email one pdf file with all application requirements to Carlos Rinaldi, carlos.rinaldi@ufl.edu<\/a>
Application Deadline:<\/strong> March 1 for Summer and Fall terms; November 1 for Spring term
Website:<\/strong>  http:\/\/www.bme.ufl.edu\/labs\/rinaldi\/<\/a>
Project Description:<\/strong> The Rinaldi lab is interested in biomedical applications of magnetic nanoparticles. We combine particle synthesis, modification, and characterization and fundamental understanding of response to magnetic actuation to advance applications in biomedical imaging, therapeutic delivery, and nanoscale thermal therapy. The research is interdisciplinary, combining concepts from biomedical, chemical, electrical, and materials science and engineering. Current efforts focus on developing tracers for magnetic particle imaging (MPI), an exciting new biomedical imaging modality that allows for non-invasive, unambiguous, and quantitative imaging of the in vivo distribution of superparamagnetic iron oxide nanoparticle tracers. This research involves nanoparticle synthesis and characterization, cell culture, animal studies, image analysis, 3D printing, and computer programming. Students interested in any of these aspects are encouraged to apply.<\/p>\n\n\n\n

Project Title #1: <\/strong>Package security & Backside protection
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor: <\/strong>Navid Asadi, nasadi@ece.ufl.edu<\/a>
Ph.D. Student Mentor(s): <\/strong>Chengjie Xi and John True
Terms Available: <\/strong>Fall, Spring, Summer
Student Level: <\/strong>Sophomore, Junior, Senior; 2 students per term 
Prerequisites: <\/strong>Familiarity with basic semiconductor and polymer material knowledge
Stipend: <\/strong>Limited OPS Positions Available
Application Requirements: <\/strong>Email Dr. Asadi with your resume; faculty interview required.
Application Deadline: <\/strong>N\/A
Website: <\/strong>nasadi.ece.ufl.edu
Project Description: <\/strong>Since the inception of mass-produced electronic devices in the 1970s, IC packaging has been a vital piece of the electronics supply chain. Packaging reliability has been discussed widely in both industry and academia. However, packaging security assessment is barely addressed in such communities. Malicious changes in packaging parameters by a manufacturer can result in undetected features that cause chip failure. This results in disastrous consequences when these changed chips go to critical applications such as space, military, hospitals, powerplants, etc. In this project, the first step is to understand the structure and material composition of different kinds of IC packaging. To achieve such understanding, the project involves evaluating the packaging with the physical inspection methods in our lab to see how the security vulnerabilities of IC packaging can be generated and exploited. Based on security issues, different kinds of protection methods will be developed later. One such attack vector is a backside attack, which is both cheap and simple. With a device as simple as a laser pointer, attackers can hack into the chips. By applying a certain wavelength laser on the chip backside, hackers can easily extract useful information or inject fault. This project aims to prevent this kind of attack happens. In the project, learning and understanding of backside attack will be the first step, and students will get a chance to do backside attacks by themselves in the lab. Based on their own background and knowledge, they can develop their own backside protection methods.<\/p>\n\n\n\n

Project Title #2: <\/strong>Automated Volumetric Analysis via X-Ray Computed Tomography
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor: <\/strong>Navid Asadi, nasadi@ece.ufl.edu<\/a>
Ph.D. Student Mentor(s): <\/strong>John True
Terms Available: <\/strong>Fall, Spring, Summer
Student Level: <\/strong>Junior or Senior; 2 students per term 
Prerequisites: <\/strong>Familiarity with Circuits 2, Image Processing, MATLAB or Python; Preferred: CAD Design, Machine Learning
Stipend: <\/strong>Limited OPS Positions Available
Application Requirements: <\/strong>Email Dr. Asadi with your resume; faculty interview required.
Application Deadline: <\/strong>N\/A
Website: <\/strong>nasadi.ece.ufl.edu
Project Description: <\/strong>X-Ray Computed Tomography (X-Ray CT) is a rapidly advancing field due to the advent of next-generation tools such as Micro-CT & Nano-CT. In addition to hardware advances, there are software improvements that offer increased speed and resolution for fast failure analysis. Auto-3D is the refining and incorporation of these advanced techniques into the hardware assurance and reverse engineering processes and flows used in the cybersecurity industry. The current methods of hardware verification for microelectronics involves destructive techniques such as cross sectioning and delayering to analyze with visual methods. Non-destructive volumetric methods such as X-ray analysis has been adequate for simple electronics designs. However, smaller internal circuitry and its increasing complexity creates many x-ray imaging issues for non-destructive internal analysis. These imaging issues include artifacts such as photon starvation due to the entire absorption of x-rays by dense materials such as metals from circuitry, components, or heat\/EMF shields. The Auto-3D project is focused on improving computational runtime speed and resolution of the reconstruction of 2D images into 3D volumes, optimizing the scan parameters of x-ray imaging for electronics through laboratory testing and computer simulation, and automated segmentation of 3D volumes and performing analysis of noise and errors via machine learning. As part of this project: students will work together to research and develop solutions, facilitate learning outcomes aligned with future academic research or industry requirements, build data-driven designs and proposals that improve upon known research in the field, and interact with F.I.C.S. faculty and facilities through presentations and lab experiments.<\/p>\n\n\n\n

Project Title #3: <\/strong>Automated Bill of Material Extraction
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor: <\/strong>Navid Asadi, nasadi@ece.ufl.edu<\/a>
Ph.D. Student Mentor(s): <\/strong>Nathan Jessurun and Olivia Paradis
Terms Available: <\/strong>Fall, Spring, Summer
Student Level: <\/strong>Junior or Senior; 2 students per term 
Prerequisites:<\/strong> Familiarity with any PCB design or CAD tool; image processing, computer vision, machine learning, and pattern recognition
Stipend: <\/strong>Limited
Application Requirements: <\/strong>Email Dr. Asadi with your resume; faculty interview required.
Application Deadline: <\/strong>N\/A
Website: <\/strong>nasadi.ece.ufl.edu
Project Description: <\/strong>The goal of AutoBoM is to automatically extract a Bill of Materials (BoM), the list of all components on a printed circuit board (PCB) given an image of the board. The extracted BoM can then be used for reverse engineering and hardware assurance purposes. For instance, such a BoM can be compared to the known list of materials for the same sample, showing any discrepancy resulting from malicious tampering. When no reference BoM is present, verification becomes much more difficult. In these cases, AutoBoM can generate a tentative circuit schematic and cross-reference it against common design metrics. In these cases, Trojans or other manipulations will appear as violations to these standards. AutoBoM involves two primary research domains: the initial stages of image acquisition and preprocessing, followed by the use of machine learning models for component detection, classification, and identification.
Image acquisition and processing inputs to the AutoBoM process include several 2D optical images of PCB surfaces. Various image processing and computer vision algorithms then extract information from these images necessary to train machine learning networks. Several subdomains are important in this stage to analyze the image data.
Image segmentation, or breaking an image into distinct regions, assists in gathering ground truth data which trains machine learning models in how to detect components on a PCB image. Next, standard preprocessing procedures such as morphological processing, bandpass filtering, structural analysis, and more determine which portions of the image may require in-depth evaluation. This feedback serves two important functions. First, it determines which neural network architectures are appropriate for different stages of the AutoBoM process (e.g. component detection, defect analysis, etc.). Second, it assists in formatting the data as inputs to these networks, which speeds up learning and processing times.
Machine learning models for detection, classification, identification Inputs to the machine learning side of the AutoBoM process include the important computer vision features extracted from the PCB images (e.g. colors, shapes, and textures). Then, a multi-stage machine learning methodology is applied. First, the machine learning algorithms detect the location of the components within the PCB images. Then, the algorithm determines the type of each component (e.g. resistor, capacitor, IC). Finally, AutoBoM leverages information such as on-component text, board text, and colors to uniquely identify each component. The end result is a BoM specific enough to purchase all required components necessary to reverse engineer the PCB.<\/p>\n\n\n\n

Undergraduate students interested in working in these areas should have knowledge of general image processing, computer vision, and machine learning procedures. Additionally, familiarity with array computing (e.g. broadcasting, GPU\/CUDA arrays, etc.) in python is strongly desired.<\/p>\n\n\n\n

Project Title: <\/strong>Integrated Radio-Frequency Filters for 5G Wireless
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor: <\/strong>Roozbeh Tabrizian, rtabrizian@ufl.edu<\/a>
Ph.D. Student Mentor(s): <\/strong>Various
Terms Available: <\/strong>Fall, Spring, Summer
Student Level: <\/strong>Junior or Senior; Number of Students Varies 
Prerequisites: <\/strong>Varies by project. No background in electro-mechanics required. Just interest in math and physics, strong curiosity, and willingness to learn.
Stipend: <\/strong>Paid positions are available based on qualifications
Application Requirements: <\/strong>Email Prof. Tabrizian (rtabrizian@ufl.edu<\/a>) your application material. Priority for students considering graduate research.
Application Deadline: <\/strong>N\/A
Website: <\/strong>https:\/\/www.img.ufl.edu\/research-groups\/roozbeh-tabrizians-research-group<\/a> or https:\/\/phonon.ece.ufl.edu\/<\/a>
Project Description: <\/strong>We are an multi-disciplinary research group targeting creation of novel integrated filters for the modern wireless commination systems. This project includes design and analysis chip-scale filters operating at ultra- and super-high frequencies. These filters are essential for operation of our smart-phones, by enabling secure access to wireless spectrum for high-speed data communication.
The filters are operating based on exciting low-loss mechanical resonance in nano-scale silicon structures. The mechanical vibration will be converted to electrical domain using piezoelectric transducers. The role of the candidate will be designing the equivalent circuit models for these electro-mechanical filters, and also help with measurement of actual filter chips.<\/p>\n\n\n\n

Project Title: <\/strong>Machine Learning and Data Science
Department: <\/strong>Electrical and Computer Engineering
Faculty Mentor: <\/strong>Catia Silva, catiaspsilva@ece.ufl.edu<\/a>
Ph.D. Student Mentor(s): <\/strong>N\/A
Terms Available: <\/strong>Fall, Spring, Summer
Student Level: <\/strong>Junior or Senior; 2 Students a Term
Prerequisites: <\/strong>Programming background (with preference in Python and\/or Matlab), Calculus, Probability and Statistics, Linear Algebra
Stipend: <\/strong>None unless selected for University Scholars
Application Requirements: <\/strong>Email one PDF with Resume to Catia Silva at catiaspsilva@ece.ufl.edu<\/a>
Application Deadline: <\/strong>N\/A
Website: <\/strong>catiaspsilva.github.io\/ <\/a>
Project Description: <\/strong>Students will work with Python to perform data collection and curation with the goal to develop machine learning algorithms in different applications. Students will learn about experimental design in machine learning, develop technical skills such as version control, Python and machine learning.<\/p>\n\n\n\n

Project Title:  <\/strong>Remote Access to Side Channel (RASC) v4 System Design
Departments: <\/strong>Electrical and Computer Engineering
Faculty Mentors: <\/strong>Domenic Fort, dforte@ece.ufl.edu<\/a>
Ph.D. Student Mentor(s): N\/A
Terms Available: <\/strong>Fall, Spring, Summer
Student Level: <\/strong>Sophomore, Junior,  Senior; 4-Feb
Prerequisites: <\/strong>None
Credit: <\/strong>0-3
Stipend: <\/strong>Depends on availability of funds
Application Requirements: <\/strong>Resume, UF unofficial transcripts, Faculty interview E-mail applications materials to Dr. Forte, dforte@ece.ufl.edu<\/a>
Application Deadline: N\/A
Website(s):  https:\/\/dforte.ece.ufl.edu\/<\/a>
Project Description: Remote access to side-channel (RASC) systems have been developed and tested in our group to detect malware and other anomalies on critical systems from power and EM measurements in real-time. To date, RASC has monitored side-channels on an Arduino UNO running at 1MHz. This project involves development of a new version of RASC that can monitor more complex microcontrollers , e.g., 32 bit running at 200MHz+. The design shall be broken down into 3 parts: (1) hardware design where a new PCB and bill of materials will be created resulting in a system with higher sampling rate, resolution, and\/or processing capabilities; (2) machine learning and classification algorithm development where captured side-channels will be used to classify instructions being run on a microcontroller; and (3) hardware description language (HDL) design where the algorithm(s) will be mapped to digital signal processors and\/or FPGAs. Students need only have the experience and\/or interest in one part of the project in order to participate.<\/p>\n\n\n\n

Project Title: <\/strong>Neural Electrode Design
Departments: <\/strong>Electrical and Computer Engineering
Faculty Mentors: <\/strong>Adam Khalifa, a.khalifa@ufl.edu<\/a>
Ph.D. Student Mentor(s): N\/A
Terms Available: <\/strong>Fall, Spring, Summer
Student Level: <\/strong>Sophomore, Junior, Senior, 1 student per semester
Prerequisites: <\/strong>None
Credit: <\/strong>0-3 credits via EGN 4912
Stipend: <\/strong>$15 per hour
Application Requirements: <\/strong>Basic online application, Faculty interview, a.khalifa@ufl.edu<\/a>
Application Deadline: N\/A
Website(s): <\/strong>N\/A
Project Description:  <\/strong>This project aims to design a device for simultaneous D wave monitoring and cerebrospinal fluid (CSF) diversion in spinal cord injury, similar to intracranial pressure monitoring in brain injury. The D wave, which reflects descending action potentials in corticospinal tracts after cortical stimulation, is a key marker for predicting neurological outcomes. Since D wave monitoring requires accessing the subdural space, this project explores the potential of combining it with CSF diversion, an intervention increasingly used in managing ischemic and traumatic spinal cord injuries.<\/p>\n","protected":false},"excerpt":{"rendered":"

Project Title: Magnetic MicrosystemsDepartment: Electrical and Computer EngineeringFaculty Mentor: David Arnold, darnold@ufl.eduPh.D. Student Mentor(s): VariousTerms Available: Fall, Spring, SummerStudent Level: Sophomore, Junior, Senior, Number of Students per Semester VariesPrerequisites:  Varies by project. No background in magnetics required. Just a strong curiosity and willingness to learn!Credit:  0-3 credits via EGN 4912Stipend: Paid positions are available based on […]<\/p>\n","protected":false},"author":19875,"featured_media":0,"parent":1782,"menu_order":6,"comment_status":"closed","ping_status":"closed","template":"page-templates\/page-section-nav.php","meta":{"_acf_changed":false,"inline_featured_image":false,"featured_post":"","footnotes":"","_links_to":"","_links_to_target":""},"class_list":["post-1928","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.eng.ufl.edu\/graduate\/wp-json\/wp\/v2\/pages\/1928","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.eng.ufl.edu\/graduate\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.eng.ufl.edu\/graduate\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.eng.ufl.edu\/graduate\/wp-json\/wp\/v2\/users\/19875"}],"replies":[{"embeddable":true,"href":"https:\/\/www.eng.ufl.edu\/graduate\/wp-json\/wp\/v2\/comments?post=1928"}],"version-history":[{"count":4,"href":"https:\/\/www.eng.ufl.edu\/graduate\/wp-json\/wp\/v2\/pages\/1928\/revisions"}],"predecessor-version":[{"id":17673,"href":"https:\/\/www.eng.ufl.edu\/graduate\/wp-json\/wp\/v2\/pages\/1928\/revisions\/17673"}],"up":[{"embeddable":true,"href":"https:\/\/www.eng.ufl.edu\/graduate\/wp-json\/wp\/v2\/pages\/1782"}],"wp:attachment":[{"href":"https:\/\/www.eng.ufl.edu\/graduate\/wp-json\/wp\/v2\/media?parent=1928"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}