Bio: Changliu is an assistant professor in the Robotics Institute at CMU, where she leads Intelligent Control Lab. Prior to joining CMU in 2019, she was a postdoc at Stanford Intelligent Systems Laboratory. She obtained her Ph.D from Berkeley in 2017, where she worked in Mechanical Systems & Control Lab. She got her bachelor degree from Tsinghua University in 2012. Her primary research focus is on the design and verification of intelligent systems that work with people, with application to manufacturing and transportation. She published the book Designing Robot Behavior in Human-Robot Interactions with CRC press in 2019. She teaches 16-899 Adaptive Control and Reinforcement Learning (fall) and 16-883 Provably Safe Robotics (spring). She has an online course on neural verification.

Bio: Eric Wolff is a Principal Research Scientist at Motional, where he leads the Autonomy Research team. He has worked in the autonomous vehicle industry for over seven years, contributing to motion planning, optimization-based control, and motion forecasting. He completed a PhD in Control and Dynamical Systems at the California Institute of Technology, and a BS in Mechanical Engineering at Cornell University.

Bio: Karen will be joining the William E. Boeing Department of Aeronautics & Astronautics at the University of Washington an Assistant Professor in Fall 2022. Currently, she is a Research Scientist at NVIDIA Research working in the Autonomous Vehicle Research Group. She obtained her M.S. and Ph.D. in Aeronautics and Astronautics from Stanford University where she was a member of the Stanford Autonomous Systems Lab, directed by Marco Pavone. Broadly speaking, her research focuses on using formal methods and verification techniques for safe interaction-aware planning and control for human-robot interactions.

Bio: Dr. McDonough received his doctorate in 2015 in which his thesis focused on the quick computation and modification of positively-invariant, constraint-admissible sets of initial aircraft states for the generation of constraint admissible flight paths, the development of a novel control scheme known as the Controller State and Reference Governor (CSRG), and stochastically-optimal, fuel-efficient control schemes for automotive applications. Dr. McDonough joined Bihrle Applied Research in June, 2016 as a Senior Research Engineer. Since then, his research efforts have been directed towards the use of UAS to inspect transportation infrastructure, the integration of UAS into urban environments, and machine learning and AI techniques for airspace mapping and UAS routing.

Bio: Lillian (Lily) Ratliff is an Assistant Professor in the Department of Electrical Engineering at the University of Washington. She also holds an Adjunct Professor position in the Allen School of Computer Science and Engineering at UW. Prior to joining UW she was a postdoctoral researcher in EECS at UC Berkeley (2015-2016) where she also obtained her PhD (2015) under the advisement of Shankar Sastry. She holds a MS (UNLV 2010) and BS (UNLV 2008) in Electrical Engineering as well as a BS (UNLV 2008) in Mathematics. Lillian's research interests lie at the intersection of game theory, learning, and optimization. She draws on theory from these areas to develop analysis tools for studying algorithmic competition, cooperation and collusion and synthesis tools for designing algorithms with performance guarantees. In addition, she is interested in developing new theoretical models of human decision-making in consideration of behavioral factors in societal-scale systems (e.g., intelligent infrastructure, platform-based markets and e-commerce, etc.) and computational schemes to shape the outcome of competitive interactions. Lillian is the recipient of an NSF Graduate Research Fellowship (2009), NSF CISE Research Initiation Initiative award (2017), and an NSF CAREER award (2019), and the ONR Young Investigator award (2020). Lillian was also an invited speaker at the NAE China-America Frontiers of Engineering Symposium (2019) and recently awarded the Dhanani Endowed Faculty Fellowship (2020).

Bio: Necmiye received her B.S. degree in Electrical and Electronics Engineering from Bogazici University, Istanbul in 2004, her M.S. degree in Electrical Engineering from the Pennsylvania State University, University Park, PA in 2006 and her Ph.D degree again in Electrical Engineering from Northeastern University, Boston, MA in 2010. Between 2010 and 2013, she was a Control and Dynamical Systems postdoctoral scholar at the Department of Computing and Mathematical Sciences at California Institute of Technology, Pasadena, CA. She joined the Electrical Engineering and Computer Science Department at the University of Michigan, Ann Arbor, MI, in Fall 2013, where she is currently an associate professor. She is part of the Michigan Controls Group, a core member of Michigan Robotics and also affiliated with the Michigan Institute for Data Science (MIDAS) and Michigan Institute for Computational Discovery & Engineering (MICDE).