UDM-KDD’24 - Organizers

Organizers

	Xujiang Zhao, NEC Laboratories America Short bio: Dr. Xujiang Zhao is a research staff member at NEC Laboratories America. He received his Ph.D. in the Computer Science Department at The University of Texas at Dallas in 2022. Dr. Zhao has published his work in top-tier machine learning and data mining conferences, including NeurIPS, AAAI, ICDM, and EMNLP. He also served on technical program committees for several high-impact venues, such as ICML, NeurIPS, ICLR, KDD, and AAAI.
	Chen Zhao, Baylor University. Short bio: Dr. Zhao is an Assistant Professor in the Department of Computer Science at Baylor University. His research focuses on machine learning, data mining, and artificial intelligence, particularly fairness-aware machine learning, novelty detection, and domain generalization. His publications have been accepted and published in premier conferences, including KDD, CVPR, ICDM, AAAI, WWW, etc. Dr. Zhao served as a PC member of top international conferences, such as KDD, NeurIPS, IJCAI, ICML, AAAI, ICLR, etc. He has helped organize and chair multiple workshops, including the workshops on Ethical AI (EAI-KDD’22, EAI-KDD’23, EAI-KDD'24) and the workshops on Uncertainty Reasoning and Quantification in Decision Making (UDM-AAAI’23, UDM-KDD'23, UDM-KDD'24).
	Feng Chen, 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 the 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 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 ACM and IEEE.
	Jin-Hee Cho, Virginia Tech. Short bio: Dr. Jin-Hee Cho serves as an Associate Professor in Computer Science at Virginia Tech, where she has distinguished herself in the fields of cybersecurity, decision-making, and network security through the publication of over 200 peer-reviewed technical papers in leading conferences and journals. Her contributions have been recognized with six best paper awards, encompassing four conference papers and two journal articles. Among her notable accolades is the 2015 IEEE Communications Society William R. Bennett Prize in Communications Networking. Dr. Cho's early career achievements earned her the prestigious 2013 Presidential Early Career Award for Scientists and Engineers (PECASE), the highest honor bestowed by the US government on early-stage independent researchers in science and engineering. In 2022, she was honored with the Dean's Award for Excellence as a Faculty Fellow by Virginia Tech's College of Engineering. Her research, primarily funded by the NSF, ARO, DoD, the Agency for Defense Development (South Korea), and the Commonwealth Cyber Initiative (CCI), continues to make significant impacts in her field.
	Hua Wei, Arizona State University. Short bio: Dr. Wei is an Assistant Professor in the School of Computing and Augmented Intelligence at Arizona State University. His research interests are generally in data mining and machine learning, with a particular focus on uncertainty, reinforcement learning, urban computing, human-in-the-loop computations, and, more recently, large language models. He has published over 60 papers in high-impact venues (including KDD, NeruIPS, ICLR, CVPR, USENIX Security, WSDM, IJCAI, AAAI, CIKM, ICDM, SDM, ECML-PKDD, TKDD, etc). He also has won the Best Paper Award in ECML-PKDD 2020. He performs on several grants funded by the National Science Foundation and the Department of Energy.
	Haifeng Chen, NEC Laboratories America. Short bio: Dr. Haifeng Chen is heading the Data Science and Systems Security Department at NEC Laboratories America. Haifeng has served on the program committee for several top conferences, such as SigKDD and AAAI, and has been on the panel of NSF programs. He has co-authored more than a hundred conference/journal publications, including best papers from top conferences such as SigKDD, and has over 60 patents. Most research results have led to advanced solutions and products for various industrial domains, including IT & data centers, network security, power plants, petroleum, satellite, natural disaster, finance, and retail businesses. In recognition of his extraordinary research contribution, Haifeng has received many awards in the past years, including the 2014 “NEC Contributors of the Year.”

Program Committee

To be announced.