Undergraduate Research with Our Faculty
Computer science education involves both the theoretical and hands-on aspects. Introducing fundamental concepts about computer science and providing associated hand-on activities are equally important to achieve effective learning. In our program we provide many opportunities for our students to foster critical-thinking, facilitate the acquisition of life-long learning skills and improve communication skills through working on research projects and capstone class projects. Those skills are particularly crucial for our graduates to function effectively in this fast-changing field. Here are some highlights:
Dr. Joe Anderson received two-year NSF Grant as a PI for project titled “CRII: RI: RUI: Exploiting Geometry in Robust Signal Processing and Feature Extraction" and has been working with three computer science students on this project since summer 2020. Grant Dawson is studying effects of heavy-tailed noise on learning the centers of Gaussian Mixture Models. Blaine Mason is using the floating body to adapt simplex learning algorithms to be robust to heavy-tailed noise. Ryan Rosiak is implementing and studying floating body (approximate) membership oracle for use in both above two applications.
Dr. Giulia Franchi is funded by Baileys Foundation in the past three years to use nano 3D-printing technology to build Reef Balls with seed matrices for calcium carbonate precipitation. SU REAL Robotics directed by Dr. Giulia Franchi is collaborating with Easton Robotics to build a Task-based Autonomous Vehicle for Small Farms. In the Robotics lab, there are several on-going projects: students have worked with Phantom 3 and 4 drones to detect litter and marine debris in coastal vegetated areas as well assessing channel shape evolution in salt marshes; or built 3D printed grippers attached to the drones for picking up objects.
Dr. Yaping Jing and her former undergraduate research student Omar Aboul-Enein, now at National Institute of Science and Technology (NIST), coauthored a paper “Formalizing Performance Evaluation of Mobile Manipulator Robots Using CTML". This paper won the outstanding Research Paper Runner-Up Award (among 190 submissions) in Proceedings of the ASME 2020 International Mechanical Engineering Congress and Exposition (IMECE 2020). Volume 2B: Advanced Manufacturing. The project started as a case study as well as for Omar's undergraduate honors’ thesis based on Dr. Jing’s previous published work on CTML. When Dr. Jing listened to Omar's summer internship experience at NIST, she realized that it would be a perfect opportunity for an undergraduate research project for Omar.
Dr. Enyue (Annie) Lu has been awarded three NSF “REU SITE: EXERCISE - Explore Emerging Computing in Science and Engineering” grants for over one million dollars and has been leading a team of interdisciplinary faculty mentors to work with a total of 84 REU students. Dr. Lu’s REU students supervised by Dr. Lu were accepted to top computer science graduate programs and have been presented at top computing conferences. Recently, funded by the USDA, Dr. Lu is collaborating with the research teams from UMCP and UMES and supporting undergraduate research on the project “Transforming Shellfish Farming with Smart Technology and Management Practices for Sustainable Production”.
Dr. Junyi Tu is working on data visualization using topological methods, such as contour trees and Reeb graphs. Persistent diagram is a recent technique developed from the interdisciplinary field of topological data analysis, which covers both pure mathematics, computer science, and applications to neuroscience, biochemistry(drug design), and material science. Dr. Tu is actively working on how to compare and evaluate the perception of different topological visuals. Interested students are encouraged to contact Dr. Tu for research opportunities.
Dr. Shuangquan (Peter) Wang's research interests include mobile & wearable computing, activity recognition, and smart health. He is looking for self-motivated students to work with him on the following two topics: 1) Gait disturbance measurement for preventing older adult falls, which combines motion sensors and EMG to model the gait disturbance and prevent falls; 2) Cognitive impairment assessment, which utilizes the motion sensor-embedded wristbands to sense users’ hand motions and provide long-term cognitive impairment assessment.Dr. Xiaohong (Sophie) Wang has been involved in two major research topics recently. She was funded by Maryland Sea Grant and NOAA to work on integration of coastal inundation predictions with GIS Google Earth for Maryland. She worked with Sam Barnes, one of our CS graduates on the Maryland Sea Grant project and their work led to journal publications, book chapter and conference presentation. She also was also supported by Maryland Center for Computing Education to develop CS education methods course and CS education research.