collaborators

12 papers

eess.SY2026

An Update to the Level Set Theorems in Hamilton-Jacobi Reachability Analysis

Dylan Hirsch, William McEneaney, Jaime Fisac +2

Hamilton-Jacobi Reachability (HJR) is an important framework for controlling safety-critical systems despite uncertainty. Its theoretical underpinnings are rooted in Hamilton-Jacob…

eess.SY2026

Robust Direct Data-Driven Hamiltonian for Safe Set Computation under Measurement Noise and Disturbances

Mohammad Bajelani, Christopher A. Strong, Claire J. Tomlin +2

Safe set computation is a fundamental challenge in safety-critical control systems, especially in direct data-driven settings where safety analysis is performed directly from noise…

eess.SY2026

Characterization and Analysis of Emergency Landing Flight Envelopes with Graded Safety Specifications

Chams Eddine Mballo, Bryce L. Ferguson, Inkyu Jang +2

Emergency landing flight envelope analysis traditionally adopts a binary notion of safety, whereby a trajectory is safe only if state constraints are satisfied pointwise in time. I…

eess.SY2026

Inverse Safety Filtering: Inferring Constraints from Safety Filters for Decentralized Coordination

Minh Nguyen, Jingqi Li, Gechen Qu +1

Safe multi-agent coordination in uncertain environments can benefit from learning constraints from other agents. Implicitly communicating safety constraints through actions is a pr…

eess.SY2026

From Global to Local: Hierarchical Probabilistic Verification for Reachability Learning

Ebonye Smith, Sampada Deglurkar, Jingqi Li +2

Hamilton-Jacobi (HJ) reachability provides formal safety guarantees for nonlinear systems. However, it becomes computationally intractable in high-dimensional settings, motivating…

eess.SY2026

Active Calibration of Reachable Sets Using Approximate Pick-to-Learn

Sampada Deglurkar, Ebonye Smith, Jingqi Li +1

Reachability computations that rely on learned or estimated models require calibration in order to uphold confidence about their guarantees. Calibration generally involves sampling…