ECE
ECE
ECE ECE

2018 SURE/SROP Research Projects: Electrical and Computer Engineering (ECE)

Directions: Below are listed the most recent descriptions of 2018 SURE and SROP projects available in Electrical and Computer Engineering (ECE). Please consider this list carefully before applying to the SURE or SROP program. You are welcome to contact faculty if you have additional, specific questions regarding these projects. 

*IMPORTANT*: In addition to their online application, SURE applicants for ECE projects must also submit a resume and statement explaining their interest in and qualifications for the project that most interests them, including why they want to work on the project, the relevant skills they bring, and what they expect from their experience. The statement should be no longer than one page (12 point font and 1” margins) and must be uploaded in “other” at the bottom of the online application. Applications without this information may not be considered. Please include your name and UMID on all documents submitted.

SROP applicants for ECE projects should follow the specific directions outlined in the online application.


 

Research Area
Project Number
Applied Electromagnetics & RF Circuits
Communications & Networks
4, 5, 32, 33, 34
Computer Vision
Control Systems
1, 23, 24
Embedded Systems
35, 36, 37, 38, 39
Engineering Education Research
Integrated Circuits & VLSI
3, 29, 30, 40
MEMS & Microsystems
2, 21, 22
Optics & Photonics
10, 26, 27, 28
Power & Energy
8, 9, 29, 30
Robotics
12, 13, 14, 15
Signal & Image Processing and Machine Learning
11, 31, 32, 33
Solid State & Nanotechnology
6, 7, 18, 19, 20

 


ECE Project 1: Privacy and Security of Cyber and Cyber-Physical Control Systems

Faculty Mentor: Stephane Lafortune (stephane@umich.edu)

Prerequisites: Programming experience in C, C++ and/or Java required.

Description: We are developing methodologies for (i) privacy enforcement in cyber systems and (ii) detection and mitigation of sensor and actuator attacks in cyber-physical control systems. The student intern will work on implementing and testing the algorithmic procedures of these methodologies, either as stand-alone procedures or as part of our existing M-DES software tools (see: https://gitlab.eecs.umich.edu/M-DES-tools). The student will also work on the development of case studies to test these algorithms, as well as on visualization tools for illustrating these case studies. The student will work in close collaboration with graduate students and postdoctoral researchers.

Please contact Prof. Lafortune is you are interested.

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ECE Project 2:  Data-driven high-throughput single-cell morphological, behavioral, and genotypic analysis

Faculty Mentor: Yu-Chih Chen (yuchchen@umich.edu)

Prerequisites:

1. Patience and carefulness in doing experiments.
2. Good hand skill for doing experiments.
3. Basic skills in using Excel for data analysis.
4. Basic understanding in statistics such as hypothesis testing.
5. The capability to use MATLAB and write simple scripts for automatic
data analysis.

Description: Cell heterogeneity is a new challenge in cancer therapy. Each cell in the heterogeneous population has its own unique property, and thus responds differently to the same drug, making cancer treatment difficult and complicated. Therefore, it is important to understand the heterogeneity characteristics of cells in drug assays. Still most assays measure the average behavior over large numbers of cells with an underline assumption that all cells are identical, which can lead to incorrect, imprecise results. To understand the behavior of each cell in heterogeneous groups, we should be able to provide high-throughput assays at single cell resolution, enlightening individual properties of each cell rather than the average behavior of the bulk tumor. Using microfluidic technologies, we can reliably monitor 10,000 single cells on-chip. In addition to cell behaviors, we are investigating the cellular heterogeneity in gene expression using Next Generation Sequencing (NGS). We also extract cell morphological features to predict its properties using random decision forest (RDF) and Convolutional neural network (CNN). Through this integrated approach, we will identify and validate novel genes and pathways, providing new therapeutic targets to eliminate cancer cells and ultimately leading to improved outcomes for patients.

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ECE Project 3: Ultra-low Power Circuit Design for Millimeter Sized Sensor Nodes

Faculty Mentor: David Blaauw (blaauw@umich.edu)

Prerequisites: Introductory circuits course (EECS 312) and VLSI design course (EECS 427) is strongly preferred.

Description: We are developing sensor nodes that have a size of 1 millimeter or less.  The sensor nodes contain a small microprocessor, a transducer, such as pressure sensor or imager, a power source such as a battery and radio circuits. Reducing a sensor processor node to this minute size allows the sensor node to be used in a host of new and interesting applications, including implanted biomedical applications and monitoring of the environment.  The work will depend on the background of the candidate and can include testing and diagnosis of fabricated chips, help with circuit design for processor, power management, and sensors, or software development for sensor applications.

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ECE Project 4: Pervasive IoT Applications using Battery-less Smart RFIDs

Faculty Mentor: Hun-Seok Kim (hunseok@umich.edu)

Prerequisites: Backgrounds in signal processing and/or wireless communication. Familiarity with Verilog, FPGA programming or embedded programming is not required but a strong plus.

Description: This program investigates new IoT applications using ubiquitously deployed battery-less RFID tags. Potential new applications include indoor localization, object identification, room occupancy detection, and gesture recognition. Commercially available RFIDs offer very limited capability because of stringent power constraints. Thanks to ultra-low power circuit techniques developed in Michigan Circuits Integrated Circuits Labs, more intelligent RFID tags have become feasible opening up new opportunities to develop novel IoT applications using passive RFIDs that were previously infeasible. SURE students involved in this project will have opportunities to model and develop a prototype system for new RFID based IoT applications. 

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ECE Project 5: Near-Zero Power Consumption Machine Learning Systems

Faculty Mentor: Hun-Seok Kim (hunseok@umich.edu)

Prerequisites: Backgrounds in signal processing and/or wireless communication. Familiarity with digital / analog integrated circuits, Verilog, FPGA programming or embedded programming is not required but a strong plus.

Description: This program investigates near-zero (<100s nW) power consumption machine learning systems using acoustic and other sensing modalities. The main goal of the project is to develop an intelligent machine learning system via algorithm – architecture cross-layer optimizations. Applications include voice activity detection, acoustic event detection, and structural health monitoring. SURE students involved in this project will have opportunities to work with graduate student mentors to model and develop a prototype system for new near-zero (<100s nW) power machine learning systems. 

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ECE Project 6: Optical Hall Characterization of Thin Film Semiconductors

Faculty Mentor: Becky Peterson (blpeters@umich.edu)

Prerequisites: EECS 215/216 or EECS 314 or equivalent

Description: In this project, the SURE student will perform Hall measurements on thin film semiconductors under optical illumination. By using light to excite electrons-hole pairs, we can probe electronic states within the bandgap that are not normally accessible during dark measurements. The project will involve electrical testing and data analysis, some coding to expedite testing, and some sample preparation using soldering to form contacts. The student should be comfortable working independently in a test lab. Previous LabView experience and completion of EECS 320 are a plus, but are not mandatory.

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ECE Project 7: Printed Electronics

Faculty Mentor: Becky Peterson (blpeters@umich.edu)

Prerequisites: EECS 215 or 314 and one semester of U-M chemistry or equivalent AP credit. The student should enjoy hands-on lab work, and show good attention to detail.

Description: High-k dielectrics - electrical insulators with relative permittivity greater than silicon dioxide - have been used for the past 15 years to increase the ON current of silicon MOSFETs. The goal of this project is to use these materials with new, non-silicon semiconductors to build high speed transistors. The project involves fabrication and characterization of new thin films using equipment in the Lurie Nanofabrication Facility, Michigan Center for Materials Characterization, and in PetersonLab. The student will have a graduate student mentor, and will develop knowledge and skills in materials science, chemistry or chemical engineering, or electrical engineering.

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ECE Project 8: Improving power system sustainability, reliability, and stability using flexible electric loads and energy storage

Faculty Mentor: Johanna Mathieu (jlmath@umich.edu)

Prerequisites: MATLAB, EECS 216, experience with optimization, controls, or simulation a plus

Description: We are developing new algorithms to use flexible electric loads like air conditioners and refrigerators and energy storage like batteries to improve power system reliability and stability, and increase the ability of the electric grid to accommodate renewable energy sources like wind and solar power. The student will learn basic load models, storage models, power system models, and control/optimization approaches; contribute to the development of these models/approaches; and run simulations to evaluate the approaches.

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ECE Project 9: Using University of Michigan Buildings as Batteries

Faculty Mentor: Johanna Mathieu (jlmath@umich.edu)

Prerequisites: MATLAB, Excel, experience with data analysis a plus

Description: We are doing experiments on University of Michigan building to determine how well they could help the power grid accommodate more renewable energy sources like wind and solar power. More information is available here: https://news.engin.umich.edu/2017/09/using-university-of-michigan-buildings-as-batteries/. The student will help collect and analyze data and/or develop building models to explain the experimental results.

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ECE Project 10: Subwavelength Optics for Infrared Imaging

Faculty Mentor: Jamie Phillips (jphilli@umich.edu)

Prerequisites: EECS 230 and EECS 334

Description: Imaging in the long wavelength infrared (LWIR, 8-12 microns) provides capabilities for thermal imaging and chemical identification, impacting applications including defense, security, medicine, and climate studies. The next generation of infrared imaging systems desire hyperspectral capabilities, where the spectrum of infrared wavelengths can be determined at each pixel in an imaging array. We are developing optical sub-wavelength gratings to enable hyperspectral capabilities in next-generation imaging systems. This project will involve the optical simulation of these optical gratings using COMSOL Multiphysics and/or RCWA; and optical measurement of gratings using Fourier Transform Infrared Spectroscopy (FTIR).

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ECE Project 11: Information processing using artificial neural network hardware

Faculty Mentor: Wei Lu (wluee@umich.edu)

Prerequisites: Knowledge of semiconductor devices and digital circuit design

Description: We are developing new circuits for efficient computing and information storage based on emerging devices (i.e. memristors that are resistive devices with an inherent memory). In this project the student will work with a team that builds artificial neural networks using memristor arrays. The goal is to build a hardware system that can extract features from complex inputs including images and videos and other sensory data through a machine learning algorithm, and analyze the data efficiently. Depending on the student’s expertise, the project may involve helping device and circuit measurements, building and programming the test system.

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ECE Project 12: Tracking Cloth for Deformable Object Manipulation

Faculty Mentor: Dmitry Berenson (berenson@umich.edu)

Prerequisites: Significant programming experience (e.g. EECS 281). Experience with computer vision and/or 3D point-cloud processing.

Description: In order to manipulate deformable objects such as cloth we need to estimate the current configuration of the object from sensor data. This project will focus on tracking the state of a cloth as it is being manipulated using data from a Kinect sensor. A key question will be how to address occlusions, i.e. what can we infer about parts of the cloth we can’t see?

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ECE Project 13: Manipulation of objects for active perception

Faculty Mentor: Dmitry Berenson (berenson@umich.edu)

Prerequisites: Significant programming experience (e.g. EECS 281). 

Description: We are studying how robots can interact with their environments to get more information about objects in complex arranges (e.g. in piles or stacks). For this project the student will help gather data and develop information-gathering motions for a robot arm sorting through a pile of objects such as clothes or blocks. The student may also contribute to the development of algorithms that can autonomously decide which information-gathering motion is best to do next.

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ECE Project 14: Parallelization of Library-based Planning

Faculty Mentor: Dmitry Berenson (berenson@umich.edu)

Prerequisites: Significant programming experience (e.g. EECS 281). Experience with parallel processing.

Description: Our group has been developing motion planning methods that use previous experience to speed up planning. This requires computing how well a previous plan fits in a new environment and how applicable it is for a given task. This project will focus on parallelizing the evaluation of previous plans to determine which is the best fit to the current planning query. 

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ECE Project 15: Graspable Fixture Detection for Humanoid Navigation

Faculty Mentor: Dmitry Berenson (berenson@umich.edu)

Prerequisites: Significant programming experience (e.g. EECS 281). Experience with computer vision and/or 3D point-cloud processing.

Description: Humanoid robots will need to navigate environments subject to unexpected disturbances. One way to do that is to use the robot’s hands to hold on to handrails or other graspable fixtures in the environment. This project will focus on perception methods to identify such fixtures from point-cloud data (e.g. coming from a Kinect sensor).

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ECE Project 16: Generating Holograms with Spatial Light Modulators

Faculty Mentor: Anthony Grbic (agrbic@umich.edu)

Prerequisites: EECS 230 required. EECS 330 or EECS 334 preferred. Student should have knowledge of time-harmonic electromagnetic fields (plane waves).

Description: The student researcher will use a spatial light modulator (SLM) to generate visible light holograms with prescribed phase and intensity distributions. SLMs are computer-programmable devices that can modulate the phase of an incident beam of light. The project will explore the use of SLMs for: the generation of 2D and 3D holographic images for display applications, the formation of cylindrical vector beams (non-diffracting beams in the Fresnel zone), and optical beam steering and shaping.

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ECE Project 17: Wireless Charging

Faculty Mentor: Anthony Grbic (agrbic@umich.edu)

Prerequisites: EECS 230 required. EECS 311 preferred.

Description: This project involves hands-on experience in the emerging field of wireless power transmission. The student will learn the fundamentals of wireless non-radiative power transfer from both circuit and electromagnetic field (EM) perspectives. They will characterize, design and test new wireless power transmission system components and systems. The work will include EM field analysis and resonator design, RF circuit simulation and design, and RF measurement/testing.

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ECE Project 18: Nanowire deep ultraviolet light-emitting devices

Faculty Mentor: Zetian Mi (ztmi@umich.edu)

Prerequisites: Background in electronics, optics and materials science. Strong experimental experience is preferred.

Description: Ultraviolet light sources are crucial for applications ranging from water purification to biochemical sensing. To date, however, the realization of high efficiency ultraviolet semiconductor optoelectronic devices including light-emitting diodes and lasers remains a challenge. This project is related to the development of nanostructures such as nanowires to achieve such solid-state light sources. The student will work with graduate student mentors on the epitaxial growth, fabrication, characterization and testing of these devices; and is expected to deliver a detailed report on the current status of deep ultraviolet light sources and the progress that is made.

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ECE Project 19: Artificial photosynthesis and solar fuels generation

Faculty Mentor: Zetian Mi (ztmi@umich.edu)

Prerequisites: Background in Electrical Engineering, Chemical Engineering or Materials Science.

Description: Artificial photosynthesis and solar fuels production has emerged one of the most promising approaches to address the energy and environment challenge we face today. This project involves the design of nanowire photocatalyst/photoelectrode and extensive photoelectrochemical and solar water splitting studies. This project will help develop interdisciplinary knowledge and skill sets in electrical engineering, materials science and chemistry. The student will have a graduate student mentor to prepare nanowires electrode, conduct measurement, and improve the device performance.

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ECE Project 20: Full-color nanowire lasers for lighting, display and imaging applications

Faculty Mentor: Zetian Mi (ztmi@umich.edu)

Prerequisites: Background in Optics and Materials Science

Description: High efficiency multi-color lasers monolithically integrated on a single chip are highly desired for future smart lighting, full-color display, and imaging applications. With the use of selective area epitaxy, the emission wavelengths of InGaN/GaN nanowires can be tuned across nearly the entire visible spectrum on a single chip by varying nanowire size and compositions. This project involves the design and optical and structural characterization of nanowire photonic crystal structures and the demonstration of surface-emitting lasers. The student will work with a graduate student mentor on optical modeling and device characterization.

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ECE Project 21: The Investigation of Cancer Stem Cell Development Using Single Cell Microfluidics

Faculty Mentor: Euisik Yoon (esyoon@umich.edu)

Prerequisites: 1. Patience and carefulness in doing experiments.
2. Good hand skill for doing experiments.
3. Basic skills in using Excel for data analysis.
4. Basic understanding in statistics such as hypothesis testing.
5. The capability to use MATLAB and write simple scripts for automatic data analysis.

Description: Cell heterogeneity is a new challenge in cancer therapy. Each cell in the heterogeneous population has its own unique property, and thus responds differently to the same drug, making cancer treatment difficult and complicated. Therefore, it is important to understand the heterogeneity characteristics of cells in drug assays. Still most assays measure the average behavior over large numbers of cells with an underline assumption that all cells are identical, which can lead to incorrect, imprecise results. To understand the behavior of each cell in heterogeneous groups, we should be able to provide high-throughput assays at single cell resolution, enlightening individual properties of each cell rather than the average behavior of the bulk tumor. In this work, we focus on studying the self-renewal and differentiation of cancer stem cells. Using microfluidic technologies, we can isolate and culture an array of 10k single cancer stem cells for several days, and observe their developments on-chip. The proliferation rate and self-renewal/differentiation can be measured using fluorescent imaging.

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ECE Project 22: Data Storage for High-speed Brain Research

Faculty Mentor: Euisik Yoon (esyoon@umich.edu)

Prerequisites: Background in Electrical Circuits and Optics. Advanced courses in such areas as embedded controls, or electromagnetics are desired. A demonstrated interest in cross-disciplinary projects is also a plus.

Description: We are looking for a highly motivated undergraduate to advance electrical circuit technology in the context of brain research. Our current project uses optical light stimulation, high-speed electrical recordings, and custom ICs. In the neuroscience experiments, the amount of data streaming out of a rodent brain is too much to transfer real-time and hence we need to write most of the information to SRAM in a small rodent backpack assembly. This system needs to be developed using commercially available parts and protocols.

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ECE Project 23:  Correct-by-construction control for autonomous driving and driver-assistance systems

Faculty Mentor: Necmiye Ozay (necmiye@umich.edu)

Prerequisites: Strong analytical skills and knowledge of linear algebra. Experience with MATLAB, Python and ROS (www.ros.org), or otherwise enough software engineering knowledge that suggests learning other languages, environments, etc. will not be difficult. At least elementary experience of working in Unix-like environments. Familiarity with git is not required but considered useful.

Description: A plethora of driver convenience and safety automation systems are being introduced into production vehicles, such as electronic stability control, adaptive cruise control, lane keeping, and obstacle avoidance. This project will investigate the use of correct-by-construction control protocol synthesis techniques [1] in automotive active safety systems in order to facilitate easy development and deployment of new automated car safety features. In particular, some of the controllers will be implemented on a scaled car and a driving simulator in our lab. New control functionality will also be developed.

[1] P. Nilsson, O. Hussien, Y. Chen, A. Balkan, M. Rungger, A. D. Ames, J. W. Grizzle, N. Ozay, H. Peng, and P. Tabuada, “Preliminary Results on Correct-by-Construction Control Software Synthesis for Adaptive Cruise Control”, IEEE Conference on Decision and Control, 2014.http://web.eecs.umich.edu/~necmiye/n+_cdc14.html

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ECE Project 24: Implementing control synthesis algorithms in TuLiP toolbox

Faculty Mentor: Necmiye Ozay (necmiye@umich.edu)

Prerequisites: Strong analytical and programming skills. Experience with git. Basic knowledge of code unit testing, discrete math, graph theory and optimization would be useful.

Description: Correct-by-construction controller synthesis is the use of a computer to automatically construct a controller such that when implemented, the resulting closed-loop system satisfies some a priori given specification. Such synthesis relies on algorithms that typically scale badly with system dimension: they suffer from the curse of dimensionality. The primary goal of this project is to implement a recently developed correct-by-construction method and integrate it into the Python toolbox TuLiP (https://tulip-control.sourceforge.io/). The method alleviates the curse of dimensionality by abstracting the state space and doing incremental abstraction refinement only in “promising” areas, thus potentially eliminating the need to analyze large swaths of the state space.

Further reading:
http://ieeexplore.ieee.org/document/7040368/?arnumber=7040368
http://ieeexplore.ieee.org/document/7852282/

Key concepts: Python development (previous experience preferred), code unit testing, algorithms, git, system abstraction, linear temporal logic

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ECE Project 25:  Teaching and Learning in Engineering

Faculty Mentor: Cindy Finelli (cfinelli@umich.edu)

Prerequisites: None.

Description: This project is also listed under Engineering Education Research as "EER Project: Teaching and Learning in Engineering." Dr. Finelli’s research investigates different factors—such as the physical classroom space, faculty teaching practices, or participation in co-curricular activities—that impact student learning and success in engineering. Depending on student interest and project needs, the research may focus on one of three topics: (1) how a flexible classroom space affects faculty teaching and student learning; (2) student resistance to innovative teaching practices and ways for faculty to alleviate it; and (3) who participates in engineering co-curricular activities, how they decide to participate, and what benefits are conferred. Responsibilities for the student include: (a) analyzing survey, interview, and observational data through qualitative and quantitative means, (b) managing data using Excel and other software packages, (c) communicating outcomes in verbal and written form, and (d) assisting in the development and delivery of faculty professional development activities. The student will work closely with Dr. Finelli and may also be part of a team of researchers from engineering education and other disciplines. Interested students should contact Dr. Finelli (cfinelli@umich.edu) for more information or to apply.

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ECE Project 26: Thin Film GaAs Solar Cells and Solar Trackers

Faculty Mentor: Stephen Forrest (stevefor@umich.edu)

Prerequisites: Background in Optics and Materials Science.

Description: We are developing a method to fabricate extremely lightweight and high efficiency, thin film gallium arsenide solar cells. These flexible cells can be attached to mini (~2 cm3) solar concentrators and tracking mechanisms based on kirigami or other concepts to reduce the cost of solar power generation for mobile and even rooftop applications.  The student will work with a graduate student mentor on topics ranging from optical modeling and semiconductor device fabrication, to device characterization in realistic environments (e.g. outdoor exposure to sunlight) to understand the limits of our approaches and to work on improvements.

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ECE Project 27: Lifetime of Organic Light Emitting Devices

Faculty Mentor: Stephen Forrest (stevefor@umich.edu)

Prerequisites: Background in Electrical Circuits, Optics and Materials Science.

Description: Today, phosphorescent organic light emitting diodes (PHOLEDs) are the backbone technology supporting the OLED display industry that provides smart phones, tablets, and televisions to over 1 billion consumers worldwide. However, there are numerous challenges facing their further development; chief among them is the limited lifetime of the blue emitting PHOLED.  Our project focuses on understanding and overcoming the fundamental limits to blue PHOLED lifetime. The student will work with a team of graduate students to measure the emitted light intensity from populations of blue PHOLEDs fabricated using structures testing different approaches for extending device operational lifetime. Extensive fabrication of devices and their characterization are among many of the areas to be pursued.

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ECE Project 28: Roll-to-Roll Fabrication of Reliable Thin Film Organic Solar Cells

Faculty Mentor: Stephen Forrest (stevefor@umich.edu)

Prerequisites: Background in Materials Science.

Description: Today, phosphorescent organic light emitting diodes (PHOLEDs) are the backbone technology supporting the OLED display industry that provides smart phones, tablets, and televisions to over 1 billion consumers worldwide. However, there are numerous challenges facing their further development; chief among them is the limited lifetime of the blue emitting PHOLED.  Our project focuses on understanding and overcoming the fundamental limits to blue PHOLED lifetime. The student will work with a team of graduate students to measure the emitted light intensity from populations of blue PHOLEDs fabricated using structures testing different approaches for extending device operational lifetime. Extensive fabrication of devices and their characterization are among many of the areas to be pursued.

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ECE Project 29: Designing and Building Labs and Demos for Teaching Power Electronics

Faculty Mentor: Al Avestruz (avestruz@umich.edu)

Prerequisites: Basic Circuits (EECS 215), Basic Signals and Systems (EECS 216), Basic Electromagnetics (EECS 230). Familiarity with Circuit Simulation (SPICE). Power Electronics (EECS 418), Electronic Circuits (EECS 311), or other advanced circuits classes a plus, but not required. Some experience with PC Board design (e.g. Altium or Eagle) and fabrication a plus. Familiarity with Embedded Systems or Microcontrollers a plus, but not required. Familiarity with 3d printing/prototyping a plus, but not required. Enthusiasm and Personal Energy for Building and Learning definitely a requirement!!

Description: We will explore, design, and build power electronics that will be used as demos and labs for future courses. Expect a thoroughly hands-on learning experience in building power electronic systems.

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ECE Project 30: Precision Measurement of High Frequency Power Inductors

Faculty Mentor: Al Avestruz (avestruz@umich.edu)

Prerequisites: Basic Circuits (EECS 215), Basic Signals and Systems (EECS 216), Basic Electromagnetics (EECS 230), and MATLAB. Familiarity with MATLAB and Circuit Simulation (SPICE). Electronic Circuits (EECS 311) or other advanced circuits classes a plus, but not required. Some experience with PC Board design (e.g. Altium or Eagle) and fabrication a plus. Familiarity with Embedded Systems or Microcontrollers a plus, but not required. Familiarity with 3d printing/prototyping a plus, but not required. Enthusiasm and Personal Energy for Building and Learning definitely a requirement!!

Description: As power electronics operate at higher frequencies, especially with the newest semiconductor devices, power inductors have become the bottleneck in the most efficient and highest density designs.  We will explore, design, build, and test a number of methods and circuits to measure power inductors, which will then apply to characterize inductor designs and core materials.

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ECE Project 31: Learning-based optimization of new caching algorithm

Faculty Mentor: Vijay Subramanian (vgsubram@umich.edu)

Prerequisites: Strong analytical skills. Experience with TensorFlow or similar learning software. Some experience working in Unix-like environments. Knowledge of probability theory.

Description: We have developed a novel architecture and algorithm for caching content. The project goal is to determine optimal parameter settings using learning algorithms, such as Deep Learning via neural networks.

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ECE Project 32: Load balancing using random graphs for cloud computing systems

Faculty Mentor: Vijay Subramanian (vgsubram@umich.edu)

Prerequisites: Strong analytical skills. Experience with Java, Python, or enough software engineering knowledge to comfortably learn and work with other such languages. Some experience working in Unix-like environments. Knowledge of basic graph theory and probability theory.

Description: We are developing novel algorithms for load balancing in cloud computing systems that use random graphs and distributed memory. The project goal is to implement and test these algorithms by developing a web-/Java-/Python-tool that can be easily configured and can run large instances with real-world topologies.

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ECE Project 33: Fast estimation of Personalized PageRank

Faculty Mentor: Vijay Subramanian (vgsubram@umich.edu)

Prerequisites: Strong analytical skills. Experience with Java, Python, or enough software engineering knowledge to comfortably learn and work with other such languages. Some experience working in Unix-like environments. Knowledge of basic graph theory and probability theory. EECS 485 would be a big plus.

Description: We are developing novel algorithms for estimating Personalized PageRank using random walks and dynamic programming. The project goal is to implement and test these algorithms in two ways: first, developing a web-/Java-/Python-tool that can be easily configured and can run large instances with real network instances, and second, developing a tool to run these on the Internet.

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ECE Project 34: Device-to-device sharing for real-time audio/video streaming

Faculty Mentor: Vijay Subramanian (vgsubram@umich.edu)

Prerequisites: Strong analytical skills. Experience with Android programming. Some experience working in Unix-like environments. Knowledge of probability theory, optimization and information theory.

Description: We are developing novel algorithms to enable easier real-time audio/video streaming on smartphone using device-to-device sharing over the WiFi interface. The project goal is to participate in the development of these algorithms, implement and test them on Android smartphones. We will use network coding and modify the kernel to implement our algorithms. We will also set up a server for generating the real-time stream. This will require two students.

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ECE Project 35: Real-time Hardware/Software Interface for Optoelectrodes

Faculty Mentor: John Seymour (seymourj@umich.edu)

Prerequisites: Background in Electrical Circuits and Computer Science. Advanced courses in such areas as C++, embedded controls, or electromagnetics are desired. A demonstrated interest in cross-disciplinary projects is also a plus. Experience programming an FPGA using C++ is preferred.

Description: We are looking for a highly motivated undergraduate to advance embedded system technology in the context of brain research. Our current project uses optical light stimulation, high-speed electrical recordings, and custom ICs. Input into the brain must react in real-time based on signal processing results of the brain output. This software and hardware system must achieve low latency and ease of programmability. The system will include embedded software running on an FPGA, analog driver IC, amplifier IC, and a computer with GUI and software platform.

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ECE Project 36: Infrastructureless Communication Smartphone App

Faculty Mentor: Robert Dick (dickrp@umich.edu)

Prerequisites: Smartphone programming or marketing experience.

Description: How would you like to be put back in control of what you see and share via social media, even as others attempt to use it as a tool of censorship and surveillance? Develop iOS/Android microblogging applications supporting direct and transitive phone-to-phone communication that is resistant to outages, blocking, censorship, and surveillance. Create local community-oriented networks that would keep working even if the plug were pulled on the internet. Development team members will need iOS or Android programming experience. Marketing team members will need website design, video production, or social media marketing experience. Status: Prototype microblogging application for iOS is functional. Focusing on improving functionality, energy efficiency, and performance.

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ECE Project 37: Smart IoT Sensor Interface Design

Faculty Mentor: Robert Dick (dickrp@umich.edu)

Prerequisites: One or more of the following:
1) PCB design.
2) PCB assembly, including surface mount soldering.
3) Electrical system testing and characterization.
4) Analog circuit design.

Description: Implement and test a smart sensor interface that turns dumb, manual sensors into accurate, automatic, wireless remote sensing systems. Water quality, air quality, audio... almost anything. Make the IoT real, today. Academic users/customers already enthusiastically waiting for the product. Status: Electrical design complete and undergoing testing and minor revisions. PCB design near-complete.

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ECE Project 38: IoT Wireless Communication Device Modeling

Faculty Mentor: Robert Dick (dickrp@umich.edu)

Prerequisites: Required Skills:
1) High-level understanding of wireless transceiver power consumption characteristics and ability to learn.
2) Ability to measure circuit power consumption.
3) Ability to interface various transceivers with development boards, e.g., Arduinos, using serial communication protocols.

Description: The personal computer, internet, and mobile computing changed mankind. The Internet of Things (IoT) is next. This network of ubiquitous, often low-power and wireless, devices will sense, analyze, and control the world. To create it, system designers must see the implications of their design decisions, and to do that they need system-level models of the wireless communication transceivers they are considering. There are many competitors (LoRa, NB-IoT, Weightless W, N, and P, Sigfox, and others), most of which are new, and nobody knows which will succeed. We are seeking someone to experimentally characterize several potential IoT wireless communication technologies, in order to build models for use in research and design. A literature survey will also be required.

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ECE Project 39: Sensing and Understanding Natural Environments

Faculty Mentor: Robert Dick (dickrp@umich.edu)

Prerequisites: One or more of the following:
1) Understanding of algorithm design and time complexity or state-of-the-art audio or image classification algorithms.
2) Embedded system design experience of the sort gained in EECS 373 and EECS 473.

Description: Design a wireless ultra long battery life system for understanding natural environments. Our initial focus will be on classifying and counting flying insects, including pollinators, pests, and disease vectors. Help figure out why so many bee colonies have died that there has been a 20% increase in the cost of pollination services, which accounts for billions of dollars per year, and why there has been a 75% reduction in the mass of flying insects in nature reserves in the base 25 years. This is a hard, representative, problem in the field of deeply embedded machine learning, where tight constraints on energy consumption and wireless communication data rates force hard decisions to be made via signal processing and machine learning algorithms running on low-power, light-weight remote systems. Status: We have developed an insect classification algorithm that functions in noisy natural environments and are working to improve its energy efficiency and accuracy, and to develop a hardware/software system prototype for deployment with our customers.

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ECE Project 40: Evaluation and Development of Analog and Wireless Systems

Faculty Mentor: Michael P. Flynn (mpflynn@umich.edu)

Prerequisites: Matlab and some knowledge of digital and analog circuit design.

Description: This research project will evaluate analog and wireless systems, help develop demonstrations of the analog and wireless systems and design new circuits. Flynn's research group designs analog and mixed-signal integrated circuits for applications as diverse as weather satellites and interfaces to the brain. This project will involve the design of new boards, and the writing of test software as well as software to control instruments. Some integrated circuit design will also be included in the project.

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