Shuo Han

Orcid: 0000-0003-2204-6256

Affiliations:
  • University of Illinois at Chicago, IL, USA
  • University of Pennsylvania, Philadelphia, PA, USA (former)
  • California Institute of Technology, Pasadena, CA, USA (Ph.D., 2013)


According to our database1, Shuo Han authored at least 43 papers between 2014 and 2023.

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Bibliography

2023
Data-Driven Distributionally Robust Electric Vehicle Balancing for Autonomous Mobility-on-Demand Systems Under Demand and Supply Uncertainties.
IEEE Trans. Intell. Transp. Syst., May, 2023

Synthesizing Attack-Aware Control and Active Sensing Strategies Under Reactive Sensor Attacks.
IEEE Control. Syst. Lett., 2023

Optimizing Sensor Allocation Against Attackers With Uncertain Intentions: A Worst-Case Regret Minimization Approach.
IEEE Control. Syst. Lett., 2023

Covert Planning against Imperfect Observers.
CoRR, 2023

Robust Multi-Agent Reinforcement Learning with State Uncertainty.
CoRR, 2023

Robust Electric Vehicle Balancing of Autonomous Mobility-on-Demand System: A Multi-Agent Reinforcement Learning Approach.
IROS, 2023

A Robust and Constrained Multi-Agent Reinforcement Learning Electric Vehicle Rebalancing Method in AMoD Systems.
IROS, 2023

Quantitative Planning with Action Deception in Concurrent Stochastic Games.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

Optimal Decoy Resource Allocation for Proactive Defense in Probabilistic Attack Graphs.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

Synthesis of Proactive Sensor Placement In Probabilistic Attack Graphs.
Proceedings of the American Control Conference, 2023

Solving Strongly Convex and Smooth Stackelberg Games Without Modeling the Follower.
Proceedings of the American Control Conference, 2023

2022
An Approximation of 2-D Inverse Scattering Problems From a Convex Optimization Perspective.
IEEE Geosci. Remote. Sens. Lett., 2022

What is the Solution for State-Adversarial Multi-Agent Reinforcement Learning?
CoRR, 2022

A Robust and Constrained Multi-Agent Reinforcement Learning Framework for Electric Vehicle AMoD Systems.
CoRR, 2022

Accelerating Model-Free Policy Optimization Using Model-Based Gradient: A Composite Optimization Perspective.
Proceedings of the Learning for Dynamics and Control Conference, 2022

2021
Data-driven Distributionally Robust Optimization For Vehicle Balancing of Mobility-on-Demand Systems.
ACM Trans. Cyber Phys. Syst., 2021

Gradient Methods With Dynamic Inexact Oracles.
IEEE Control. Syst. Lett., 2021

A Secure and Efficient Federated Learning Framework for NLP.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Qualitative Planning in Imperfect Information Games with Active Sensing and Reactive Sensor Attacks: Cost of Unawareness.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2019
Data-Driven Robust Taxi Dispatch Under Demand Uncertainties.
IEEE Trans. Control. Syst. Technol., 2019

Systematic Design of Decentralized Algorithms for Consensus Optimization.
IEEE Control. Syst. Lett., 2019

Computational Convergence Analysis of Distributed Gradient Tracking for Smooth Convex Optimization Using Dissipativity Theory.
Proceedings of the 2019 American Control Conference, 2019

2018
Computational Convergence Analysis of Distributed Gradient Descent for Smooth Convex Objective Functions.
CoRR, 2018

Privacy in Control and Dynamical Systems.
Annu. Rev. Control. Robotics Auton. Syst., 2018

2017
Differentially Private Distributed Constrained Optimization.
IEEE Trans. Autom. Control., 2017

Data-driven distributionally robust vehicle balancing using dynamic region partitions.
Proceedings of the 8th International Conference on Cyber-Physical Systems, 2017

Quantification on the efficiency gain of automated ridesharing services.
Proceedings of the 2017 American Control Conference, 2017

2016
Taxi Dispatch With Real-Time Sensing Data in Metropolitan Areas: A Receding Horizon Control Approach.
IEEE Trans Autom. Sci. Eng., 2016

Gradual Release of Sensitive Data under Differential Privacy.
J. Priv. Confidentiality, 2016

Data-Driven Robust Taxi Dispatch Approaches.
Proceedings of the 7th ACM/IEEE International Conference on Cyber-Physical Systems, 2016

Differential privacy in control and network systems.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

Event-based information-theoretic privacy: A case study of smart meters.
Proceedings of the 2016 American Control Conference, 2016

2015
Data-Driven Network Resource Allocation for Controlling Spreading Processes.
IEEE Trans. Netw. Sci. Eng., 2015

Bio-Inspired Framework for Allocation of Protection Resources in Cyber-Physical Networks.
CoRR, 2015

Optimality of the Laplace Mechanism in Differential Privacy.
CoRR, 2015

Robust taxi dispatch under model uncertainties.
Proceedings of the 54th IEEE Conference on Decision and Control, 2015

A sublinear algorithm for barrier-certificate-based data-driven model validation of dynamical systems.
Proceedings of the 54th IEEE Conference on Decision and Control, 2015

Optimal control in Markov decision processes via distributed optimization.
Proceedings of the 54th IEEE Conference on Decision and Control, 2015

An approximately truthful mechanism for electric vehicle charging via joint differential privacy.
Proceedings of the American Control Conference, 2015

2014
Data-Driven Allocation of Vaccines for Controlling Epidemic Outbreaks.
CoRR, 2014

Computation of privacy-preserving prices in smart grids.
Proceedings of the 53rd IEEE Conference on Decision and Control, 2014

Differentially private convex optimization with piecewise affine objectives.
Proceedings of the 53rd IEEE Conference on Decision and Control, 2014

Differentially private distributed protocol for electric vehicle charging.
Proceedings of the 52nd Annual Allerton Conference on Communication, 2014


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