Dr. Kenny Q. Zhu is a full professor of computer science at University of Texas at Arlington. He graduated with B.Eng (Hons) in Electrical Engineering in 1999 and PhD in Computer Science in 2005 from National University of Singapore. He was a postdoctoral researcher and lecturer from 2007 to 2009 at Princeton University. Prior to that, he was a software design engineer at Microsoft, Redmond, WA. From Feb 2010 to Aug 2010, he was a visiting professor at Microsoft Research Asia in Beijing. From 2010 to 2023, he was an associate professor and then full professor at Shanghai Jiao Tong University. Kenny's main research interests are natural language processing and knowledge engineering. He has published extensively in AI, NLP, and Database at top venues such as AAAI, IJCAI, ACL, EMNLP, WWW, SIGMOD, and CIKM. He has served as the SPC or PC of AAAI, IJCAI, ACL, EMNLP, NAACL, WWW, CIKM, ECML, etc. His research has been supported by NSF China, MOE China, Microsoft, Google, Oracle, Morgan Stanley and AstraZeneca. Kenny is the winner of the 2013 Google Faculty Research Award and 2014 DASFAA Best Paper Award.
Research Experience for Undergraduates Site
REU Site: Animal Language Processing and Understanding
REU Site Faculty Mentors
Dr.Walsh is a Professor in the Biology Department at UTA. He earned his PhD in Evolution, Ecology & Organismal Biology from University of California Riverside. Before joining UTA in the Fall of 2012, he was an Environmental Research Fellow at Yale University. He has been awarded with Presidents Award for Excellence in Teaching at UTA in May 2021 and College of Science Teaching Excellence Award at UTA in May 2020.
Vassilis Athitsos is a professor of computer science and engineering at UTA. A significant part of his research effort focuses on human motion analysis and gesture recognition. In recent projects, he and his team have developed and published new methods for sign language recognition and automatic scoring of physical exercises performed by children. While at UTA, he has mentored 14 undergraduates in their research. Several of those undergraduates belonged to groups that are underrepresented in computer science: four were women (one of which is also Deaf and African American), two were Hispanics, and one had an Asian/Pacific ethnic background. Several of these students have authored or coauthored research papers. One of these undergraduates later graduated with a Computer Science Master from Carnegie Mellon. At least four of those students are currently Ph.D. students, including one recently joining the Computer Science Ph.D. program at the University of Chicago.
Melissa Walsh is an associate professor of instruction and the associate chair in the Department of Biology at UTA. She specializes in the development of undergraduate classroom-based research experiences that foster competency with data analysis, scientific thinking, and communication. Her pedagogical research has focused on curricular designs that improve equitable learning outcomes and success in STEM courses, particularly for underrepresented groups. She has mentored numerous undergraduates in scientific pedagogy, including participants in the Louis Stokes Alliance for Minority Participation program. Dr. Walsh contributes both her background as a statistical ecologist and expertise in science education to this project.
Dr. Yingying Zhu is an Assistant Professor in the Department of Computer Science and Engineering at the University of Texas at Arlington (UTA). Dr. Zhu has been extensively working on extending fundamental machine learning to solve general computer vision and biomedical data analysis problems. She especially works on developing machine learning models for analyzing videos and audio to identify the chicken virus. She also supervised undergraduate intern students in an NIH program to develop a paper that was published and won the NIH Summer Mentor award. Her research work has been recognized across various disciplines and published in top-tier Machine Learning and Computer Vision conferences (Computer Vision and Pattern Recognition (CVPR), European Conference on Computer Vision (ECCV), KDD as well as high-impact Medical Imaging journals (NeuroImage, Medical Imaging Analysis), IEEE Transaction on Medical Imaging, IEEE Transaction on and conferences (Medical Image Computing and Computer Assisted Intervention (MICCAI), international conference on Information Processing (IPMI)) and IEEE Transactions on Pattern Analysis and Machine Intelligence.
Dr. Mengyue Wu is an associate professor of the computer science and engineering department at Shanghai Jiao Tong University. She specializes in audio and speech signal processing, integrating technology with human cognition. Her main focus is acoustic-based disease detection and bioacoustics understanding. With a background in phonetics, psycholinguistics, and experimental psychology, she’s published over 50 papers in top signal-processing conferences and journals. She is passionate about mentoring and has supervised/is supervising three Ph.D. students, seven Master's students, and over 20 undergraduates. She was honored as an "Outstanding Mentor" for two consecutive years and led a university-level award-winning "Innovative Project for Undergraduate Research" in digital mental health. Since 2020, she’s led the "Med-Engineering Site" research initiative, fostering collaboration between the computer science department and the School of Public Health. The site has been recognized as an "Excellent Med-X Research Site". Mengyue is dedicated to involving students from different backgrounds in research, driving innovation at the intersection of technology and science, with collaboration with many bioacoustic experts in the signal processing field.