A Flexible Concept for Designing Multiaxis Force/Torque Sensors Using Force Closure Theorem. - Dangxiao Wang; Jing Guo; Chuangchuang Sun; Mu Xu; Yuru Zhang (IEEE Trans. Instrum. Meas., 2013)

Distributed estimation for spatial rigid motion based on dual quaternions. - Yue Zu; Chuangchuang Sun; Ran Dai (CDC, 2014)

Identification of network topology via quadratic optimization. - Chuangchuang Sun; Ran Dai (ACC, 2015)

An iterative approach to Rank Minimization Problems. - Chuangchuang Sun; Ran Dai (CDC, 2015)

A decomposition method for nonconvex quadratically constrained quadratic programs. - Chuangchuang Sun; Ran Dai (ACC, 2017)

A customized ADMM for rank-constrained optimization problems with approximate formulations. - Chuangchuang Sun; Ran Dai (CDC, 2017)

Rank-constrained optimization and its applications. - Chuangchuang Sun; Ran Dai (Autom., 2017)

An Efficient Module Detection Algorithm for Large-Scale Complex Networks. - Chuangchuang Sun; Ran Dai (ACC, 2018)

Distributed Optimization for Convex Mixed-Integer Programs based on Projected Subgradient Algorithm. - Chuangchuang Sun; Ran Dai (CDC, 2018)

Weighted Network Design With Cardinality Constraints via Alternating Direction Method of Multipliers. - Chuangchuang Sun; Ran Dai; Mehran Mesbahi (IEEE Trans. Control. Netw. Syst., 2018)

Joint Estimation of OD Demands and Cost Functions in Transportation Networks from Data. - Salomón Wollenstein-Betech; Chuangchuang Sun; Jing Zhang 030; Ioannis Ch. Paschalidis (CDC, 2019)

An Iterative Rank Penalty Method for Nonconvex Quadratically Constrained Quadratic Programs. - Chuangchuang Sun; Ran Dai (SIAM J. Control. Optim., 2019)

Automata Guided Semi-Decentralized Multi-Agent Reinforcement Learning. - Chuangchuang Sun; Xiao Li 013; Calin Belta (ACC, 2020)

Continuous-Time Safe Learning with Temporal Logic Constraints in Adversarial Environments. - Chuangchuang Sun; Kyriakos G. Vamvoudakis (ACC, 2020)

Scaling Up Multiagent Reinforcement Learning for Robotic Systems: Learn an Adaptive Sparse Communication Graph. - Chuangchuang Sun; Macheng Shen; Jonathan P. How (IROS, 2020)

Optimal composition of heterogeneous multi-agent teams for coverage problems with performance bound guarantees. - Chuangchuang Sun; Shirantha Welikala; Christos G. Cassandras (Autom., 2020)

Set-Invariant Constrained Reinforcement Learning with a Meta-Optimizer. - Chuangchuang Sun; Dong-Ki Kim; Jonathan P. How (CoRR, 2020)

Temporal-Logic-Based Intermittent, Optimal, and Safe Continuous-Time Learning for Trajectory Tracking. - Aris Kanellopoulos; Filippos Fotiadis; Chuangchuang Sun; Zhe Xu 005; Kyriakos G. Vamvoudakis; Ufuk Topcu; Warren E. Dixon (CDC, 2021)

A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning. - Dong-Ki Kim; Miao Liu 001; Matthew Riemer; Chuangchuang Sun; Marwa Abdulhai; Golnaz Habibi; Sebastian Lopez-Cot; Gerald Tesauro; Jonathan P. How (ICML, 2021)

FISAR: Forward Invariant Safe Reinforcement Learning with a Deep Neural Network-Based Optimizer. - Chuangchuang Sun; Dong-Ki Kim; Jonathan P. How (ICRA, 2021)

Reachability Analysis of Neural Feedback Loops. - Michael Everett; Golnaz Habibi; Chuangchuang Sun; Jonathan P. How (IEEE Access, 2021)

A Unified Formulation and Nonconvex Optimization Method for Mixed-Type Decision-Making of Robotic Systems. - Chuangchuang Sun; Nathaniel Kingry; Ran Dai (IEEE Trans. Robotics, 2021)

ROMAX: Certifiably Robust Deep Multiagent Reinforcement Learning via Convex Relaxation. - Chuangchuang Sun; Dong-Ki Kim; Jonathan P. How (ICRA, 2022)

Influencing Long-Term Behavior in Multiagent Reinforcement Learning. - Dong-Ki Kim; Matthew Riemer; Miao Liu 001; Jakob N. Foerster; Michael Everett; Chuangchuang Sun; Gerald Tesauro; Jonathan P. How (NeurIPS, 2022)

An efficient approach for nonconvex semidefinite optimization via customized alternating direction method of multipliers. - Chuangchuang Sun (CoRR, 2022)

Joint Data-Driven Estimation of Origin-Destination Demand and Travel Latency Functions in Multiclass Transportation Networks. - Salomón Wollenstein-Betech; Chuangchuang Sun; Jing Zhang 030; Christos G. Cassandras; Ioannis Ch. Paschalidis (IEEE Trans. Control. Netw. Syst., 2022)

Wasserstein Distributionally Robust Control Barrier Function using Conditional Value-at-Risk with Differentiable Convex Programming. - Alaa Eddine Chriat; Chuangchuang Sun (CoRR, 2023)

Distributionally Safe Reinforcement Learning under Model Uncertainty: A Single-Level Approach by Differentiable Convex Programming. - Alaa Eddine Chriat; Chuangchuang Sun (CoRR, 2023)

Distributed Optimization for Rank-Constrained Semidefinite Programs. - Chaoying Pei; Sixiong You; Chuangchuang Sun; Ran Dai (IEEE Control. Syst. Lett., 2023)

On the Optimality, Stability, and Feasibility of Control Barrier Functions: An Adaptive Learning-Based Approach. - Alaa Eddine Chriat; Chuangchuang Sun (IEEE Robotics Autom. Lett., 2023)

Constrained Meta-Reinforcement Learning for Adaptable Safety Guarantee with Differentiable Convex Programming. - Minjae Cho; Chuangchuang Sun (AAAI, 2024)

Towards an Adaptable and Generalizable Optimization Engine in Decision and Control: A Meta Reinforcement Learning Approach. - Sungwook Yang; Chaoying Pei; Ran Dai; Chuangchuang Sun (CoRR, 2024)

Out-of-Distribution Adaptation in Offline RL: Counterfactual Reasoning via Causal Normalizing Flows. - Minjae Cho; Jonathan P. How; Chuangchuang Sun (CoRR, 2024)

Sparsity-based Safety Conservatism for Constrained Offline Reinforcement Learning. - Minjae Cho; Chuangchuang Sun (CoRR, 2024)

Multi-Task Learning for Few-Shot Online Adaptation under Signal Temporal Logic Specifications. - Andres Arias; Chuangchuang Sun (CoRR, 2024)

Hierarchical Meta-Reinforcement Learning via Automated Macro-Action Discovery. - Minjae Cho; Chuangchuang Sun (CoRR, 2024)