Research Projects

This is a list of research projects that may have opportunities for undergraduate students. You can browse all the projects, or view only projects in the following categories:

Industrial Engineering

 

A Multi-Objective Optimization Approach for Generating Complex Networks

Research categories:  Computational/Mathematical, Computer Engineering and Computer Science, Industrial Engineering
School/Dept.: Industrial Engineering
Professor: Mario Ventresca
Preferred major(s): CS, CE, EE, IE, STATS, Math
Desired experience:   Basic coding skills (R -preferred, Matlab, etc.), basic courses in probability and statistics, proficiency in English speaking and writing, experience in algorithm design and analysis is highly desirable.
Number of positions: 1-2

Complex networks are often used to model a wide range of systems in nature and society from biological to social networks. One area of importance is the ability to model network formation, which has lead to the development of many different algorithms (network generators) capable of synthesizing networks with very specific structural characteristics (e.g., degree distribution, average path length). However, existing generators are not capable of synthesizing networks with strong resemblance to those observed in the real world. In our recent work we created a new class of network generators, called Action-based Network Generators that have shown the ability to produce complex structure of networks exhibiting different properties. This SURF project will involve rigorous testing of the action-based network generator. The student, together with a PhD student, will be involved in running simulation experiments on real world networks, generalizing the generator for different types of networks and trying different computational techniques to obtain the optimal generator. This will also involve analyzing the simulation data to interpret results and further improve the algorithms. Finally, the project also provides the student with an opportunity to publish work as paper.

 

In Situ Strain Mapping Experiments

Research categories:  Aerospace Engineering, Civil and Construction, Computational/Mathematical, Computer Engineering and Computer Science, Industrial Engineering, Material Science and Engineering, Mechanical Systems
School/Dept.: School of Aeronautics and Astronautics
Professor: Michael Sangid
Preferred major(s): AAE, MSE, or ME
Number of positions: 2

The research we do is building relationships between the material's microstructure and the subsequent performance of the material, in terms of fatigue, fracture, creep, delamination, corrosion, plasticity, etc. The majority of our group’s work has been on advanced alloys and composites. Both material systems have direct applications in Aerospace Engineering, as we work closely with these industries. We are looking for a motivated, hard-working student interested in research within the field of experimental mechanics of materials.

The in situ experiments include advanced materials testing, using state-of-the-art 3d strain mapping. We deposit self-assembled sub-micron particles on the material’s surface and track their displacement as we deform the specimen. Coupled with characterization of the materials microstructure, we can obtain strain localization as a precursor to failure. Specific projects look at increasing the structural integrity of additive manufactured materials and increasing fidelity of lifing analysis to introduce new light weight materials into applications.

 

Nano-Piezotronics for Smarter Electronics

Research categories:  Bioscience/Biomedical, Chemical, Electronics, Industrial Engineering, Material Science and Engineering, Mechanical Systems, Nanotechnology, Physical Science
School/Dept.: Industrial Engineering
Professor: Wenzhuo Wu
Preferred major(s): Mechanical, Electrical, Materials, Biomedical, Industrial Engineering
Number of positions: 1

The seamless and adaptive interactions between electronics and their environment (e.g. the human body) are crucial for advancing emerging technologies e.g. wearable devices, implantable sensors, and novel surgical tools. Non-electrical stimuli, e.g. mechanical agitations, are ubiquitous and abundant in these applications for interacting with the electronics. Current scheme of operation not only requires complex integration of heterogeneous components, but also lacks direct interfacing between electronics and mechanical actuations.

Piezotronics is an emerging field in nanomaterials research and offers novel means of manipulating electronic processes via dynamically tunable strain. In this research, the SURF students will develop flexible and transparent piezotronic nanowires transistors for active and adaptive bio-electronics sensing and interfacing. The device is capable of self-powered active sensing by converting mechanical stimulations into electrical controlling signals without applied bias, which emulates the physiological operations of mechanoreceptors in biological entities, e.g. hair cells in the cochlea.

This project is scientifically novel with transformative impact because it not only dramatically advances fundamental understanding of the emerging research in piezotronics, but also enables new opportunities in designing “smarter” electronics that are capable of interacting with the environment seamlessly and adaptively, which is not available in existing technologies, for societally pervasive applications in intelligent wearable devices, surgical tools and bio-probes. The SURF student will work with two PhD students on the nanomaterials synthesis, nanodevices fabrication and measurement. For more information, please visit our lab, the Nanosystems and Nanomanufacturing Lab or feel free to contact me. Contact information appears in the website.

 

Ultra-Flexible Triboelectric Nanogenerators for Self-Powered Wearable Sensors

Research categories:  Bioscience/Biomedical, Chemical, Electronics, Industrial Engineering, Material Science and Engineering, Mechanical Systems, Nanotechnology, Physical Science
School/Dept.: Industrial Engineering
Professor: Wenzhuo Wu
Preferred major(s): Biomedical, Mechanical, Electrical, Materials, Industrial Engineering
Number of positions: 1

Triboelectric nanogenerator (TENG) has emerged as a promising technology for efficiently harvesting mechanical energy due to high conversion efficiency, low fabrication cost, and broad choice of materials. TENGs utilize contact electrification to generate surface charges and convert mechanical energy into electricity from contact and separation between triboelectric layers. Apart from material selection and device structure, one crucial factor affecting the performance of contact electrification process is materials properties and topography of triboelectric contact surfaces. In this project, we will manufacture large scale TENG with modifiable properties at high production rate. These flexible TENGs will be used to harvest mechanical energy from human body, e.g. muscle stretching/motion, and from ambient environment, e.g. wind, raindrops. The converted electricity can be utilized to power small electronic devices, e.g. sensors and processers. The TENGs can also function as self-powered wearable sensors to quantitatively track human motion and monitor posture. The student will work with our PhD students on the nanomaterials synthesis, nanodevices fabrication and measurement.

For more information, please visit our lab, the Nanosystems and Nanomanufacturing Lab or feel free to contact me. Contact information appears in the website.

 

WeRead: Engage Students in Reading Assignments

Research categories:  Industrial Engineering
School/Dept.: School of Industrial Engineering
Professor: Ji Soo Yi
Preferred major(s): IE
Desired experience:   Prior research experiences with qualitative research with some basic web programming skill sets are required.
Number of positions: 1

Students are expected to know what subjects will be covered in class before they come. One good way is to do the readings assigned by teachers. As active learners, they usually come to class prepared and do the readings. However, many students spend little time reading their textbook or additional reading materials. Without preparing for class, it’s hard for them to understand the content and lead the in-class discussion. In this project, we are trying to encourage students to read materials before the class, so they can effectively communicate with classmates in the student-led discussion.

In order to achieve the goal, we are conducting a design study to develop a web-based tool to engage students in reading assignments, titled “WeRead: Engage Students in Reading Assignments”. Before starting to develop a web, we will collect data to understand the current situation and needs regarding reading assignment through a survey for students and instructors. The survey results will be used to decide what features and functions that will be shown in this web application.

 

Wearable Sensors for Improving Health Care Delivery

Research categories:  Bioscience/Biomedical, Industrial Engineering, Innovative Technology/Design
School/Dept.: Industrial Engineering
Professor: Denny Yu
Preferred major(s): Industrial Engineering, Biomedical Engineering
Desired experience:   Strong interest in human factors and healthcare. Experienced with Matlab. Comfortable with conducting field and laboratory-based studies.
Number of positions: 1

Healthcare is provided in a dynamic environment with complex human interactions. Excessive team and individual workload impact both patient and care provider safety, but quantifying workload in these environments remains elusive. Student selected for this project will conduct cutting-edge and applied research related to smart wearables for reducing provider workload and sensor-based quantification of human dynamics with the goal of informing interventions to enable the highest levels of health care delivery.