Research Projects

The projects below have been solicited from our respective faculty members for summer of 2015. We will recruit new projects from faculty members soon.  In your online application, please list the top five projects by preference with Project 1 as your most desired research project. You will not be guaranteed to work on your most desired project, but we will assign you to projects that best matches your background and experience. If no project matches your interest, please indicate your preferred research area.  You will be assigned to a project close to your area of interest.

If you do not see any projects that align with your major/interests, please specify what research area you are interested in on your application.

Project #1: Development of Nanoparticle-Filled Magnetorheological Nanocomposites for Semi-active Isolators
Project #2: 3D Computer Modeling of Cellular Biomechanics
Project #3: Microfluidic Platform for Cellular Biomechanics
Project #4: Quantitative Evaluation of Bone Development
Project #5: Low Impact Development of Small Scale Water Treatment System
Project #6: Quantitative Risk Assessment of Marine Vibrio Related Human Illness
Project #7: Global Satellite-Based Drought Monitoring and Prediction System
Project #8: Low Power Design
Project #9: Microcontrollers
Project #10: Mobile Apps Development
Project #11: Dielectrophoretic Electropolymerization for Particle Entrapment
Project #12: Design and Development of Autonomous Vehicles
Project #13: Development of a Hybrid Energy Storage Prototype
Project #14: Data-Driven Security Analysis for DNA Synthesizing
Project #15: Software Defined Radio
Project #16: Solar Panel and Tracker
Project #17: Camera-based Image Capture and Processing
Project #18: Sensor Based Telemetry
Project #19: Data-Driven Approaches for Analyzing the Manufacturing IoT Systems in a 3D-Pinter
Project #20: Development of Optical Imaging Technology for Biomedical Applications
Project #21: Spine-Rad Brachytherapy Bone Cement
Project #22: DietMate- A Multimodal Diet Monitoring System

 

Project #1: Development of Nanoparticle-Filled Magnetorheological Nanocomposites for Semi-active Isolators

Faculty Mentor: Professor Lizhi SunCivil & Environmental Engineering

Description:  Studies on magneto-mechanical responses for magnetorheological (MR) composites are of great interest to researchers and engineers in many science and engineering disciplines with civil engineering in particular since such smart materials can be employed for high power magnetostrictive actuation for anti-vibration applications, magnetoelastic sensor application in civil infrastructures monitoring, and on-demand damping control. The proposed research project aims to develop a novel type of MR nanocomposites filled with nanoparticles (such as carbon nanotubes and graphenes). Specifically, the project will focus on the composite fabrication process, three-dimensional tomography-based microstructural characterization, and dynamic magneto-mechanical testing of the MR three-phase nanocomposites. It is among the first attempt in the literature to combine the advantages of nanocomposites and magnetorheological materials to produce the novel smart nanocomposites in applications such as semi-active dampers and isolators for civil infrastructure systems. In addition, the project provides a unique opportunity for performing interdisciplinary research and cross-disciplinary education since it requires knowledge from engineering mechanics, materials science and civil structural engineering.

Students’ Involvement and Expected Outcomes: Under the faculty mentor’s supervision, the selected student will conduct research on (1) materials fabrication process, (2) microstructural characterization using nano-CT system, and (3) dynamic magneto-mechanical analysis of the developed MR three-phase nanocomposites. It is expected that the undergraduate student gain hand-on research experience on nanocomposites development in the field of structural engineering for future graduate research programs.

Prerequisites: Junior-standing undergraduate student majoring in engineering mechanics, civil engineering/structures, or materials science.

Recommended Web sites and publications: Li, R. and Sun, L.Z., 2011, “Dynamic mechanical behavior of magnetorheological nanocomposites filled with carbon nanotubes”, Applied Physics Letters, vol. 99, 131912-1-3.

 

Project #2: 3D Computer Modeling of Cellular Biomechanics

Faculty Mentor:  Professor William C. TangBiomedical Engineering

Description:  The mechanical behaviors of cells and small tissues are crucial manisfestation of physiological activities and disease states of the associated cells, but yet are beyond the reach of most conventional biochemical and optical-based investigation approaches. With the applications of microfabrication techniques and microfluidics, powerful tools can be realized to study the intricate relationships between the changes in mechanical properties and the underlying physiological activities of tissues and single cells. This research project aims at developing a set of 3D computer models that mimic the essential biomechanical behaviors of certain cell types, and how they interact with microfabricated sensor structures. The models are crucial in designing sensors that could be used to quantify mechanical properties of cells.

Students’ Involvement and Expected Outcomes: Students selected for this research project will study the essential biomechanical properties of a selected cell type, which will be chosen from among those with strong mechanical manifestations including cardiomyocytes, cancer cells, malaria infected red blood cells, and others. The students will learn the research skills needed to develop, test, and refine a set of 3D computer models and how they interact with the controlled environment for the chosen cell type.

Prerequisites:  Students with biology background and experience in computer modeling is preferred. Experience in using ABAQUS, SolidWorks, COMSOL, or similar programs is a plus.

 

Project #3 Microfluidic Platform for Cellular Biomechanics 

Faculty Mentor:  Professor William C. TangBiomedical Engineering

Description:  The mechanical behaviors of cells and small tissues are crucial manisfestation of physiological activities and disease states of the associated cells, but yet are beyond the reach of most conventional biochemical and optical-based investigation approaches. With the applications of microfabrication techniques and microfluidics, powerful tools can be realized to study the intricate relationships between the changes in mechanical properties and the underlying physiological activities of tissues and single cells. This research project aims at investigating the feasibility of microfluidic platforms for studying several cellular mechanical properties including sizes, surface morphology, stiffness, and stickiness and correlating these properties with cellular activities such as mitosis, apoptosis, or metastatic transformation of cancer cells.

Students’ Involvement and Expected Outcomes: Students selected for this research project will study the essential biomechanical properties of a selected cell type, which will be chosen from among those with strong mechanical manifestations including cardiomyocytes, cancer cells, malaria infected red blood cells, and others. The students will learn the research skills needed to design, fabricate, and characterize a microfluidic platform for the chosen cell type.

Prerequisites:  Students with biology background and experience in culturing cells is preferred. Experience in soft lithography is a plus.

 

Project #4 Quantitative Evaluation of Bone Development

Faculty Mentor:  Professor Joyce H. KeyakRadiological Sciences

Description:  A number of diseases and poor nutrition can interfere with bone development, potentially leading to abnormal bone shape and size, poor bone mineralization, and increased risk of bone fracture at any age. Early detection and treatment of these conditions, while the patient is still developing, can help restore normal growth and prevent fractures in childhood and decades later. However, current technology to evaluate bone has limited sensitivity.The goal of this project is to quantify several aspects of normal bone development through analysis of quantitative computed tomography scans of pediatric patients. Ultimately, development of a database for normal bone development will enable diagnosis of abnormal bone development. The results of this work also will be useful for prosecuting cases of child abuse in which bone fractures have occurred.

Students’ Involvement and Expected Outcomes: Students involved in this project will learn about anatomy and biology of bone, bone growth and development, x-ray imaging, x-ray computed tomography scans (CT or CAT scans), and quantitative computed tomography of bone. Students will perform quantitative analyses of bone in pediatric patients, will formulate and test hypotheses, and will interpret the results.

Prerequisites:  Engineering, math or physics major required. Knowledge of unix, computer programming and/or statistics would enhance the experience, but is not required.

 

Project #5 Low Impact Development of Small Scale Water Treatment System

Faculty Mentor:  Professor Chenyang “Sunny” JiangCivil & Environmental Engineering

Description:  Waterborne viral diseases are important burden to human society. A simple and low-cost method to inactivate viruses is needed to treat viral contamination in water for human uses. Nano-titanium dioxide (TiO2) coupled with solar radiation will be investigated to inactivate viruses in different types of water matrix using seeded coliphage. Light transmitting material will be explored as the support for TiO2 attachment.

Students’ Involvement and Expected Outcomes: Students are required to conduct both literature research and field testing. Students will be trained for sampling technique and microbiological methods for viral assays. Probability based analyses will also be taught to students. Students involved in the project are expected to have a comprehensive understanding of the overall project, not only the tasks preformed by them. They are required to make a sound science-based presentation at the end of the research training.

Prerequisites:  The ideal candidate should have fundamental knowledge of chemistry, biology, and preferable environmental microbiology. Statistical courses and math skills are also strongly desired. Students should be willing to participate in field-based research. Biological safety and lab safety training are required at the beginning of the research training.

Recommended Web sites and publications: Water Res. 2011 Jan;45(2):535-44. doi: 10.1016/j.watres.2010.09.012. Epub 2010 Sep 19. Virus inactivation by silver doped titanium dioxide nanoparticles for drinking water treatment. Liga MV, Bryant EL, Colvin VL, Li Q.: http://www.ncbi.nlm.nih.gov/pubmed/20926111

 

Project #6 Quantitative Risk Assessment of Marine Vibrio Related Human Illness

Faculty Mentor:  Professor Chenyang “Sunny” JiangCivil & Environmental Engineering

Description:  Vibrios are gram negative, motile bacteria that can cause diseases in humans. They are commonly found in marine coastal ecosystems where their population changes with seawater temperature, increasing with warmer temperatures and algal blooms, while decreasing with cooler temperatures. Vibrio vulnificus and Vibrio parahaemolyticus were two of the most common vibrio infections reported in the United States between 1997 and 2006, responsible for the most vibrio related hospitalizations and deaths. With the ultimate goal of managing coastal resources and protecting human health, this research will develop a model to estimate the marine vibrio-related human illness. The objectives of this research are to: 1) Quantify the occurrence and distribution of vibrios along west coast of U.S. to generate database for vibrio concentrations and environmental parameters; 2) Perform quantitative microbial risk assessment (QMRA) to determine the human health risk of vibrio illness.

Students’ Involvement and Expected Outcomes: Students are required to conduct both literature research and field sample collection and analysis for Vibrios. Students will be trained for sampling technique and microbiological methods for vibrio isolation and identification. Probability based analyses will also be taught to students. Students involved in the project are expected to have a comprehensive understanding of the overall project, not only the tasks preformed by them. They are required to make a sound science-based presentation at the end of the research training.

Prerequisites:  The ideal candidate should have fundamental knowledge of chemistry, biology, and preferable environmental microbiology. Statistical courses and math skills are also strongly desired. Students should be willing to participate in field-based research. Biological safety and lab safety training are required at the beginning of the research training.

Recommended Web sites and publications: Dickinson, G., K.Y. Lim, S. C. Jiang. 2013. Quantitative Microbial Risk Assessment of Pathogenic Vibrios in Marine Recreational Waters of Southern California. Applied and Environmental Microbiology. 79:294-392.

 

Project #7 Global Satellite-Based Drought Monitoring and Prediction System

Faculty Mentor: Amir AghaKouchak, Civil & Environmental Engineering

Project Description: Drought is a common climatic extreme that often spreads across a large spatial scale and spans over a long period of time. The economic damage of droughts across the United States on average is estimated as $6-8 billion annually. This indicates the importance of reliable drought monitoring, prediction and analysis tools in sustainable water resources management. The objective of this project is to validate and improve the currently available Global Drought Monitoring and Prediction System (GIDMaPS; http://drought.eng.uci.edu/).

Students’ Involvement:  The project activates include: (a) validation and verification of GIDMaPS drought information over different regions (e.g., China); (b) analysis of trends and patterns of droughts across different spatial scales; (c) developing visualization portals to improve the way drought information is communicated globally. Students will develop skills in data processing, time series analysis, computer programing, Java scripting, and web design and development.

Prerequisites:  All students familiar with basics of computer programming and web development are eligible. Relevant majors include: Computer Science; Civil and Environmental Engineering; Hydrology, Climatology.

Recommended Readings & Publications (optional): Here are relevant websites and publications:
http://drought.eng.uci.edu/
http://amir.eng.uci.edu/
Hao Z., AghaKouchak A., 2013, A Nonparametric Multivariate Multi-Index Drought Monitoring Framework, Journal of Hydrometeorology, doi:10.1175/JHM-D-12-0160.1.

 

Project #8 Low Power Design

Faculty Mentor: Professor Fadi J. KurdahiElectrical Engineering & Computer Science

Description:  Power consumption is a major challenge in today’s integrated circuits.

Students’ Involvement and Expected Outcomes: Students selected for this research project will help develop an html interface to existing CAD tools for low power design.

Prerequisites:  Students with Computer Engineering background and experience in html or other web development tools.

 

Project #9 Microcontrollers

Faculty Mentor:  Professor Fadi J. KurdahiElectrical Engineering & Computer Science

Description:  Today there are many cheap microcontroller boards that sport laptop level capabilities and interfaces. Examples include Beaglebone and Raspberry Pi.

Students’ Involvement and Expected Outcomes: Students selected for this research project will study the programming interfaces in microcontrollers. They will use the available microcontroller platforms to bring up an operating system and develop applications promoting sustainability or energy efficiency.

Prerequisites:  Students with Computer Engineering background and experience in computer programming. Experience in using Linux and microcontrollers is a plus.

 

Project #10 Mobile Apps Development

Faculty Mentor:  Professor Fadi J. KurdahiElectrical Engineering & Computer Science

Description:  Mobile programming is becoming a major component in today’s training of Computer and Communication Engineers.

Students’ Involvement and Expected Outcomes: Students selected for this research project will study the Java language and the Eclipse development system. They will develop apps for Android phones/tablets that can make use of the available sensors in a typical platform and perform useful tasks.

Prerequisites:  Students with Computer Engineering background and experience in computer programming. Experience in using JAVA and Eclipse programming environment is a plus.

 

Project #11: Dielectrophoretic Electropolymerization for Particle Entrapment

Faculty Mentor:  Dr. Lawrence Kulinsky,  Mechanical & Aerospace Engineering

Description:  Dielectrophoretic Electropolymerization is a novel technology developed in the BioMEMs research Lab at the University of California, Irvine. This technology is used to attract and entrap microparticles on conductive surfaces to create high specific surface area electrodes. Polymeric microbeads, silicon particles, and biological cells (such as yeast cells) can be used to pattern the surface of the electrodes.

Students’ Involvement and Expected Outcomes: Students will perform experiments in sequential dielectrophoresis and electropolymerization in pyrrole solution with polystyrene microbeads and yeast cells and study parametric conditions (voltage, frequency, flow rate) for optimized patterning of microelectrodes.

Prerequisites:  Consent of Research Mentor.

 

Project #12: Design and Development of Autonomous Vehicles

Faculty Mentor:  Prof. Al FaruqueElectrical Engineering & Computer Science

Description: The technology of autonomous vehicles (e.g. Google self-driving cars) offers the potential to improve energy efficiency, reduce accidents, and save human lives. Autonomous vehicles relies on both sensor and wireless communication technologies to gather the information of surrounding environments. Based on the gathered information, the vehicle is able to understand its position, surround obstacles, and incoming traffics, thus enable the self-driving. In this project, the students will (1) implement a Vehicle to Vehicle (V2V) communication on the experimental vehicles, (2) implement a simple self-drive control algorithm based on the information from the V2V communications on the experimental vehicles.

Current Status of the Project: During 2016, a group of undergraduate students are building the following autonomous car as shown in the following figure.

This small vehicle is capable of decision-making at high-speeds of up to 65 km/h! In order to do this our autonomous car is utilizing the powerful Nvidia Jetson TK1 GPU to perform real-time computer vision calculations using CUDA. Our autonomous car is also utilizing state of the art sensors like the Hokuyo UST-10LX Scanning Laser Rangefinder (LIDAR) which will scan up to 30m around the car for obstacles.

Students’ Involvement and Expected Outcomes: Students involved in this project will learn the basics of V2V communication in autonomous vehicles and the knowledge of control algorithms for autonomous vehicles. Technically, the students will gain the experience of electrical engineering and embedded software programming.

Prerequisites: Engineering and basic knowledge of programming is required. Experience of embedded system design will be useful but not required.

 

Project #13: Development of a Hybrid Energy Storage Prototype

Faculty Mentor:  Prof. Al FaruqueElectrical Engineering & Computer Science

Description: Energy storage is a major component in state-of-the-art smart grids and electric vehicles storing and providing energy temporarily. However, the restricted energy stored in the system is the main bottleneck limiting the duration of the operation, e.g. electric vehicle driving range. Moreover, the energy characteristics of the storage (e.g. power density, energy density) influence the system operating parameters such as energy efficiency and reliability. Recently, hybrid energy storage has been introduced to leverage the energy characteristics of different energy storage (mainly electrical energy) in order to improve the operating parameters. The challenges involved in hybrid energy storage are designing the hardware components and managing the energy among the storage banks.

Current Status of the Project: We have built a battery-powered CPS Testbed in our lab. During this project, we will use this testbed for our experimental purposes during this project.

Students’ Involvement and Expected Outcomes: In this project, the students will comprehend the basics of electrical energy storage, electric vehicle operation, and smart grid operation, in order to analyze their power request for different conditions. Moreover, they will learn energy management methodologies for monitoring and controlling hybrid energy systems. Meanwhile, the students are required to deploy a table-scale prototype and test bed for the hybrid energy storage and its corresponding management system.

Prerequisites: Student with Electrical and Computer Engineering background and experience in programming and hardware design. Experience in system modeling and simulation (e.g. using MATLAB/Simulink) is a plus.

 

Project #14: Data-Driven Security Analysis for DNA Synthesizing

Faculty Mentor:  Prof. Al Faruque,  Electrical Engineering & Computer Science

Description: Any living organism’s development, functionality, and growth are the result of executing genetic instructions embedded in DNA molecules inside the cells. Currently, one of the most controversial capabilities of the scientist is to artificially synthesize DNA molecules. The enabling technology for this advancement is made through a tight integration of cyber and physical components. This integration poses various security vulnerability which can result in loss of intellectual property or distortion of integrity of the synthesized DNA molecules. In this project, students are going to evaluate such vulnerabilities through analysis of side-channel data. The main objectives of the research are (1) to explore various data that can be collected through the different sensors mounted around DNA synthesizer machine and develop algorithms to fuse them for feature extraction, (2) to design machine learning algorithms to estimate the state of the system for security assurance.

Current Status of the Project: The similar security analysis has been conducted on a different application. Our security-related work on 3D-printer received worldwide coverage. For details see https://www.youtube.com/watch?v=DlOHnp_gpGs&feature=youtu.be. In this work, we were able to recreate an object just from the sound the 3D-priner makes.

Students’ Involvement and Expected Outcomes: Students will conduct research on digital signal processing, data fusion algorithms, and various machine learning algorithms. They will understand the DNA synthesis mechanisms and develop skills in system forensics through data analysis.

Prerequisites: Strong understanding of basic programming language (C, C++) and experience of developing a project with Matlab or Python is required. Basic knowledge of digital signal processing and machine learning is required. Knowledge of DNA synthesizers would enhance the experience, but is not required.

 

Project #15: Software Defined Radio

Faculty Mentor: Prof. Ahmed EltawilElectrical Engineering & Computer Science

Description: A major obstacle facing most radio platforms is the rigid nature of the current radio platforms. At design time, all radio parameters are hard wired into the device and can never be adapted to optimally serve a specific purpose. Software Defined Radio (SDR) is a new technology that aims to change this reality by combining a collection of software modules, such that the waveforms transmitted and received are defined by software, therefore allowing unprecedented flexibility in adapting the radio platform to the current task at hand. This project requires the design, simulation and implementation of a complete SDR framework. A case study of a simple Frequency Modulated (FM) radio will used to showcase the flexibility of the SDR solution. The functionality of the SDR framework will be tested on actual hardware utilizing a Personal Computer (PC) to run the software related tasks and an external board that receives the signal at radio frequency, down-converts it to a lower intermediate frequency, and finally presents digitized samples for processing by the PC. Full simulation and implementation results are expected, complemented by a thorough discussion of the design process.

Students’ Involvement and Expected Outcomes:
1- Study: Identifying and understanding major radio blocks, Understanding the basics of frequency modulation.
2- Analysis: Studying tradeoffs of different FM architectures, Estimating performance of each topology.
3- Implementation: Using the GNU radio framework with USRP to implement a working FM radio.
The project involves (1) FM demodulation in matlab (2) Implementation of FM demodulation using GNU radio and USRP.

Design Tool Used: Matlab, Python, Scripting, GNU radio and hardware implementation on the Universal Software Radio Peripheral (USRP) board.

Prerequisites:  Consent of Research Mentor.

 

Project #16: Solar Panel and Tracker

Faculty Mentor: Prof. Ahmed EltawilElectrical Engineering & Computer Science

Description: In this project, students will first understand the importance of renewable energy; mainly solar energy. To harvest the solar energy, photocells are employed to convert the solar energy into electrical energy. However, to maximize the gain of the conversion, the photocells need to face the sun (light source). This requires placing the photocells on a plate that can be rotated in 3 dimensional space. Students will be required to build a prototype using the Arduino board, Light Dependent Resistors (LDR’s) and stepper motors.

Students’ Involvement and Expected Outcomes:
1- Study: Understanding how solar cells work, Energy conversion and efficiency, Characteristics of photo cells (photo resistors).
2- Implementation: Interfacing photocells mounted on a stepper motor to the Raspberry Pi board, Controlling the rotation of the servo motor.

Design Tool Used: C, MATLAB programming, Raspberry programming.

Prerequisites:  Consent of Research Mentor.

 

Project #17: Camera-based image capture and processing

Faculty Mentor: Prof. Ahmed EltawilElectrical Engineering & Computer Science

Description: The project is divided into two parts. In the first part, students will first learn the basic concepts about image and image processing. Then, they will learn how to use MATLAB to read, analyze and perform fundamental processing on images. The second part of the project involves building a simple prototype using Raspberry Pi board and a webcam/camera. The camera will take pictures which will be analyzed with MATLAB. The camera will be mounted on a servo motor where its rotation is controlled by a Micro-controller of the Raspberry Pi board.

Students’ Involvement and Expected Outcomes:
1- Study: Introduction to MATLAB programming, Understanding the basics of images and pixels format, Digital Signal Processing techniques for images.
2- Analysis: Image filtering and compression, Identifying objects in the image.
3- Implementation: Interfacing web-cam to a servo motor and then to the Raspberry Pi board, Controlling the rotation of the servo motor, Transferring images to PC to analyze/process with MATLAB.

Design Tool Used: C, MATLAB programming, Raspberry programming.

Prerequisites:  Consent of Research Mentor.

 

Project #18: Sensor based telemetry

Faculty Mentor: Prof. Ahmed EltawilElectrical Engineering & Computer Science

Description: The recent progress in electronics and telecommunications has made remote telemetry systems very reliable and cost effective. In this project, students will learn the structure of telemetry systems. Based on that, they will build a prototype weather telemetry system suing the Raspberry boards which is integrated with a few sensors. The processing unit on the raspberry board will collect the sensor data periodically and display these results on an LCD display. Also, these results will be transmitted over WIFI to the central processing unit.

Students’ Involvement and Expected Outcomes:
1- Study: Understanding how telemetry system works, Understanding how sensors work
2- Implementation: Interfacing temperature and humidity sensors and LCD to the Raspberry board, Collecting the measured data, analyze it and send messages to the central unit.

Design Tool Used: C, MATLAB programming, Raspberry programming.

Prerequisites:  Consent of Research Mentor.

 

Project #19: Data-Driven Approaches for Analyzing the Manufacturing IoT Systems in a 3D-Printer

Faculty Mentor: Professor Al FaruqueElectrical Engineering & Computer Science

Description: Today’s smart manufacturing system has evolved with the capability to collect large amount of data from different sensors. As the demand for quality increases, it is imperative to leverage multiple data in monitoring and estimating (through various machine learning algorithms) the system performance for process/quality control. This project will focus on additive manufacturing systems (3D-printing), which have gained wide acceptance in many sectors for manufacturing. The main objectives of the research are (1) to explore various data that can be collected through the additive manufacturing system (3D-printing) and develop algorithms to fuse them for feature extraction, (2) to design machine learning algorithms to estimate the performance of the system for process/quality control.

Current Status of the Project: Our security-related work on 3D-printer received worldwide coverage. For details see https://www.youtube.com/watch?v=DIOHnp_gpGs&t=5s. In this work, we were able to recreate an object just from the sound the 3D-priner makes.

Students’ Involvement and Expected Outcomes:
Students will conduct research on digital signal processing, data fusion algorithms, and various machine learning algorithms. They will understand the framework of additive manufacturing system and develop skills in system forensics through data analysis.

Prerequisites: Strong understanding of basic programming language (C, C++) and Matlab is required. Basic knowledge of digital signal processing and machine learning is required. Knowledge of additive manufacturing system would enhance the experience, but is not required.

 

Project #20: Development of Optical Imaging Technology for Biomedical Applications

Faculty Mentor: Zhongping Chen, Biomedical Engineering

Description: Optical coherence tomography (OCT) is one of the fastest growing areas of biomedical optics with many potential clinical applications. Research areas that are of particular interests include the development of optical coherence tomography (OCT), Doppler optical coherence tomography, optical coherence elastography, nonlinear optical microendoscopy, and photoacoustic tomography for imaging tissue structure and physiology. The technology will be translated to clinical applications for the diagnosis and management of cardiovascular diseases and cancers.

Students’ Involvement and Expected Outcomes:
Students selected for this research project will study essential optical imaging techniques, participate in the construction of optical imaging systems and miniature endoscopic probes, conduct experiments to collect imaging data, and develop software programs for image processing.

Prerequisites: Students with an electrical engineering background is preferred. Experience in programming and optics is a plus.

 

Project #21: Spine-Rad Brachytherapy Bone Cement

Faculty Mentor: Professor Joyce H. KeyakRadiological Sciences

Description: Spinal metastases are a common manifestation of many cancers such as those originating in the prostate, breast, lung, kidney, and thyroid. Approximately 200,000 people with spinal metastases die each year in the United States. These metastases are painful, reduce bone strength, and can lead to vertebral collapse and serious neurological complications. Conventional treatment of vertebral metastases involves external beam radiation therapy (EBRT) to slow tumor progression and potentially alleviate pain, although EBRT can further weaken bone and lead to vertebral fracture. Vertebroplasty or kyphoplasty (percutaneous injection of bone cement into the vertebral body) can be performed prior to EBRT to restore bone strength and provide immediate marked or complete pain relief in 50% to 85% of cases. Although this approach is an improvement over EBRT alone, a major shortcoming of EBRT remains: EBRT irradiates the spinal cord, limiting the dose that can be delivered to tumors
To address the limitations of conventional treatments for vertebral body metastases, UCI researchers have developed Spine-RadTM Brachytherapy Bone Cement which consists of an FDA-approved bone cement that has been mixed with an insoluble radioactive powder, P-32-hydroxyapatite (P-32-HA). Spine-Rad Cement would be delivered percutaneously (through a needle passing through the skin) to the vertebral body to restore bone strength and provide pain relief while simultaneously providing local radiation (brachytherapy) to the tumors. Dosimetry studies have shown that, because P-32 is a beta emitter, a high dose can be delivered to tumors nearby while virtually eliminating radiation to the spinal cord. This single procedure would also be more convenient for patients than multiple EBRT treatment sessions and would cause fewer side effects because radiation would travel only a short distance in the body.

Students’ Involvement and Expected Outcomes:
A student working on this project would have the opportunity to be involved in a range of activities related to radiation therapy. The student would gain an understanding of how radioisotopes are produced, how to safely handle radioactive samples and how to evaluate radiation dose. Furthermore, the student would gain experience in how to prepare sterile samples for treatment. At the end of the program the student is expected to have gained broad insight in the field of radiation therapy and nuclear medicine, including hands on experience, and should be well poised to continue and deepen his or her knowledge in a specific area related to cancer treatment by medical isotopes.

Prerequisites/Student Eligibility: Engineering, Chemistry or Physics major required. Students are expected to have taken basic chemistry, math and physics courses. Engineering students with experience designing and fabricating devices (e.g. machining experience) are encouraged. Previous lab experience in chemistry or similar settings, either from courses or from individual research projects, is beneficial.

 

Project #22: DietMate- A Multimodal Diet Monitoring System

Faculty Mentor: Professor Al FaruqueElectrical Engineering & Computer Science

Description: Healthcare has always been the key concern for everyone around the world. Significant amount of resources are invested to improve the medical treatments and mitigating the effect of various diseases. However, the preventive healthcare has always been neglected so far. Preventive healthcare allows for maintaining a balanced diet and overall a healthy life style by monitoring regular food intake and daily activities. Though there are lots of commercial devices available for monitoring daily activities but very less attention has been paid for monitoring the regular food intake. This project will focus on improving the techniques for diet monitoring. The main objectives of the research are- 1) Using piezoelectric sensors around the throat to gather data for different eating activities like swallowing, chewing etc. 2) Also use acoustic methods like throat microphone to obtain data. 3) Data generated from the above two modalities will be used to distinguish various eating activities as well as the type of food using various machine learning algorithms.

Current Status of the Project: Currently our project is in the design phase where we plan to develop a smart collar with a bow tie. The bow tie will be equipped with all the necessary devices like piezoelectric sensor and microphone for data collection. Data collected from this modalities will be sent to a cloud where different data analysis algorithm will be implemented using machine learning.

Final decision of the analysis will be displayed in the mobile interface. Though the design is under development however the expected prototype will look like given figure.

Students’ Involvement and Expected Outcomes: Students will conduct research on embedded systems, digital signal processing, data fusion algorithms, and various machine learning algorithms. They will understand the framework of Health IoT system and develop skills in system forensics through data analysis.

Prerequisites/Student Eligibility: Strong understanding of basic programming language (C, C++) and Matlab is required. Basic knowledge of digital signal processing, hardware design and machine learning is required. Knowledge of coding in android platform is a plus, but is not required.