Faculty

Institution

Unit

Venue

Han, Shuo

Assistant Professor

University of Illinois Chicago

Affiliations

College of Engineering

Electrical and Computer Engineering

Han, Shuo is currently serving as a College Of Engineering Assistant Professor at University of Illinois Chicago.

Honors

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Experiences

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Education

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Han, Shuo

University of Illinois Chicago

Assistant Professor

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computer science systems engineering reinforcement learning mathematical optimization computer security information security data science data security differential privacy communication security computational optimization control optimization vehicular technology data privacy transportation engineering machine learning data management convex analysis convex optimization on-demand transport attack simulation robust optimization control systems robotics automatic control control system security stochastic games technology control system technology privacy protection photonic devices transportation system management attack graph attack model probabilistic attack graphs proactive defense distributed systems cyber conflict distributed constraint optimization privacy-preserving communication engineering optimization cybernetics infection control constrained optimization control science data-driven optimization flight control aerial robotics taxi dispatch metropolitan areas demand uncertainties spreading processes piecewise affine objectives gradual release laplace mechanism vehicle balancing robotics automation unconstrained optimization automation engineering control technology control engineering information theory vehicle control mobility data demand response distributed robotics real-time control aeronautics threat detection network security signal estimation arbitrary side information dynamic region partitions event-based information-theoretic privacy sensitive data mobility-on-demand systems cyber-physical systems transportation networks power system optimization

Notable Scholarly Works

Notable Federal Grants

Collaborators

A Robust and Constrained Multi-Agent Reinforcement Learning Electric Vehicle Rebalancing Method in Amod Systems. 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2023)

Sihong HeYue WangShuo HanShaofeng ZouFei Miao

systems engineeringreinforcement learningelectrical engineeringamod systems

Covert Planning Against Imperfect Observers. arXiv (Cornell University) (2023)

Ma, HaoxiangShi, ChongyangHan, ShuoDorothy, Michael R.Fu, Jie

artificial intelligencecomputer sciencemathematical optimizationstochastic dynamicscovert planning agentinferenceimperfect observersmarkov decision processapproximate reasoningmultiagent systemsreinforcement learningsequential decision makingcovert planningapplied mathematicsstochastic optimization

Data-Driven Distributionally Robust Electric Vehicle Balancing for Autonomous Mobility-On-Demand Systems Under Demand and Supply Uncertainties. IEEE Transactions on Intelligent Transportation Systems (2023)

Sihong HeZhili ZhangShuo HanLynn PepinGuang WangDesheng ZhangJohn A. StankovicFei Miao

systems engineeringtransportation system managementintelligent systemssupply uncertaintieselectric vehiclesdemand responsedistribution (marketing)electrical engineeringdata sciencedata managementtransportation engineeringmobility dataautonomous mobility-on-demand systemsvehicular technology

Optimal Decoy Resource Allocation for Proactive Defense in Probabilistic Attack Graphs. arXiv (Cornell University) (2023)

Ma, HaoxiangHan, ShuoLeslie, NandiKamhoua, CharlesFu, Jie

computer sciencesystems engineeringadversarial machine learningnetwork securityprobabilistic attack graphsdecision theoryproactive defenseinformation securitycomputer securityapplied mathematics

Optimal Resource Allocation for Proactive Defense With Deception in Probabilistic Attack Graphs. Lecture notes in computer science (2023)

Haoxiang MaShuo HanCharles KamhouaJie Fu

computer scienceoptimal resource allocationattack simulationprobabilistic attack graphsproactive defenseinformation securitycomputer securitydata securitycommunication securityattack graphattack modelcyber conflictnetwork analysis

Optimizing Sensor Allocation Against Attackers With Uncertain Intentions: A Worst-Case Regret Minimization Approach. IEEE Control Systems Letters (2023)

Haoxiang MaShuo HanCharles A. KamhouaJie Fu

mathematical optimizationcomputer sciencesystems engineeringrobust game theoryattack planning problemgame theorycomputational game theorycomputer securitymarkov decision processcommunication securityuncertainty quantificationcomputational optimizationalgorithmic game theorymultiagent systemsreinforcement learningstochastic gamesstochastic optimization

Quantitative Planning With Action Deception in Concurrent Stochastic Games. arXiv (Cornell University) (2023)

Shi, ChongyangHan, ShuoFu, Jie

computer sciencequantitative planningaction deceptiongame theoryconcurrent stochastic games

Robust Electric Vehicle Balancing of Autonomous Mobility-On-Demand System: A Multi-Agent Reinforcement Learning Approach. 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2023)

Sihong HeShuo HanFei Miao

artificial intelligencesystems engineeringintelligent systemsautonomous mobility-on-demand systemengineeringcomputer engineeringreinforcement learningtransportation engineeringmachine learning

Robust Multi-Agent Reinforcement Learning With State Uncertainty. arXiv (Cornell University) (2023)

He, SihongHan, SongyangSu, SanbaoHan, ShuoZou, ShaofengMiao, Fei

computer scienceintelligent systemsstate uncertaintyreinforcement learningmachine learning

Solving Strongly Convex and Smooth Stackelberg Games Without Modeling the Follower. 2022 American Control Conference (ACC) (2023)

Yansong LiShuo Han

smooth stackelberg gamesgame theoryapplied mathematics

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Han, Shuo

Assistant Professor

University of Illinois Chicago

Affiliations

College of Engineering

Electrical and Computer Engineering

Han, Shuo is currently serving as a College Of Engineering Assistant Professor at University of Illinois Chicago.

Honors

Create free account to unlock more features

Experiences

Create free account to unlock more features

Education

Create free account to unlock more features

Han, Shuo

University of Illinois Chicago

Assistant Professor

You can click a keyword to filter the displayed items

Notable Scholarly Works

Notable Federal Grants

Collaborators

Sihong HeYue WangShuo HanShaofeng ZouFei Miao

systems engineeringreinforcement learningelectrical engineeringamod systems

Covert Planning Against Imperfect Observers. arXiv (Cornell University) (2023)

Ma, HaoxiangShi, ChongyangHan, ShuoDorothy, Michael R.Fu, Jie

Sihong HeZhili ZhangShuo HanLynn PepinGuang WangDesheng ZhangJohn A. StankovicFei Miao

Optimal Decoy Resource Allocation for Proactive Defense in Probabilistic Attack Graphs. arXiv (Cornell University) (2023)

Ma, HaoxiangHan, ShuoLeslie, NandiKamhoua, CharlesFu, Jie

computer sciencesystems engineeringadversarial machine learningnetwork securityprobabilistic attack graphsdecision theoryproactive defenseinformation securitycomputer securityapplied mathematics

Optimal Resource Allocation for Proactive Defense With Deception in Probabilistic Attack Graphs. Lecture notes in computer science (2023)

Haoxiang MaShuo HanCharles KamhouaJie Fu

Optimizing Sensor Allocation Against Attackers With Uncertain Intentions: A Worst-Case Regret Minimization Approach. IEEE Control Systems Letters (2023)

Haoxiang MaShuo HanCharles A. KamhouaJie Fu

Quantitative Planning With Action Deception in Concurrent Stochastic Games. arXiv (Cornell University) (2023)

Shi, ChongyangHan, ShuoFu, Jie

computer sciencequantitative planningaction deceptiongame theoryconcurrent stochastic games

Sihong HeShuo HanFei Miao

artificial intelligencesystems engineeringintelligent systemsautonomous mobility-on-demand systemengineeringcomputer engineeringreinforcement learningtransportation engineeringmachine learning

Robust Multi-Agent Reinforcement Learning With State Uncertainty. arXiv (Cornell University) (2023)

He, SihongHan, SongyangSu, SanbaoHan, ShuoZou, ShaofengMiao, Fei

computer scienceintelligent systemsstate uncertaintyreinforcement learningmachine learning

Solving Strongly Convex and Smooth Stackelberg Games Without Modeling the Follower. 2022 American Control Conference (ACC) (2023)

Yansong LiShuo Han

smooth stackelberg gamesgame theoryapplied mathematics

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