TAYLOR JOHNSON, PE (TN), is an Associate Professor of Computer Science (CS), Computer Engineering (CmpE), and Electrical Engineering (EE) at Vanderbilt University, where he directs the Verification and Validation for Intelligent and Trustworthy Autonomy Laboratory (VeriVITAL), is a Senior Research Scientist in the Institute for Software Integrated Systems (ISIS), and is a Faculty Affiliate of the Data Science Institute (DSI). Taylor's research focus is developing formal verification techniques and software tools for cyber-physical systems (CPS), with a focus most recently on autonomous CPS that incorporate artificial intelligence (AI) and machine learning (ML) components, such as neural networks, for tasks ranging from sensing/perception through planning/control. Taylor helps organize the Verification of Neural Networks Competition (VNN-COMP) and the Verification of Continuous and Hybrid Systems Competition (ARCH-COMP), including the AI and neural network control systems (AINNCS) category. Taylor received an AFOSR Summer Faculty Fellowship Program (SFFP) award, was a Visiting Faculty Research Program (VFRP) award fellow, is a recipient of the AFOSR Young Investigator Program (YIP) award, and an NSF CISE Research Initiation Initiative (CRII) award. His research is / has been supported by AFRL, AFOSR, ARO, DARPA, Mathworks, NSA, NSF, NVIDIA, ONR, Toyota, and USDOT.

JERRY ZHU is a full professor in the Department of Computer Sciences at the University of Wisconsin-Madison. Jerry received his Ph.D. from Carnegie Mellon University in 2005. His research interest is in machine learning, particularly machine teaching and adversarial sequential decision making. He currently serves or has served the following roles: conference chair for AISTATS and CogSci, Action Editor of Machine Learning Journal, member of DARPA ISAT advisory group. He is a recipient of a NSF CAREER Award, and winner of multiple best paper awards including an ICML classic paper prize in 2013.

KATE SAENKO is an Associate Professor of Computer Science at Boston University and a consulting professor for the MIT-IBM Watson AI Lab. She leads the Computer Vision and Learning Group at BU, is the founder and co-director of the Artificial Intelligence Research (AIR) initiative, and member of the Image and Video Computing research group. Kate received a PhD from MIT and did her postdoctoral training at UC Berkeley and Harvard. Her research interests are in the broad area of Artificial Intelligence with a focus on dataset bias, adaptive machine learning, learning for image and language understanding, and deep learning.

DR. PAVITHRA PRABHAKAR is an NSF Program Director in the Division of Computing and Communication Foundations  (CISE/CCF), on leave as a Professor of Computer Science from Kansas State University. She holds a Peggy and Gary Edwards Chair in Engineering from the College of Engineering. She obtained her doctorate in computer science and a master's degree in applied mathematics from the University of Illinois at Urbana-Champaign, followed by a CMI postdoctoral fellowship for a year at the California Institute of Technology. Prior to coming to K-State, she spent four years at the IMDEA Software Institute in Spain as a tenure-track assistant research professor. She previously interned at Bell Labs, Murray Hill, while working toward her doctorate.