Sotabase

Career

· Doctor of Philosophy - PhD, Computing and Mathematical Sciences, 3.5, Caltech2019–2025
· Graduate Research Assistant, Caltech2019–
· Research Assistant, Carnegie Mellon University2018–2018
· Master's degree, Computer Science, 3.92, Georgia Institute of Technology2017–2019
· Intern, iRobot2017–2017
· Bachelor's degree, Computer Science, 3.64, Georgia Tech2012–2016

Publications (0)

Differentiable MPC for End-to-end Planning and Control
Neural Information Processing Systems · 2018
431
cited
LyaNet: A Lyapunov Framework for Training Neural ODEs
International Conference on Machine Learning · 2022
73
cited
Optimization Methods for Interpretable Differentiable Decision Trees in Reinforcement Learning
2019
33
cited
Learning First-Order Representations for Planning from Black-Box States: New Results
International Conference on Principles of Knowledge Representation and Reasoning · 2021
26
cited
Self-Supervised Online Learning for Safety-Critical Control using Stereo Vision
IEEE International Conference on Robotics and Automation · 2022
16
cited
Flexible FOND Planning with Explicit Fairness Assumptions
International Conference on Automated Planning and Scheduling · 2021
12
cited
Interpretable Reinforcement Learning via Differentiable Decision Trees
arXiv.org · 2019
12
cited
Neural Gaits: Learning Bipedal Locomotion via Control Barrier Functions and Zero Dynamics Policies
Conference on Learning for Dynamics & Control · 2022
8
cited
Safe Drone Flight with Time-Varying Backup Controllers
IEEE/RJS International Conference on Intelligent RObots and Systems · 2022
7
cited
FI-ODE: Certified and Robust Forward Invariance in Neural ODEs
arXiv.org · 2022
6
cited
Constructive Nonlinear Control of Underactuated Systems via Zero Dynamics Policies
IEEE Conference on Decision and Control · 2024
4
cited
Learning Unstable Dynamics with One Minute of Data: A Differentiation-based Gaussian Process Approach
arXiv.org · 2021
4
cited
FI-ODE: Certifiably Robust Forward Invariance in Neural ODEs
2022
3
cited
FOND Planning with Explicit Fairness Assumptions
2022
3
cited
Robust Agility via Learned Zero Dynamics Policies
IEEE/RJS International Conference on Intelligent RObots and Systems · 2024
3
cited
Learning to Control an Unstable System with One Minute of Data: Leveraging Gaussian Process Differentiation in Predictive Control
IEEE/RJS International Conference on Intelligent RObots and Systems · 2021
2
cited
KALIKO: Kalman-Implicit Koopman Operator Learning For Prediction of Nonlinear Dynamical Systems
arXiv.org · 2025
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