Boulder, Colorado
March 25, 2018
March 25, 2018
March 27, 2018
Diversity
17
10.18260/1-2--29619
https://peer.asee.org/29619
419
Jayson Mercurio studies computer science at UC Santa Barbara. He is a recent transfer student from Canada College in Redwood City and interned at SFSU over the summer of 2017, working on image recognition with neural networks.
Jose L. Guzman is currently an undergraduate at Canada College. He participated in a research program at San Francisco State University where he focuses on a conventual neural network to identify the object at high and accurate results.
Xiaorong Zhang received the B.S. degree in computer science from Huazhong University of Science and Technology, China, in 2006, the M.S. and the Ph.D. degrees in computer engineering from University of Rhode Island, Kingston, in 2009 and 2013 respectively. She is currently an Assistant Professor in the School of Engineering at San Francisco State University. Her research interests include embedded systems, wearable technologies, neural-machine interface, and cyber-physical systems.
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.
Dr. Pong is a registered Professional Engineer in California. He is a member of the American Society of Civil Engineers and the Structural Engineers Association of California. He has published over fifty technical papers in the areas of Structural Control and Earthquake Engineering. Dr. Pong has been the Director of the School of Engineering at SFSU with 20 full-time faculty and over 25 part-time faculty since 2009.
Amelito Enriquez is a professor of Engineering and Mathematics at Cañada College in Redwood City, CA. He received a BS in Geodetic Engineering from the University of the Philippines, his MS in Geodetic Science from the Ohio State University, and his PhD in Mechanical Engineering from the University of California, Irvine. His research interests include technology-enhanced instruction and increasing the representation of female, minority and other underrepresented groups in mathematics, science and engineering.
Zhaoshuo Jiang graduated from the University of Connecticut with a Ph.D. degree in Civil Engineering. Before joining San Francisco State University as an assistant professor, he worked as a structural engineering professional at Skidmore, Owings & Merrill (SOM) LLP. As a licensed professional engineer in the states of Connecticut and California, Dr. Jiang has been involved in the design of a variety of low-rise and high-rise projects. His current research interests mainly focus on Smart Structures Technology, Structural Control and Health Monitoring and Innovative Engineering Education.
Dr. Cheng Chen is currently an associate professor in the school of engineering at San Francisco State University. His research interests include earthquake engineering, structural reliability and fire structural engineering.
Kwok Siong Teh received his B.S., M.S., Ph.D. degrees in Mechanical Engineering from the University of Illinois Urbana-Champaign, University of Michigan at Ann Arbor, and University of California at Berkeley in 1997, 2001, and 2004, respectively. He is currently an associate professor of mechanical engineering at San Francisco State University. His primary research interests are in: (i) the synthesis, characterization, and applications of metal oxides, conductive polymer, and low dimensional carbon nanostructures for energy generation and storage; (ii) engineering design pedagogy that incorporates makerspace, case studies, and scenario-based learning.
Hamid Mahmoodi received his Ph.D. degree in electrical and computer engineering from Purdue University, West Lafayette, IN, in 2005. He is currently a professor of electrical and computer engineering in the School of Engineering at San Francisco State University. His research interests include low-power, reliable, and high-performance circuit design in nano-electronic technologies. He has published more than one hundred technical papers in journals and conferences and holds five U.S. patents. He was a co-recipient of the 2008 SRC Inventor Recognition Award, the 2006 IEEE Circuits and Systems Society VLSI Transactions Best Paper Award, 2005 SRC Technical Excellence Award, and the Best Paper Award of the 2004 International Conference on Computer Design. He has served on technical program committees of Custom Integrated Circuits Conference, International Symposium on Low Power Electronics Design, and International Symposium on Quality Electronics Design.
Hao Jiang received the B.S. degree in materials sciences from Tsinghua University, China, in 1994 and the Ph.D. degree in electrical engineering from the University of California, San Diego, in 2000.
Hao Jiang has been with San Francisco State University since August 2007 as an assistant professor in electrical engineering. Prior joining SFSU, he worked for Broadcom Corporation, Jazz Semiconductor and Conexant Systems Inc. His research interests are in the general area of analog integrated circuits, particularly in ultra-low-power circuits for biomedical applications.
Alexander Choi is a junior at the University of California, Irvine that majors in Computer Engineering. Interests include artificial intelligence, optics, and other machine learning related topics.
Community colleges provide a beneficial foundation for undergraduate education in STEM majors. To inspire community college students to pursue a major in STEM, it is crucial to adapt strategies that help facilitate this interest. With support from the Department of Education Minority Science and Engineering Improvement program (MSEIP) and the Hispanic-Serving Institution Science, Technology, Engineering and Mathematics (HIS STEM), an internship program with multiple colleges was developed between community colleges and a public four-year university to engage community college students in cutting-edge engineering research. In the summer of 2017, four community college students participated in a ten-week electrical and computer engineering research internship project at a four-year university research lab. The summer internship project aimed to develop a real-time handwritten digit recognition system leveraging Neural Networks and Nvidia’s Jetson Tx1 platform. Utilizing a modified Nvidia workflow, a robust digit recognition algorithm was designed using two industry standard programs for deep learning -- Tensor Flow and DIGITS. Nvidia’s live image recognition demonstration created the framework to interface a camera module that sends images to the input of the digit classifying network in real-time. The student interns designed experiments to test the robustness of the algorithm in their daily environment, from low light situations to cluttered backgrounds with the handwritten digit blending in. The internship project created a stimulating environment for student interns to gain research experiences and learn a wealth of knowledge in deep learning, real time pattern recognition systems and leading-edge hardware platforms. The experiences contained within the ten-week internship allowed the interns to drastically improve technical writing and presentations, experimental design, data analysis and management, teamwork, and perseverance. The ten-week research internship was an effective method for engaging aspiring community college students by teaching the tools and methodology for success within an engineering profession.
Mercurio, J. P., & Yamada, K., & Guzman, J. L., & Zhang, X., & Pong, W., & Enriquez, A. G., & Jiang, Z., & Chen, C., & Teh, K. S., & Mahmoodi, H., & Jiang, H., & Choi, A., & Iqbal, A. R. (2018, March), Inspiring Community College Students in Electrical and Computer Engineering Research through Live Digit Recognition using Nvidia’s Jetson Tx1 Paper presented at 2018 ASEE Zone IV Conference, Boulder, Colorado. 10.18260/1-2--29619
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