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Summer Undergraduate Research in Engineering (SURE)

SURE offers summer research internships to outstanding current U-M undergraduate students who have completed their sophomore or junior year (preference will be given to those who have completed three years of study) by the time of their internship.  Participants have the opportunity to conduct 10-12 weeks of full-time summer research with some of the country’s leading faculty in a wide range of engineering disciplines. The program provides opportunities for students to assess their interests and potential in pursuing research at the Masters or Ph.D. level in graduate school.  All participants must apply online through the SURE website.  Accepted applicants from the University of Michigan receive guidance by a faculty advisor in a College of Engineering research facility, a stipend of $5,000, attend regular meetings and seminars and contribute to an abstract booklet with highlights of their summer research project and/or experience.

Selection Process: Once the SURE Manager has shared your application with the Department, we will provide the eligible applications to the Faculty Mentors who will review your application materials. It is possible that they will reach out to you directly for further information. You do not need to do anything else, but if you have any specific questions regarding a SURE Project, you are welcome to reach out to the listed Faculty Mentor. Any notification of an offer will be sent from the SURE Manager, Shira Washington.

General Timeline:
January – Application is due
February – Applications are reviewed
March – Offers will begin being sent out
April – Offers may still be issued during this time
May – SURE Projects may begin

Learn more:

The SURE Application is due January 15, 2021

Mechanical Engineering 2021 SURE Research Projects

ME Project #1: 3D-Printing of Custom Assistive Devices

Faculty Mentor: Albert Shih,
Research Mode: In-lab
Project Description: This project explores the use of material extrusion (MEX), one of the additive manufacturing processes, for 3D-printing of various assistive devices. The project works closely with the University of Michigan Orthotics and Prosthetics Center with the goal to develop design and manufacturing methodologies for a new service system for rapid turn-around and high-quality 3D-printing of assistive devices that will have personalized fit and comfort. Such assistive devices including lower and upper limb prosthesis, orthoses for diabetes partial foot amputees, ankle foot orthoses for stroke patients. Contact modeling based on the computed tomography (CT) or 3D scanning images will be developed to design the geometry.

ME Project #2: Computational Studies of Bubble Collapse

Faculty Mentor: Eric Johnsen,
Research Mode: Remote
Project Description: The goal of this project is to computationally investigate the potential damage produced by collapsing cavitation bubbles. This research is motivated by cavitation erosion observed in naval hydrodynamics (e.g., propellers) as well as deliberate damage produced by ultrasound-induced cavitation to destroy pathogenic tissue. The student will use an in-house code to conduct the numerical simulations. The project may additionally include opportunities to develop reduced-order, data-driven models of collapsing bubbles.

ME Project #3: Durability of Soft Robot Snakes

Faculty Mentor: Talia Moore,
Prerequisites/desired background: Previous experience with materials testing and biomimicry
Research Mode: Hybrid
Project Description: In this project, the student will experiment with different manufacturing methods to create the most durable snake-mimicking pneumatically actuated robots for deployment in the rainforest and interaction with live predators. The student will design and perform longitudinal studies to characterize the long-term performance and durability of their designs.

ME Project #4: Simulation of Off-road Autonomous Vehicles

Faculty Mentor: Bogdan I. Epureanu
Research Mode: Hybrid or Fully Remote
Lab: Applied Nonlinear Dynamics of Multi-Scale Systems
Prerequisites/desired background:

  • Programming familiarity with C++ and Python
  • Experience programming in both Windows and Ubuntu environments
  • Experience with Unreal Engine 4 (UE4) is desirable
  • Basic knowledge of Robot Operating System (ROS) and MATLAB
  • Basic knowledge of CarSim or PhysX

Project Description: In this project, students will assist us in our development of a high-fidelity automotive simulation built with Unreal Engine 4. At a high-level, we are building an off-road simulation in which multiple users (human players) can interact with multiple virtual vehicles. Each vehicle will have a sensor suite (camera, LiDAR, IMU, and radar), and will have various control and perception algorithms so they can navigate autonomously in the environment.

Tasks will be defined periodically, and may include:

  • Creating algorithms and programming landscapes in UE 4, which include modeling the terrains, creating materials using multiple textures, and applying these to the landscape. Testing new features in a virtual environment under developmen
  • Testing VR integration with a virtual environment under development
  • Implementing control/perception/navigation algorithms using UE4 blueprinting, C++, Python
  • Integrating control/perception/navigation algorithms with UE4 using ROS communication
  • Modifying vehicle physics properties using CarSim or PhysX
  • Developing automated data collection capabilities
  • Exploring platooning of vehicles in UE4 by simulating chains of vehicles that follow eachother and move on a predetermined path within UE4.

ME Project #5: Immersive Environment for Autonomous Vehicles using Unreal Engine Simulations

Faculty Mentor: Bogdan I. Epureanu
Research Mode: Hybrid or Fully Remote
Lab: Applied Nonlinear Dynamics of Multi-Scale Systems
Prerequisites/desired background:

  • Programming familiarity with C++ and Python
  • Experience programming in both Windows and Ubuntu environments
  • Experience with Unreal Engine 4 (UE4)
  • Basic knowledge of Robot Operating System (ROS) and MATLAB
  • Experience with image processing and video systems highly desirable

Project Description:

In this project, students will assist us in the development of a high-fidelity automotive simulation built with Unreal Engine 4. At a high-level, we are building an off-road simulation in which multiple users (human players) can interact with multiple virtual vehicles. We are also building a new lab to help us realize this entire simulation and provide an immersive experience for the user. In this new facility, we will be displaying the simulation on a large LED video wall. Students will assist in configuring an existing environment to visualize our simulation on the video wall.

Tasks will be defined periodically, and may include:

  • Adding capabilities in UE4 to our simulation platform to render scenes on a video wall
  • Testing the simulation with the video wall
  • Testing new features in a virtual environment under development
  • Testing VR integration with a virtual environment under development

ME Project #6: AI-Based Interaction of Autonomous Agents and Humans in Synthetic Environments

Faculty Mentor: Bogdan I. Epureanu
Research Mode: Hybrid or Fully Remote
Lab: Applied Nonlinear Dynamics of Multi-Scale Systems
Prerequisites/desired background:

  • Programming familiarity with C++ and Python
  • Experience programming in both Windows and Ubuntu environments
  • Experience with Unreal Engine 4 (UE4) is desirable
  • Basic knowledge of Robot Operating System (ROS) and MATLAB

Project Description: In this project, students will assist us in our development of an interface connecting a virtual gaming environment in Unreal Engine to a team of autonomous and human agents/players. In particular, given existing plugins such as high-level task distribution algorithms, path planning algorithms, autonomous agent control algorithms, the desired interface is able to provide visual image, extract essential data (state of the operation, state of the agent, etc.), broadcast information through a communication channel to other players, and exchange information. The developed interface is used for human players to collaborate with autonomous agents in the virtual environment to perform an operation and achieve a defined common mission goal.

Tasks will be defined periodically, and may include:

  • Creating VR, integration with a virtual environment
  • Implementing control algorithms using UE4 blueprinting C++, Python
  • Integrating control algorithms with UE4 using ROS communication
  • Developing automated data collection capabilities

ME Project #7: Engineering a synthetic neuron using bottom-up synthetic biology

Faculty Mentor: Allen Liu,
Prerequisites/desired background: see below.
Research mode: In lab
Project description: Building synthetic cells is an exciting area of synthetic biology with opportunities to unravel basic design and organizational principles of cellular life. Besides a cellular reconstitution approach of using purified protein components, the current paradigm in the construction of a bottom-up synthetic cell system involves lipid bilayer vesicle encapsulation of cell-free expression systems to engineer active membranes. The Liu lab and his collaborative team have identified neuron as a potentially tractable system to construct from the bottom-up. Neurons convert biochemical information (through binding of a neurotransmitter) to electrical signal (via action potential) and back to biochemical signal (through the release of neurotransmitters). These distinct and separable processes can be reconstituted in a synthetic neuron by using natural and engineered proteins. As part of the team, the student involved will be offered an opportunity to work on reconstituting ion channels using a mammalian cell-free expression system and testing their functions using electrophysiology. Candidate with interests in biology and hands-on lab work is highly desirable. Basic knowledge in chemistry and molecular biology is a plus.

ME Project #8: Environmental and economic assessment of CO2 utilization

Faculty Mentor: Volker Sick,
Prerequisites/desired background: A good understanding of dealing with uncertainty in data and resulting complexity in decision making is required. Familiarity with literature and data searches is desirable as is an interest in environmental issues.
Research Mode: In lab
Project description: Carbon dioxide utilization offers an opportunity to help counter climate change effects. Technologies that can turn CO 2 into products ranging from construction materials like concrete to chemicals like synthetic fuels and plastics, all the way to human food must be evaluated for their environmental and economic benefits and implementation risks. This project will result in life cycle assessments and techno-economic assessments of select technologies in collaboration with researchers in the Global CO 2 Initiative.

ME Project #9: Control of Active Seat for Motion Sickness Mitigation in Autonomous Vehicles

Faculty Mentor: Shorya Awtar,
Prerequisites/Desired background: Candidates should meet the following prerequisites: (1) Background in Mechatronics covering practical aspects of modeling mechanical and electrical systems, control theory, sensors & actuators, (2) Proficiency in engineering design and analysis tools such as SolidWorks, MATLAB, (3) Experience in machining, fabrication and assembly of mechanical components and systems, and (4) Prior experience with sensor and instrumentation systems for experimental data collection.
Research Mode: Hybrid – a combination of in lab mechanical assembly, on track testing at MCity, and online meetings and remote work on design and documentation. All required safety precautions and protocols will be followed for any in person work.
Project Description: The aim of this project is to assemble, and test an active seat mechatronic system in a MCity test vehicle, and use the test results to make modifications to the active seat system. Motion sickness is a condition that afflicts one in three US adults travelling in passenger vehicles, and the NHTSA has estimated that commutes hold the productivity potential of $500B. The literature has shown promise in active seats that tip and tilt in response to vehicle motion to reduce passenger motion sickness, and improve passenger comfort and productivity. Students will have an opportunity to develop and hone mechatronic design skills, learn experimental design and data analysis, and learn about engineering design methodology and practice. Prior research in the lab has focused on motion sickness simulation, mechanism design, and mechatronic systems design. The students working on this project will be responsible for (1) Static and Dynamic modelling of active seat system, (2) Design of controllers of active seat system, (3) Experimental design and data collection, (4) Experimental data analysis, and (5) All documentation and reports associated with research investigations.

ME Project #10: Experimental Study of Flow Dynamics and Heat Transfer in Particulate Flows

Faculty Mentor: Rohini Bala Chandran,
Project Prerequisites: Candidates should have had an introduction to heat transfer (ME 335), fluid mechanics (ME 320) and experience with engineering design and analysis tools like SolidWorks and MATLAB. Lab courses covering  basic measurements, materials and thermodynamics will be considered a plus (ME 395).
Research Mode: In Lab/Hybrid
Project Description: An increasing number of engineering applications rely on high-temperature flows of particulate media, including up-and-coming renewable energy technologies like particle-based concentrated solar power (CSP) with thermal energy storage (TES). The goal of this project is to experimentally investigate the role of radiative heat transfer in high temperature (> 700°C) particulate flows. Students will have a hand in (1) design work related to the development of a test chamber for flow and heat transfer measurements, (2) the construction and assembly of experimental apparatus, and (3) data collection and analysis that support the work of the project. Candidates with an interest in hands-on work and challenging experimental work are preferred.

ME Project #11: Electrochemical Flow Cell Development for Wastewater Nitrates Treatment

Faculty Mentor: Rohini Bala Chandran,
Project Prerequisites: Candidates should have experience with engineering design and analysis tools like SolidWorks and MATLAB; prior experience in designing, prototyping, fabricating parts and small components will be considered a plus;  prior wet-lab experience and/or courses related to energy and electrochemistry will be considered a plus.
Research Mode: In-lab/hybrid
Project Description: Nitrates are a widespread pollutant present in many water streams that affect the health of both the environment and humans. The effectiveness of possible (photo)electrochemical treatment approaches are sensitive to the pH of the water, concentrations of pollutant species present and the materials used for the electrodes. We are looking to recruit a highly motivated student that can work  together with a graduate student to design, develop and test a prototype reactor to assess these effects. Students will learn (1) the basics of the theory and operation of electrochemical devices; (2) design and perform experimental measurements, and (3) analyze experimental data coupled with modeling tools. Candidates with interest and prior experience in hands-on experimental work are highly encouraged to participate and will be preferred over other applicants.

ME Project #12: Engaging People to Define Problems in Engineering Design Projects

Research Mentor: Shanna Daly;
Desired background: some engineering design coursework and/or co-curricular design experience
Research Mode: Planned to be remote
Project Description: How can designs truly incorporate stakeholder and contextual needs into their design decisions? And, how do designers identify the best design problems to solve in the first place? We are conducting research examining how engineering students explore potential problems to solve and use information from stakeholders to make design decisions. We are investigating (a) how engineering students engage with users as they define problems, (b) design strategies engineering students use in understanding problems, and (c) design tools that can support best practices in identifying problems and incorporating user feedback when developing design solutions. Assistants on our projects will gain hands-on experience in how to do research in engineering design, particularly how to organize and analyze data, and learn about best practices for front-end design processes.

ME Project #13: Design of Novel Upper Limb Prosthesis

Faculty Mentor: Shorya Awtar,
Project Prerequisites: Candidates should be proficient in SolidWorks and MATLAB and have experience in machining, fabrication
and assembly of mechanical components and systems.
Research Mode: Remote, Hybrid
Project Description: The mechanical design of powered upper limb prostheses has been an area of intense research for the past 40 years. However, there is still a significant gap in the performance of these prostheses when compared with the capabilities of a human arm. The aim of this project is to design and build a novel upper limb prosthesis that seeks to fill in the performance gaps that exist in current prostheses. Students will be working in (1) Static and Dynamic modeling of elements of the prosthesis, (2) Research and modeling of different types of actuators, and (3) Design and fabrication of elements of the prosthesis. The ideal candidate should be passionate about learning more about Mechatronics system design and prostheses in general.

ME Project #14: Automatic Fault Detection for 3D Printing

Faculty Mentor: Chinedum Okwudire,
Research Mode: In lab, Hybrid, Remote
Project Description: The student working on this project will help develop an algorithm for automatic detection of failures and faults in 3D printing using low-cost sensors. The ideal student should be very skilled in CAD software, MATLAB and C++ (or Python), and enjoy coding. Some familiarity with machine learning and 3D printing is a plus. The student will get to implement and test their algorithms on 3D printers.

ME Project #15: Engineering Electrodes and Electrochemical Flow Cells for CO2 Capture

Faculty Mentor: David Kwabi,

Prerequisites/desired background: Organic Chemistry, Thermodynamics, Electrochemistry, MATLAB/Python

Research Mode: In lab/hybrid

Project Description: Large-scale CO2 separation and concentration from point sources, seawater and the atmosphere can play key roles in mitigating climate change and promoting the conversion of CO2 into chemical fuels and high-value products. Electrochemical CO2 separation processes have the potential to be more cost-effective than conventional thermal analogues if they use inexpensive active materials and are sufficiently energy-efficient. The aim of this project is to functionalize porous carbon electrodes with organic acid/base groups and deploy them in electrochemical flow cells capable of separating CO2 from seawater or emissions from fossil fuel-burning plants using a pH swing cycle. The experimental work will be coupled with modeling to understand the various thermodynamic and kinetic factors that contribute to the electrical energy consumed per unit of concentrated CO2 (kJ/molCO2), which is a critical figure of merit for practical systems.

ME Project #16: Estimating the mechanical impedance of the ankle during hopping

Faculty Mentor: Elliott Rouse,

Research Mode: Hybrid

Lab: Neurobionics Lab

Project Description: The mechanics of human joints are important to understand and imitate in order to create prosthetics that feel more natural and function more naturally. Impedance (stiffness and damping) is an important mechanical property in joints and varies depending on the specific motion being performed. Studies have been conducted to determine the mechanical impedance of the ankle during walking, but little is known about how the impedance of the ankle changes during other activities, including hopping. The purpose of this project will be to analyze the mechanical impedance of the ankle while hopping in healthy human subjects. This information will add to collective knowledge of how the mechanics of the ankle change during various activities, which will allow better prosthetics to be created. The student will recruit and collect hopping data from healthy subjects, then use tools established by the lab to quantify the ankle’s mechanical impedance. The student should have a background or interest in conducting hands-on biomechanical research including collecting data from human subjects. Interest in biomechanics and knowledge of how to use common lab tools such as motion capture systems are a plus.

ME Project #17: Biomechanical Modeling and Experimental Evaluation of Lower Limb Exoskeletons

Faculty Mentor: Robert Gregg,

Research Mode: In-lab

Project Description: Description: This project has 3 main parts. The first part of this project involves biomechanical modelling in  OpenSim (a popular open-source program) and Matlab of the effect of powered lower-limb orthoses on muscle activity, joint loads and metabolic cost. Various exoskeleton assistance strategies can be explored for different activities of daily living. The second part involves performing human subject experiments using our two prototype exoskeletons. This will primarily involve the use of a 3D  motion capture system (Vicon) and electromyography system. Motion capture will require learning the high level operations of the data capture and pre-processing software (Nexus) and customizing of standard biomechanical models to suit the experimental objective. Post processing of the data will be performed in Matlab. The final part will involve CAD design and 3D printing of exoskeleton attachment revisions based on user feedback.