Engaging Community College Students in Artificial Intelligence Research through an NSF-Funded Summer Research Internship Program
- Conference
- Location
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Portland, Oregon
- Publication Date
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June 23, 2024
- Start Date
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June 23, 2024
- End Date
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July 12, 2024
- Conference Session
- Tagged Division
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Two-Year College Division (TYCD)
- Tagged Topic
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Diversity
- Permanent URL
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https://peer.asee.org/47266
Paper Authors
Zhuwei Qin San Francisco State University
Dr. Zhuwei Qin is currently an assistant professor in the School of Engineering at San Francisco State University (SFSU). His research interests are in the broad area of deep learning acceleration, interpretable deep learning, and edge computing. Dr. Qin serves as the director of the Mobile and Intelligent Computing Laboratory (MIC Lab) at SFSU. Dr. Qin's research endeavors are dedicated to addressing the inherent challenges related to efficiency and robustness in the practical application of deep learning within real-world environments. A central emphasis within his research lab revolves around the achievement of computational acceleration for deep learning on low-power, and memory-constrained devices by deep compression and develop end-to-end deep learning training, acceleration, and deployment solutions on mobile and edge devices. His group actively collaborates with experts from various fields, such as robotics, rehabilitation sciences, and industrial partners.
Xiaorong Zhang San Francisco State University
Dr. Xiaorong Zhang is an Associate Professor in Computer Engineering in the School of Engineering at San Francisco State University (SFSU). She is the Director of the Intelligent Computing and Embedded Systems Laboratory (ICE Lab) at SFSU. She has broad research experience in human-machine interfaces, neural-controlled artificial limbs, embedded systems, and intelligent computing technologies. She is a recipient of the NSF CAREER Award to develop the next-generation neural-machine interfaces (NMI) for electromyography (EMG)-controlled neurorehabilitation. She is a senior member of the Institute of Electrical and Electronics Engineers (IEEE) and a member of the Society of Women Engineers (SWE). She has served in professional societies in various capacities including the Chair of the IEEE Engineering in Medicine and Biology Society (EMBS) San Francisco Chapter (2018-present), an Associate Editor of the IEEE Inside Signal Processing E-Newsletter (2016-2018), an Outreach Co-Chair of the Society of Women Engineers (SWE) Golden Gate Section (2017-2018), a Co-Chair of the Doctoral Consortium at 2014 IEEE Symposium Series on Computational Intelligence, a Program Committee Member of various international conferences, and a regular reviewer of a variety of journals and conferences in related fields.
David Quintero
San Francisco State University
orcid.org/0000-0002-3400-9535
Dr. David Quintero received B.S. degree from Texas A&M University, a M.S. degree from Stanford University, and a Ph.D. from the University of Texas at Dallas all in mechanical engineering. He is now an Assistant Professor of Mechanical Engineering at San Francisco State University representing as a Hispanic-Serving Institution with research focus on design and control of wearable robotic systems, and engineering education in the field areas of mechatronics/robotics.
Wenshen Pong P.E. San Francisco State University
Wenshen Pong received his Ph.D. in Structural Engineering from the State University of New York at Buffalo. He joined the School of Engineering at San Francisco State University in 1998. He teaches courses in Civil/Structural Engineering. He has received many grants from NSF, Department of Education and NASA.
Yiyi Wang San Francisco State University
Yiyi Wang is an assistant professor of civil engineering at San Francisco State University. In addition to engineering education, her research also focuses on the nexus between mapping, information technology, and transportation and has published in Accident Analysis & Prevention, Journal of Transportation Geography, and Annuals of Regional Science. She served on the Transportation Research Board (TRB) ABJ80 Statistical Analysis committee and the National Cooperative Highway Research Program (NCHRP) panel. She advises the student chapter of the Society of Women Engineers (SWE) at SFSU.
Jenna Wong P.E. San Francisco State University
Dr. Wong is a structural engineer broadly focused on seismic design of critical facilities. Her doctorate research at UC Berkeley investigated the applicability of seismic isolation and supplemental viscous damping to nuclear power plants with focus on se
Robert Petrulis
Dr. Petrulis is an independent consultant specializing in education-related project evaluation and research. He is based in Columbia, South Carolina.
Abstract
Supported by the National Science Foundation's Improving Undergraduate STEM Education: Hispanic-Serving Institutions (IUSE-HSI) Program, a collaborative summer research internship initiative united a public four-year institution with two local community colleges to offer community college students significant engineering research opportunities and hands-on experiences. In summer 2023, four students from the community college in computer science and engineering participated in a eight-week research internship project in a research lab at the four-year university. This internship project aimed to develop and implement of real-time computer vision on energy-efficient cortex-m microprocessor. This projet explores a unique approach to engage community college students in the realm of artificial intelligence research. By focusing on the development and implementation of real-time computer vision on energy-efficient Cortex-M microprocessors, we offer a practical and educational avenue for students to delve into the burgeoning field of AI. Through a combination of theoretical understanding and practical application, students are empowered to explore AI concepts, gain proficiency in low-power computing, and contribute to real-world AI projects. Furthermore, the project offered student interns a valuable opportunity to refine their research capabilities, particularly in the realms of scientific writing and presentation, while simultaneously boosting their self-assurance and enthusiasm for pursuing STEM careers in the field of AI.
Qin, Z., & Zhang, X., & Quintero, D., & Pong, W., & Wang, Y., & Wong, J., & Petrulis, R. (2024, June), Engaging Community College Students in Artificial Intelligence Research through an NSF-Funded Summer Research Internship Program Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. https://peer.asee.org/47266
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