7/16/2021 Jim Ormond, ACM
Winning dissertation by Chuchu Fan (MS '16, PhD '19) makes foundational contributions to verification of embedded and cyber-physical systems.
Written by Jim Ormond, ACM
ACM, the Association for Computing Machinery, announced that Chuchu Fan (MS '16, PhD '19) received the 2020 ACM Doctoral Dissertation Award for her dissertation “Formal Methods for Safe Autonomy: Data-Driven Verification, Synthesis, and Applications.” The dissertation makes foundational contributions to the verification of embedded and cyber-physical systems and demonstrates the applicability of the developed verification technologies in industrial-scale systems.
Presented annually to the author(s) of the best doctoral dissertation(s) in computer science and engineering, the Doctoral Dissertation Award is accompanied by a prize of $20,000. The winning dissertations will also be published in the ACM Digital Library as part of the ACM Books Series. Fan is the first PhD graduate from the University of Illinois Urbana-Champaign to receive this award.
Fan’s dissertation also advances the theory for sensitivity analysis and symbolic reachability; develops verification algorithms and software tools (DryVR, Realsyn); and demonstrates applications in industrial-scale autonomous systems.
Key contributions of her dissertation include the first data-driven algorithms for bounded verification of nonlinear hybrid systems using sensitivity analysis. A groundbreaking demonstration of this work on an industrial-scale problem showed that verification can scale. Her sensitivity analysis technique was patented, and a startup based at the University of Illinois at Urbana-Champaign has been formed to commercialize this approach.
Fan also developed the first verification algorithm for “black box” systems with incomplete models combining probably approximately correct (PAC) learning with simulation relations and fixed point analyses. DryVR, a tool that resulted from this work, has been applied to dozens of systems, including advanced driver assist systems, neural network-based controllers, distributed robotics, and medical devices.
Additionally, Fan’s algorithms for synthesizing controllers for nonlinear vehicle model systems have been demonstrated to be broadly applicable. The RealSyn approach presented in the dissertation outperforms existing tools and is paving the way for new real-time motion planning algorithms for autonomous vehicles.
Fan's PhD research advisor, Illinois ECE Professor Sayan Mitra, commended this outstanding recognition. "Chuchu’s work combining formal methods and statistics provides tools for analyzing systems that were previously beyond our grasp." Mitra added that "working with her was very enjoyable. Every time we would formulate a conjecture, she worked on it ferociously until she emerged with a proof and working code, or an interesting corner case." Over the course of her PhD research Fan also worked closely with a number of other graduate students and faculty, including Zhenqi Huang, Hussein Sibai, Prof. Mahesh Viswanathan of Illinois CS, Prof. Marta Kwiatkowska of Oxford University, and Prof. Scott Smolka of SUNY Stony Brook.
Fan is the Wilson Assistant Professor of Aeronautics and Astronautics at the Massachusetts Institute of Technology, where she leads the Reliable Autonomous Systems Lab. Her group uses rigorous mathematics including formal methods, machine learning, and control theory for the design, analysis, and verification of safe autonomous systems. Fan received a BA in Automation from Tsinghua University. She earned her PhD in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign.
Honorable Mentions for the 2020 ACM Doctoral Dissertation Award go to Henry Corrigan-Gibbs for his dissertation from Stanford University, and Ralf Jung for his dissertation from Saarland University and the Max Planck Institute for Software Systems.
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Read the original announcement from ACM on its website.