MAIR Faculty
MAIR Faculty
Vishnu Boddeti
Associate Professor, Michigan State University
Department of Computer Science and Engineering
Email Lab Website
Vishnu Boddeti is an Associate Professor in the Department of Computer Science and Engineering at Michigan State University. He received a Ph.D. in Electrical and Computer Engineering from Carnegie Mellon University in 2013. His research interests are in fairness, privacy, and security of computer vision systems. He also works on making AI systems more computationally efficient and on topics at the intersection of AI and Physics. Papers co-authored by him have received multiple awards including Best Paper Awards at BTAS 2013 and GECCO 2019 and the Best Student Paper Awards at ACCV 2018, SMAIS 2022, IJCB 2022, and TBIOM 2023.
Associate Professor, Michigan State University
Department of Computer Science and Engineering
Email Lab Website
Vishnu Boddeti is an Associate Professor in the Department of Computer Science and Engineering at Michigan State University. He received a Ph.D. in Electrical and Computer Engineering from Carnegie Mellon University in 2013. His research interests are in fairness, privacy, and security of computer vision systems. He also works on making AI systems more computationally efficient and on topics at the intersection of AI and Physics. Papers co-authored by him have received multiple awards including Best Paper Awards at BTAS 2013 and GECCO 2019 and the Best Student Paper Awards at ACCV 2018, SMAIS 2022, IJCB 2022, and TBIOM 2023.
Mohammad Ghassemi
Assistant Professor, Michigan State University
Department of Computer Science and Engineering
Email
Dr. Mohammad M. Ghassemi is an Assistant Professor of Computer Science at Michigan State University, where he leads the Human Augmentation and Artificial Intelligence Laboratory. He performs research to enable robust machine learning in circumstances where: (1) data are limited, (2) data are noisy, and (3) humans are actively involved in sensitive decision-making procedures. He holds graduate degrees from the Massachusetts Institute of Technoloy (PhD), and the University of Cambridge (MPhil). Dr. Ghassemi was formerly a director of data science at S&P Global, and a strategic consultant with BCG. He is the lead inventor on multiple US Patents, the author of a widely consumed book on health informatics (over 1 Million downloads), and has authored over 50 peer-reviewed scientific papers in venues including: Nature (Scientific Data), Science (Translational Medicine), Proceedings of the IEEE, and the Proceedings of the Association for the Advancement of Artificial Intelligence. His scientific contributions have been cited over 9,000 times. He is also a Senior member of the Institute of Electrical and Electronics Engineers.
Assistant Professor, Michigan State University
Department of Computer Science and Engineering
Dr. Mohammad M. Ghassemi is an Assistant Professor of Computer Science at Michigan State University, where he leads the Human Augmentation and Artificial Intelligence Laboratory. He performs research to enable robust machine learning in circumstances where: (1) data are limited, (2) data are noisy, and (3) humans are actively involved in sensitive decision-making procedures. He holds graduate degrees from the Massachusetts Institute of Technoloy (PhD), and the University of Cambridge (MPhil). Dr. Ghassemi was formerly a director of data science at S&P Global, and a strategic consultant with BCG. He is the lead inventor on multiple US Patents, the author of a widely consumed book on health informatics (over 1 Million downloads), and has authored over 50 peer-reviewed scientific papers in venues including: Nature (Scientific Data), Science (Translational Medicine), Proceedings of the IEEE, and the Proceedings of the Association for the Advancement of Artificial Intelligence. His scientific contributions have been cited over 9,000 times. He is also a Senior member of the Institute of Electrical and Electronics Engineers.
Anil K. Jain
Member, United States National Academy of Engineering
Distinguished Professor, Michigan State University
Department of Computer Science and Engineering
Email Lab Website
Anil Jain is a University Distinguished Professor and Douglas E. Zongker endowed professor at Michigan State University where he has taught and conducted research for 50 years. For his many advances in pattern recognition and biometrics, Jain was inducted into the United States National Academy of Engineering, Indian National Academy of Engineering, The World Academy of Sciences, Chinese Academy of Sciences and the National Academy of Inventors. Jain served as the Editor-in-Chief of the IEEE Transactions on Pattern Analysis and Machine Intelligence and was awarded the Guggenheim, Humboldt and Fulbright fellowships along with the IAPR King-Sun Fu Prize. He was appointed to the Defense Science Board, Forensic Science Standards Board, and the National Academies Study on “Facial Recognition: Current Capabilities, Future Prospects, and Governance.” He has authored foundational books in both biometrics and pattern recognition including: Introduction to Biometrics, Handbook of Face Recognition, Handbook of Fingerprint Recognition, and Algorithms for Clustering Data. For his plethora of discoveries and applications in biometrics, his service to the research community, and his extensive mentorship, Jain was awarded Doctor Honoris Causa by Universidad Autónoma de Madrid, Hong Kong University of Science and Technology and Hong Kong Baptist University.
Member, United States National Academy of Engineering
Distinguished Professor, Michigan State University
Department of Computer Science and Engineering
Email Lab Website
Anil Jain is a University Distinguished Professor and Douglas E. Zongker endowed professor at Michigan State University where he has taught and conducted research for 50 years. For his many advances in pattern recognition and biometrics, Jain was inducted into the United States National Academy of Engineering, Indian National Academy of Engineering, The World Academy of Sciences, Chinese Academy of Sciences and the National Academy of Inventors. Jain served as the Editor-in-Chief of the IEEE Transactions on Pattern Analysis and Machine Intelligence and was awarded the Guggenheim, Humboldt and Fulbright fellowships along with the IAPR King-Sun Fu Prize. He was appointed to the Defense Science Board, Forensic Science Standards Board, and the National Academies Study on “Facial Recognition: Current Capabilities, Future Prospects, and Governance.” He has authored foundational books in both biometrics and pattern recognition including: Introduction to Biometrics, Handbook of Face Recognition, Handbook of Fingerprint Recognition, and Algorithms for Clustering Data. For his plethora of discoveries and applications in biometrics, his service to the research community, and his extensive mentorship, Jain was awarded Doctor Honoris Causa by Universidad Autónoma de Madrid, Hong Kong University of Science and Technology and Hong Kong Baptist University.
Kristen Johnson
Assistant Professor, Michigan State University
Department of Computer Science and Engineering
Email Lab Website
Kristen Marie Johnson is an assistant professor in the Department of Computer Science and Engineering. Her research interests include the application of natural language processing and machine learning techniques for social computing and computational social science. She received her PhD from Purdue University in August 2019.
Assistant Professor, Michigan State University
Department of Computer Science and Engineering
Email Lab Website
Kristen Marie Johnson is an assistant professor in the Department of Computer Science and Engineering. Her research interests include the application of natural language processing and machine learning techniques for social computing and computational social science. She received her PhD from Purdue University in August 2019.
Yu Kong
Assistant Professor, Michigan State University
Department of Computer Science and Engineering
Email Lab Website
Dr. Yu Kong is now an Assistant Professor directing the ACTION Lab at Michigan State University. Prior to joining MSU, he was an Assistant Professor at the Rochester Institute of Technology, and a postdoctoral research associate at Northeastern University and University at Buffalo, SUNY. Dr. Kong's research in Computer Vision and Machine Learning has been supported by the National Science Foundation, Army Research Office, and Office of Naval Research, etc. His work has been publishing on top-tier conferences and transactions in the AI community such as CVPR, ECCV, ICCV, T-PAMI, IJCV, etc. He is an Associate Editor for Springer Journal of Multimedia Systems, and also serves as reviewers and PC members for prestige journals and conferences, including T-PAMI, T-IP, T-NNLS, T-CSVT, CVPR, ICLR, AAAI, and IJCAI.
Assistant Professor, Michigan State University
Department of Computer Science and Engineering
Email Lab Website
Dr. Yu Kong is now an Assistant Professor directing the ACTION Lab at Michigan State University. Prior to joining MSU, he was an Assistant Professor at the Rochester Institute of Technology, and a postdoctoral research associate at Northeastern University and University at Buffalo, SUNY. Dr. Kong's research in Computer Vision and Machine Learning has been supported by the National Science Foundation, Army Research Office, and Office of Naval Research, etc. His work has been publishing on top-tier conferences and transactions in the AI community such as CVPR, ECCV, ICCV, T-PAMI, IJCV, etc. He is an Associate Editor for Springer Journal of Multimedia Systems, and also serves as reviewers and PC members for prestige journals and conferences, including T-PAMI, T-IP, T-NNLS, T-CSVT, CVPR, ICLR, AAAI, and IJCAI.
Parisa Kordjamshidi
Faculty, Michigan State University
Department of Computer Science and Engineering
Email Lab Website
Parisa Kordjamshidi is an assistant professor in the Department of Computer Science and Engineering at Michigan State University. She holds an affiliated with Florida Institute for Human and Machine Cognition as a research scientist. Prior to MSU, she was an assistant professor at Tulane University (2016-2019). She was a Postdoctoral researcher at University of Illinois at Urbana-Champaign (2013-2016). She obtained her PhD from KU Leuven, Belgium, in July 2013. Her research interests include Machine learning, Natural language processing, Combining learning and reasoning paradigms and Learning-based programming. She is a recipient of a National Science Foundation Career Award in 2019.
Faculty, Michigan State University
Department of Computer Science and Engineering
Email Lab Website
Parisa Kordjamshidi is an assistant professor in the Department of Computer Science and Engineering at Michigan State University. She holds an affiliated with Florida Institute for Human and Machine Cognition as a research scientist. Prior to MSU, she was an assistant professor at Tulane University (2016-2019). She was a Postdoctoral researcher at University of Illinois at Urbana-Champaign (2013-2016). She obtained her PhD from KU Leuven, Belgium, in July 2013. Her research interests include Machine learning, Natural language processing, Combining learning and reasoning paradigms and Learning-based programming. She is a recipient of a National Science Foundation Career Award in 2019.
Sijia Liu
Assistant Professor, Michigan State University
Department of Computer Science and Engineering
Email Lab Website
Sijia Liu is currently an Assistant Professor at the CSE department of Michigan State University, and an Affiliate Professor at the MIT-IBM Watson AI Lab, IBM Research. He received the Ph.D. degree (with the All-University Doctoral Prize) in Electrical and Computer Engineering from Syracuse University, NY, USA, in 2016. He was a Postdoctoral Research Fellow at the University of Michigan, Ann Arbor, in 2016-2017, and a Research Staff Member at the MIT-IBM Watson AI Lab in 2018-2020. His research is at the forefront of developing trustworthy and scalable machine learning (ML) algorithms and systems, alongside advancing optimization theory and methods. His contributions have been recognized with several awards, including the Best Paper Runner-Up Award at the 38th Conference on Uncertainty in Artificial Intelligence (UAI’22) and the Best Student Paper Award at the 42nd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP’16). He has published over 70 papers at top-tier ML/CV conferences, including NeurIPS, ICML, ICLR, CVPR, ICCV/ECCV, AISTATS, UAI, and AAAI. He has also given tutorials at AAAI(’23, ’24), CVPR (’20, ’23), NeurIPS’22, KDD’19, ICASSP'24 and MLSP’23, and led the organization of the 1st and 2nd New Frontiers in Adversarial Machine Learning (AdvML-Frontiers) workshops at ICML ('22, '23). He is a Senior Member of IEEE, and a Technical Committee (TC) Member of Machine Learning for Signal Processing (MLSP) in the IEEE’s Signal Processing Society.
Assistant Professor, Michigan State University
Department of Computer Science and Engineering
Email Lab Website
Sijia Liu is currently an Assistant Professor at the CSE department of Michigan State University, and an Affiliate Professor at the MIT-IBM Watson AI Lab, IBM Research. He received the Ph.D. degree (with the All-University Doctoral Prize) in Electrical and Computer Engineering from Syracuse University, NY, USA, in 2016. He was a Postdoctoral Research Fellow at the University of Michigan, Ann Arbor, in 2016-2017, and a Research Staff Member at the MIT-IBM Watson AI Lab in 2018-2020. His research is at the forefront of developing trustworthy and scalable machine learning (ML) algorithms and systems, alongside advancing optimization theory and methods. His contributions have been recognized with several awards, including the Best Paper Runner-Up Award at the 38th Conference on Uncertainty in Artificial Intelligence (UAI’22) and the Best Student Paper Award at the 42nd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP’16). He has published over 70 papers at top-tier ML/CV conferences, including NeurIPS, ICML, ICLR, CVPR, ICCV/ECCV, AISTATS, UAI, and AAAI. He has also given tutorials at AAAI(’23, ’24), CVPR (’20, ’23), NeurIPS’22, KDD’19, ICASSP'24 and MLSP’23, and led the organization of the 1st and 2nd New Frontiers in Adversarial Machine Learning (AdvML-Frontiers) workshops at ICML ('22, '23). He is a Senior Member of IEEE, and a Technical Committee (TC) Member of Machine Learning for Signal Processing (MLSP) in the IEEE’s Signal Processing Society.
Xiaoming Liu
Anil K. and Nandita Jain Endowed Professor, MSU Foundation Professor, Michigan State University
Department of Computer Science and Engineering
Email Lab Website
Dr. Xiaoming Liu is the MSU Foundation Professor, and Anil and Nandita Jain Endowed Professor at the Department of Computer Science and Engineering of Michigan State University (MSU). He is also a visiting scientist at Google Research. He received Ph.D. degree from Carnegie Mellon University in 2004. Before joining MSU in 2012 he was a research scientist at General Electric (GE) Global Research. He works on computer vision, machine learning, and biometrics especially on face related analysis and 3D vision. Since 2012 he helps to develop a strong computer vision area in MSU who is ranked top 15 in US according to the 5-year statistics at csrankings.org. He is an Associate Editor of IEEE Transactions on Pattern Analysis and Machine Intelligence. He has authored more than 200 scientific publications, and has filed 35 patents. His work has been cited over 20000 times, with an H-index of 76. He is a fellow of The Institute of Electrical and Electronics Engineers (IEEE) and International Association for Pattern Recognition (IAPR).
Anil K. and Nandita Jain Endowed Professor, MSU Foundation Professor, Michigan State University
Department of Computer Science and Engineering
Email Lab Website
Dr. Xiaoming Liu is the MSU Foundation Professor, and Anil and Nandita Jain Endowed Professor at the Department of Computer Science and Engineering of Michigan State University (MSU). He is also a visiting scientist at Google Research. He received Ph.D. degree from Carnegie Mellon University in 2004. Before joining MSU in 2012 he was a research scientist at General Electric (GE) Global Research. He works on computer vision, machine learning, and biometrics especially on face related analysis and 3D vision. Since 2012 he helps to develop a strong computer vision area in MSU who is ranked top 15 in US according to the 5-year statistics at csrankings.org. He is an Associate Editor of IEEE Transactions on Pattern Analysis and Machine Intelligence. He has authored more than 200 scientific publications, and has filed 35 patents. His work has been cited over 20000 times, with an H-index of 76. He is a fellow of The Institute of Electrical and Electronics Engineers (IEEE) and International Association for Pattern Recognition (IAPR).
Hui Liu
Assistant Professor, Michigan State University
Department of Computer Science and Engineering
Email Lab Website
Hui Liu received her PhD degree in Electrical Engineering from Southern Methodist University in 2015. Her research interests include trustworthy AI, designing data mining algorithms for wireless communication of smart devices, and applying machine learning and data mining in wireless communications. She has more than 7-year research experience in data science on mobile data.
Assistant Professor, Michigan State University
Department of Computer Science and Engineering
Email Lab Website
Hui Liu received her PhD degree in Electrical Engineering from Southern Methodist University in 2015. Her research interests include trustworthy AI, designing data mining algorithms for wireless communication of smart devices, and applying machine learning and data mining in wireless communications. She has more than 7-year research experience in data science on mobile data.
Arun Ross
Martin J. Vanderploeg Endowed Professor, Michigan State University
Site Director, NSF Center for Identification Technology Research
Department of Computer Science and Engineering
Email Lab Website
Arun Ross is the John and Eva Cillag Endowed Chair in the College of Engineering and a Professor in the Department of Computer Science and Engineering. He received the B.E. (Hons.) degree in Computer Science from BITS Pilani, India, and the M.S. and PhD degrees in Computer Science and Engineering from Michigan State University. He was in the faculty of West Virginia University between 2003 and 2012 where he received the Benedum Distinguished Scholar Award for excellence in creative research and the WVU Foundation Outstanding Teaching Award. Ross is an internationally recognized expert in biometrics, computer vision and machine learning. He has advocated for the responsible use of biometrics in multiple forums including the NATO Advanced Research Workshop on Identity and Security in Switzerland in 2018. He testified as an expert panelist in an event organized by the United Nations Counter-Terrorism Committee at the UN Headquarters in 2013. Ross is a recipient of the NSF CAREER Award. He was designated a Kavli Fellow by the US National Academy of Sciences in 2006. In recognition of his contributions to the field of pattern recognition and biometrics, the International Association of Pattern Recognition (IAPR) honored him with the prestigious JK Aggarwal Prize in 2014 and the Young Biometrics Investigator Award in 2013.
Martin J. Vanderploeg Endowed Professor, Michigan State University
Site Director, NSF Center for Identification Technology Research
Department of Computer Science and Engineering
Email Lab Website
Arun Ross is the John and Eva Cillag Endowed Chair in the College of Engineering and a Professor in the Department of Computer Science and Engineering. He received the B.E. (Hons.) degree in Computer Science from BITS Pilani, India, and the M.S. and PhD degrees in Computer Science and Engineering from Michigan State University. He was in the faculty of West Virginia University between 2003 and 2012 where he received the Benedum Distinguished Scholar Award for excellence in creative research and the WVU Foundation Outstanding Teaching Award. Ross is an internationally recognized expert in biometrics, computer vision and machine learning. He has advocated for the responsible use of biometrics in multiple forums including the NATO Advanced Research Workshop on Identity and Security in Switzerland in 2018. He testified as an expert panelist in an event organized by the United Nations Counter-Terrorism Committee at the UN Headquarters in 2013. Ross is a recipient of the NSF CAREER Award. He was designated a Kavli Fellow by the US National Academy of Sciences in 2006. In recognition of his contributions to the field of pattern recognition and biometrics, the International Association of Pattern Recognition (IAPR) honored him with the prestigious JK Aggarwal Prize in 2014 and the Young Biometrics Investigator Award in 2013.
Pang-Ning Tan
Professor, Michigan State University
Department of Computer Science and Engineering
Email Lab Website
Dr. Pang-Ning Tan is a Professor in the Department of Computer Science and Engineering at MSU. He received his M.S degree in Physics and Ph.D. degree in Computer Science from University of Minnesota. His research interests span a broad range of data mining problems, from pattern discovery (association analysis, anomaly detection, and cluster analysis) to predictive modeling. In addition to addressing fundamental problems in data mining, he is also interested in applying data mining techniques to various application domains including climate and Earth sciences, social and information networks, botnet and webspam detection, and medical informatics. His research has been supported by the National Science Foundation, Office of Naval Research, Army Research Office, National Aeronautics and Space Administration, and Michigan State University.
Professor, Michigan State University
Department of Computer Science and Engineering
Email Lab Website
Dr. Pang-Ning Tan is a Professor in the Department of Computer Science and Engineering at MSU. He received his M.S degree in Physics and Ph.D. degree in Computer Science from University of Minnesota. His research interests span a broad range of data mining problems, from pattern discovery (association analysis, anomaly detection, and cluster analysis) to predictive modeling. In addition to addressing fundamental problems in data mining, he is also interested in applying data mining techniques to various application domains including climate and Earth sciences, social and information networks, botnet and webspam detection, and medical informatics. His research has been supported by the National Science Foundation, Office of Naval Research, Army Research Office, National Aeronautics and Space Administration, and Michigan State University.
Jiliang Tang
MSU Foundation Professor, Michigan State University
Department of Computer Science and Engineering
Email Lab Website
Jiliang Tang is a University Foundation Professor in the computer science and engineering department at Michigan State University. He got one early promotion to associate professor at 2021 and then a promotion to full professor (designated as MSU foundation professor) at 2022. Before that, he was a research scientist in Yahoo Research and got his PhD from Arizona State University in 2015 under Dr. Huan Liu. His research interests include graph machine learning,trustworthy AI and their applications in education and biology. He was the recipient of various awards including 2022 AI's 10 to Watch, 2022 IAPR J. K. AGGARWAL Award, 2022 SIAM/IBM Early Career Research Award, 2021 IEEE ICDM Tao Li Award, 2021 IEEE Big Data Security Junior Research Award, 2020 ACM SIGKDD Rising Star Award, 2020 Distinguished Withrow Research Award, 2019 NSF Career Award, and 8 best paper awards (or runner-ups). His dissertation won the 2015 KDD Best Dissertation runner up and Dean's Dissertation Award. He serves as conference organizers (e.g., KDD, SIGIR, WSDM and SDM) and journal editors (e.g., TKDD, TOIS and TKDE). He has published his research in highly ranked journals and top conference proceedings, which have received tens of thousands of citations with h-index 88 (Google Scholar) and extensive media coverage.
MSU Foundation Professor, Michigan State University
Department of Computer Science and Engineering
Email Lab Website
Jiliang Tang is a University Foundation Professor in the computer science and engineering department at Michigan State University. He got one early promotion to associate professor at 2021 and then a promotion to full professor (designated as MSU foundation professor) at 2022. Before that, he was a research scientist in Yahoo Research and got his PhD from Arizona State University in 2015 under Dr. Huan Liu. His research interests include graph machine learning,trustworthy AI and their applications in education and biology. He was the recipient of various awards including 2022 AI's 10 to Watch, 2022 IAPR J. K. AGGARWAL Award, 2022 SIAM/IBM Early Career Research Award, 2021 IEEE ICDM Tao Li Award, 2021 IEEE Big Data Security Junior Research Award, 2020 ACM SIGKDD Rising Star Award, 2020 Distinguished Withrow Research Award, 2019 NSF Career Award, and 8 best paper awards (or runner-ups). His dissertation won the 2015 KDD Best Dissertation runner up and Dean's Dissertation Award. He serves as conference organizers (e.g., KDD, SIGIR, WSDM and SDM) and journal editors (e.g., TKDD, TOIS and TKDE). He has published his research in highly ranked journals and top conference proceedings, which have received tens of thousands of citations with h-index 88 (Google Scholar) and extensive media coverage.
Jiayu Zhou
Associate Professor, Michigan State University
Department of Computer Science and Engineering
Email Lab Website
Jiayu 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.
Associate Professor, Michigan State University
Department of Computer Science and Engineering
Email Lab Website
Jiayu 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.
MAIR Students
Former MAIR Students
