papers

Publications (101)

cs.AI2021

Learning Density Distribution of Reachable States for Autonomous Systems

Yue Meng, Dawei Sun, Zeng Qiu +2

State density distribution, in contrast to worst-case reachability, can be leveraged for safety-related problems to better quantify the likelihood of the risk for potentially hazar…

cs.LG2023

Signal Temporal Logic Neural Predictive Control

Yue Meng, Chuchu Fan

Ensuring safety and meeting temporal specifications are critical challenges for long-term robotic tasks. Signal temporal logic (STL) has been widely used to systematically and rigo…

cs.RO2022

Safe Control with Learned Certificates: A Survey of Neural Lyapunov, Barrier, and Contraction methods

Charles Dawson, Sicun Gao, Chuchu Fan

Learning-enabled control systems have demonstrated impressive empirical performance on challenging control problems in robotics, but this performance comes at the cost of reduced t…

cs.CL2025

TUMIX: Multi-Agent Test-Time Scaling with Tool-Use Mixture

Yongchao Chen, Jiefeng Chen, Rui Meng +6

While integrating tools like Code Interpreter and Search has significantly enhanced Large Language Model (LLM) reasoning in models like ChatGPT Agent and Gemini-Pro, practical guid…

eess.SY2017

Road to safe autonomy with data and formal reasoning

Chuchu Fan, Bolun Qi, Sayan Mitra

We present an overview of recently developed data-driven tools for safety analysis of autonomous vehicles and advanced driver assist systems. The core algorithms combine model-base…

cs.LG2025

Scalable Surrogate Verification of Image-based Neural Network Control Systems using Composition and Unrolling

Feiyang Cai, Chuchu Fan, Stanley Bak

Verifying safety of neural network control systems that use images as input is a difficult problem because, from a given system state, there is no known way to mathematically model…