I am an independent group leader at the Max Planck Institute for Intelligent Systems. Previously, I was a Digital Futures Postdoctoral Fellow at the KTH Royal Institute of Technology in Stockholm where I worked with Jana Tumova in the Divison of Robotics, Perception and Learning. I'm a PhD graduate from the Stanford Intelligent Systems Lab (SISL) in the Stanford University Department of Aeronautics and Astronautics, advised by Mykel Kochenderfer.
I have been very lucky to be able to collaborate with a talented postdogtoral scholar, Jazz.
In my current position at MPI-IS, I am leading a group focused on verification and learning for intelligent systems, which relies on methods based in optimization, dynamical systems and control theory, machine learning, and formal methods.
My current primary research focus is on verification for machine learning-enabled autonomous robotic systems. I am particularly interested in analyzing systems where machine learning is part of the feedback control loop and the inputs lie in state space.
Assuring the safety and reliability of machine learning systems is especially important when machine learning is used in safety-critical applications like cars, planes, spacecraft, and more. Broadly, I am interested in applying formal methods to learning enabled systems so that we can develop more reliable data-driven algorithms. When possible, I am motivated by application domains that have socially-relevant, climate-relevant or human-focused impact.
If you are interested in these areas as well and would like to connect please reach out to me at chelsea.sidrane@tuebingen.mpg.de or apply to work with me.
Peer-Reviewed Conference Papers
Sidrane, Chelsea, and Jana Tumova. "BURNS: Backward Underapproximate Reachability for Neural-Feedback-Loop Systems." Accepted to Learning for Dynamics & Control (L4DC) 2026.
Verhagen, Joris, Elias Krantz, Chelsea Sidrane, David Dörner, Nicola De Carli, Pedro Roque, Huina Mao, Gunnar Tibert, Ivan Stenius, Christer Fuglesang, Dimos Dimarogonas, Jana Tumova. “Validation of Space Robotics in Underwater Environments via Disturbance Robustness Equivalency.” ICRA 2026.
Akinwande, Samuel, Chelsea Sidrane, Mykel J. Kochenderfer, Clark Barrett. "Verifying Nonlinear Neural Feedback Systems using Polyhedral Enclosures." Learning for Dynamics & Control (L4DC) 2026.
Schmidt, Jule, Xin Tao, Chelsea Sidrane, Swarup Kumar Mohalik, Ahkil Prasad, Jana Tumova, and Nils Jansen. “A Case for Causal Reinforcement Learning in Longitudinal Vehicle Control”. ICAART 2026.
Chelsea Sidrane and Jana Tumova. TTT: A Temporal Refinement Heuristic for Tenuously Tractable Discrete Time Reachability Problems. ACC 2025. https://arxiv.org/pdf/2407.14394
Kiessling, Alexander, Ignacio Torroba, Chelsea Rose Sidrane, Ivan Stenius, Jana Tumova, and John Folkesson. Efficient Non-Myopic Layered Bayesian Optimization For Large-Scale Bathymetric Informative Path Planning. ICRA, 2025.
Michael Kelly, Chelsea Sidrane, Katherine Driggs-Campbell and Mykel J. Kochenderfer. HG-DAgger: Interactive Imitation Learning with Human Experts. International Conference on Robotics and Automation (ICRA), 2019. https://arxiv.org/abs/1810.02890
Chelsea Sidrane, Mykel J. Kochenderfer. Closed-Loop Planning for Disaster Evacuation with Stochastic Arrivals. IEEE International Conference on Intelligent Transportation Systems (ITSC), 2018. https://drive.google.com/open?id=1l4Quv2XuYloIRcbrATVhYax8eJVku2ip
Peer-Reviewed Journal Papers
Nicholas Rober, Sydney Katz, Chelsea Sidrane, Esen Yel, Michael Everett, Mykel J. Kochenderfer, Jonathon P. How. Backward Reachability Analysis of Neural Feedback Loops: Techniques for Linear and Nonlinear Systems. 2023.
Chelsea Sidrane*, Amir Maleki*, Ahmed Irfan, Mykel Kochenderfer. OVERT: An Algorithm for Safety Verification of Neural Network Control Policies for Nonlinear Systems. Journal of Machine Learning Research (JMLR), 2022. http://jmlr.org/papers/v23/21-0847.html (* denotes equal contribution)
Peer-Reviewed Workshop Papers
Akinwande, Samuel, Chelsea Sidrane, Mykel J. Kochenderfer, Clark Barrett. Verifying Nonlinear Neural Feedback Systems using Polyhedral Enclosures. Accepted to IAGNC 2025.
Chelsea Sidrane. Safety assurance for systems with machine learning components. Doctoral Consortium, AAAI Conference on Artificial Intelligence (AAAI), 2021.
Taylor T. Johnson, Diego Manzanas Lopez, Patrick Musau, Hoang-Dung Tran, Elena Botoeva, Francesco Leofante, Amir Maleki, Chelsea Sidrane, Jiameng Fan, Chao Huang. ARCH-COMP20 Category Report: Artificial Intelligence and Neural Network Control Systems (AINNCS) for Continuous and Hybrid Systems Plants. International Workshop on Applied Verification of Continuous and Hybrid Systems, 2020. https://easychair.org/publications/paper/Jvwg
Chelsea Sidrane, Dylan J. Fitzpatrick, Andrew Annex, Diane O'Donoghue, Yarin Gal, and Piotr Biliński. Machine Learning for Generalizable Prediction of Flood Susceptibility. NeurIPS 2019 Artificial Intelligence for Humanitarian Assistance and Disaster Response Workshop. arXiv:1910.06521 (2019).
Chelsea Sidrane and Mykel J. Kochenderfer. OVERT: Verification of Nonlinear Dynamical Systems with Neural Network Controllers via Overapproximation. SafeML ICLR 2019. https://drive.google.com/uc?export=download&id=17dj7HXXzjGymoh1VUm4sfb7ynQ_R0Xem
Michael Kelly, Chelsea Sidrane, Katherine Driggs-Campbell and Mykel J. Kochenderfer. Safe Interactive Imitation Learning from Humans. NeurIPS 2018 Imitation Learning and its Challenges in Robotics. https://drive.google.com/open?id=18rJr7eXPa9rEvapyrQOfjgyQtSlMd03y
Preprints
Torroba, Ignacio, David Dorner, Victor Nan Fernandez-Ayala, Mart Kartasev, Joris Verhagen, Elias Krantz, Gregorio Marchesini, Carl Ljung, Pedro Roque, Chelsea Sidrane, Linda Van der Spaa, Nicola De Carli, Petter Ogren, Christer Fuglesang, Jana Tumova, Dimos V. Dimarogonas and Ivan Stenius. Marinarium: A New Arena to Bring Maritime Robotics Closer to Shore. arXiv preprint arXiv:2602.23053.
Chelsea Sidrane, Sydney Katz, Anthony Corso, Mykel Kochenderfer. Verifying Inverse Model Neural Networks. https://arxiv.org/abs/2202.02429
OVERT.jl
Nonlinear Overapproximation
https://github.com/sisl/OVERT.jl
OVERTVerify.jl
Reachability for Nonlinear Systems with Neural Network Control Policies
I was born and raised in the suburbs of New York City. I received my Bachelor's degree in Mechanical Engineering from Cornell University in 2016 and my Master's and PhD degrees from Stanford University in 2022. My interests include singing, comedy, cooking, skiing, hiking, ultimate frisbee, and memes.