About me

I am currently a 4th year PhD student advised by Professor Milind Tambe. I mostly work on algorithmic game theory and theory in machine learning, including statistical learning, multi-armed bandits, and applications like graph neural networks etc. I enjoy thinking any kinds of interesting math and computer science problems, which are always distracting me from my research. Please find my resume and publication below. Feel free to contact me if you are interested in my work.


Resume

My CV


Conference Publication

Getting Agents to Reach Better Equilibria: A Gradient-based Optimization Approach

Kai Wang, Lily Xu, Andrew Perrault, Michael K. Reiter, and Milind Tambe
under review

Dual-Mandate Patrols: Multi-Armed Bandits for Green Security

Lily Xu, Elizabeth Bondi, Fei Fang, Andrew Perrault, Kai Wang, and Milind Tambe
AAAI 2021 (best paper runner up)

Automatically Learning Compact Quality-aware Surrogates for Optimization Problems

Kai Wang, Bryan Wilder, Andrew Perrault, and Milind Tambe
NeurIPS 2020 (spotlight presentation)

Robust Spatial-Temporal Incident Prediction

Ayan Mukhopadhyay, Kai Wang, Andrew Perrault, Mykel Kochenderfer, Milind Tambe, and Yevgeniy Vorobeychik
UAI 2020

Scalable Game-Focused Learning of Adversary Models:Data-to-Decisions in Network Security Games

Kai Wang, Andrew Perrault, Aditya Mate, and Milind Tambe
AAMAS 2020

DeepFP for Finding Approximate Nash Equilibrium in Continuous Action Spaces

Nitin Kamra, Umang Gupta, Kai Wang, Fei Fang, Yan Liu, and Milind Tambe
GameSec 2019

Learning to Signal in the Goldilocks Zone: Improving Adversary Compliance in Security Games

Sarah Cooney, Kai Wang, Elizabeth Bondi, Thanh Nguyen, Phebe Vayanos, Hailey Winetrobe, Edward Cranford, Cleotilde Gonzalez, Christian Lebiere, and Milind Tambe
ECML 2019

Deep Fictitious Play for Games with Continuous Action Spaces

Nitin Kamra, Umang Gupta, Kai Wang, Fei Fang, Yan Liu, and Milind Tambe
Extended abstract in AAMAS 2019

The Price of Usability: Designing Operationalizable Strategies for Security Games

Sara Marie Mc Carthy, Corine Laan, Kai Wang, Phebe Vayanos, Milind Tambe, and Arunesh Sinha
IJCAI 2018

Equilibrium Refinement in Security Games with Arbitrary Scheduling Constraints

Kai Wang, Qingyu Guo, Phebe Vayanos, Milind Tambe, and Bo An
AAMAS 2018

Strategic Coordination of Human Patrollers and Mobile Sensors with Signaling for Security Games

Haifeng Xu, Kai Wang, Phebe Vayanos, and Milind Tambe
AAAI 2018


Workshop Publication

Balance Between Scalability and Optimality in Network Security Games

Kai Wang AAMAS 2020 Doctoral Consortium

Adversarial Machine Learning with Double Oracle

Kai Wang, Bryan Wilder, and Milind Tambe
IJCAI 2019 Doctoral Consortium

Improving GP-UCB Algorithm by Harnessing Decomposed Feedback

Kai Wang, Bryan Wilder, Sze-chuan Suen, Milind Tambe, and Bistra Dilkina
ECML 2019 SoGood Workshop

Mobile Game Theory with Street Gangs

Sarah Cooney, Wendy Gomez, Kai Wang, Jorja Leap, P. Jeffery Brantingham, and Milind Tambe
ECML 2019 SoGood Workshop

Routing Games with Priorities

Kai Wang, Hong-Jyun Wang, and Ho-Lin Chen
AAAC 2016