1st ACM SIGKDD Workshop on Ethical Artificial Intelligence: Methods and Applications
August 15, 2022, Washington DC
August 15, 2022, Washington DC
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Chen Zhao, Kitware Inc. Short bio: Dr. Zhao is a senior R&D computer researcher at Kitware Inc. He received his Ph.D. in Computer Science from the University of Texas at Dallas in 2021. Dr. Zhao’s research interests include large-scale data mining, machine learning and computer vision with a focus on fairness-aware machine learning and novelty detection. His research has been accepted and published in premier conferences, including KDD, ICDM, AAAI, WWW, PAKDD, etc. Besides, Dr. Zhao served as PC members of top international conferences, such as KDD, ICDM, AAAI, SDM, BigData, AISTATS, WSDM, WACV, etc. |
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Feng Chen, The University of Texas at Dallas Short bio: Dr. Chen is an Associate Professor at the Department of Computer Science at the University of Texas at Dallas, where he directs the Pattern Discovery and Machine Learning Laboratory. He was previously an Assistant Professor at University at Albany – SUNY and a Postdoctoral Fellow at Carnegie Mellon University. He received his Ph.D. in Computer Science from Virginia Tech in 2012. Dr. Chen’s research interests include large-scale data mining, network mining, and machine learning, with a focus on event and pattern discovery in massive, complex networks. His research has been funded by NSF, NIH, ARO, IARPA, and the U.S. Department of Transportation, and published in more than 100 peer-reviewed in premier conferences, such as KDD, ICDM, WWW, CIKM, AAAI, IJCAI, ICML, and NeurIPS, and in top journals, such as TKDD, TKDE, TIST, KAIS, and Proceedings of the IEEE. He is a recipient of NSF CAREER award in 2018 and the NSF FAI award entitled “A Novel Paradigm for Fairness-Aware Deep Learning Models on Data Streams” in 2022 as the principal investigator (PI). |
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Xintao Wu, University of Arkansas Short bio: Dr. Wu is a Professor and the Charles D. Morgan/Acxiom Endowed Graduate Research Chair in Database and leads Social Awareness and Intelligent Learning (SAIL) Lab in Computer Science and Computer Engineering Department at University of Arkansas. Dr. Wu has co-authored over 150 scholarly papers, many of which were published in premier conferences. Dr. Wu is an associate editor or editorial board member of several journals and program committees as area chair, senior PC, and PC of top international conferences. He also served as the program co-chair of the 2020 IEEE International Conference on Big Data, publication co-chair of KDD15, and award co-chair of DSAA 18 & 19. Dr. Wu gave multiple tutorials on causality-based ethical AI in top international conferences, including ACM KDD and IEEE BigData. |
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Christopher Funk, Kitware Inc. Short bio: Dr. Funk is a senior R&D computer researcher at Kitware Inc. He is primarily involved in computer vision/machine learning projects and his research interests are in symmetry detection, keypoint detection, learning with limited labels, remote sensing, and novelty detection. He leads the two Defense Advanced Research Projects Agency (DARPA) projects at Kitware, Learning with Less Labeling and SAIL-ON Novelty Detection. He has helped organize a symmetry detection workshop for ICCV 2017, a novelty detection workshop for WACV 2022, and has helped organize the main CVPR 2017 conference. He is also chairing the WACV 2023 conference and creates the main conference visualization for CVPR, ICCV, and WACV. He has published in multiple top-tier computer vision conferences including CVPR, ICCV, and ECCV. Dr. Funk received his Ph.D. from Pennsylvania State University in 2018. He has been a program chair/reviewer for ICML, ICLR, CVPR, ICCV, ECCV, WACV, etc. |
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Anthony Hoogs, Kitware Inc. Short bio: Dr. Hoogs is the Vice President of AI at Kitware. He coordinates AI activities across the company and leads Kitware’s Computer Vision Team, which he founded when he joined Kitware in 2007. For more than two decades, he has supervised and performed research in various areas of computer vision including: ethical and explainable AI; media forensics; event, activity and behavior recognition; deep learning; object detection, recognition and tracking; and content-based retrieval. He has led dozens of projects, sponsored by commercial companies and government entities including DARPA, AFRL, ONR, I-ARPA and NGA, that range from basic, academic research to developing advanced prototypes and demonstrations installed at operational facilities. He has been the overall Principal Investigator on multiple large DARPA programs, where he was responsible for overseeing collaborations with more than 25 universities and more than ten commercial subcontractors. At GE Global Research (1998-2007), Dr. Hoogs led a team of researchers in video and imagery analysis on projects sponsored by the US Government, Lockheed Martin and NBC Universal. He has served on technical panels for DARPA, NSF, NOAA and the National Academies, including DARPA Information Science and Technology (ISAT) panels in 2007, 2009 and 2013 and as an ISAT member 2018-2020. In 2019 he served as the lead organizer for an ISAT study on ethical reasoning in computational autonomy. Dr. Hoogs received a Ph.D. in Computer and Information Science from the University of Pennsylvania in 1998. He has published more than 80 papers in computer vision, pattern recognition, artificial intelligence and remote sensing. His academic service includes General Chair and Program Chair roles for major computer vision conferences such as the IEEE/CVF Conference on Computer Vision and Pattern Recognition and the IEEE Winter conference on Applications of Computer Vision. He has co-organized more than ten workshops at major AI conferences. He regularly serves as an Area Chair and on program committees for the primary computer vision and AI conferences and workshops. |
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Jiayu Zhou, Michigan State University. Short bio: Dr. Zhou is an associate professor at Department of Computer Science and Engineering, Michigan State University. Before joining MSU, Jiayu was a staff research scientist at Samsung Research America. Jiayu received his Ph.D. degree in computer science at Arizona State University in 2014. Jiayu has a broad research interest in large-scale machine learning and data mining, and biomedical informatics. |