EAI-KDD'23 Keynotes

Invited Keynote Speakers

	Chris White, NEC Laboratories America Short bio: Dr. Christopher A. White is the President of NEC Laboratories America where he leads a team of world-class researchers focusing on diverse topics from sensing to networking to machine learning based understanding. Prior to joining NEC he spent 22 years working at Bell Labs where he led the Algorithms, Analytics, Augmented Intelligence and Devices (AAAID) research lab. He joined Bell Labs in 1997 after graduating with a Ph.D. in theoretical quantum chemistry from the University of California in Berkeley, California. His research interests include the development of computational models and methods for the simulation and control of interesting physical and digital systems. This has included work in areas ranging from linear scaling quantum chemistry simulations, to the design of new optical devices, to the global control of transparent optical mesh networks and to understanding and facilitating the propagation of ideas in organizations. In addition to the management of a team of world-class researchers, Dr. White's current work focuses on the creation of assisted thinking tools that leverage structural similarity in data with the goal of augmenting human intelligence.
	Atlas Wang, The University of Texas at Austin Short bio: Dr. Atlas Wang is the Jack Kilby/Texas Instruments Endowed Assistant Professor in the Chandra Family Department of Electrical and Computer Engineering at the University of Texas at Austin. He is also a faculty member of the UT Computer Science Graduate Studies Committee (GSC) and the Oden Institute CSEM program. Prof. Wang is broadly interested in the fields of machine learning, computer vision, optimization, and their interdisciplinary applications. His latest interests focus on automated machine learning (AutoML), learning-based optimization, machine learning robustness, and efficient deep learning. His research is gratefully supported by NSF, DARPA, ARL/ARO, as well as a few more industry and university grants. He has received many research awards and scholarships, including most recently an ARO Young Investigator award, an IBM faculty research award, an Amazon research award, a Young Faculty Fellow of TAMU, and four research competition prizes from CVPR/ICCV/ECCV.
	Xia Hu, Rice University Short bio: Dr. Xia “Ben” Hu is an Associate Professor at Rice University in the Department of Computer Science. Dr. Hu has published over 200 papers in several major academic venues, including NeurIPS, ICLR, KDD, WWW, IJCAI, AAAI, etc. An open-source package developed by his group, namely AutoKeras, has become the most used automated deep learning system on Github (with over 8,000 stars and 1,000 forks). Also, his work on deep collaborative filtering, anomaly detection and knowledge graphs have been included in the TensorFlow package, Apple production system and Bing production system, respectively. His papers have received several Best Paper (Candidate) awards from venues such as ICML, WWW, WSDM, ICDM, AMIA and INFORMS. He is the recipient of NSF CAREER Award and ACM SIGKDD Rising Star Award. His work has been cited more than 20,000 times with an h-index of 58. He is the conference General Co-Chair for WSDM 2020 and ICHI 2023. He is also the founder of AI POW LLC.