Ryan Shi

I am an Assistant Professor in the Department of Computer Science at the University of Pittsburgh. I work with public sector organizations to address societal challenges in food security, environmental conservation, and poverty alleviation using AI. Some of my research has been deployed at these organizations worldwide. I was the recipient of a 2023 IAAI Deployed Application Award, a 2022 Siebel Scholar Award, a 2021 Carnegie Mellon Presidential Fellowship, and was selected as a 2022 Rising Star in Data Science and ML & AI by UChicago and USC. Previously, I consulted for DataKind and interned at Microsoft and Facebook. I got my Ph.D. in Societal Computing from Carnegie Mellon University advised by Fei Fang and a B.A. in Mathematics and Computer Science from Swarthmore College.

I am looking for undergraduate and graduate students to work on research related to multi-agent systems, reinforcement learning, and LLM for public sector applications. Please send me an email if you are interested!

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Recent News

February 2024

One paper accepted to WWW-24.

December 2023

In Spring 2024, I will be teaching CS3710 Advanced Topics in AI: AI for Social Good at Pitt.

September 2023

Co-organizing the AAAI-24 Workshop on Public Sector LLMs: Algorithmic and Sociotechnical Design.

August 2023

Invited talk and panel at the RL in the Real World Workshop at the 1st International Conference on AI-generated Content (AIGC-2023).

April 2023

Started consulting for DataKind.

February 2023

NewsPanda received IAAI Deployed Application Award.

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Volunteer Engagement for Food Security

Working with Food Rescue Hero, we developed a series of AI-based tools to make sure that as many food donations reach the underprivileged communities as possible. Our work has gone through user studies and randomized trials, and has been deployed in the real world.

Predicting and Presenting Task Difficulty for Crowdsourcing Food Rescue Platforms
Zheyuan Ryan Shi, Jiayin Zhi, Siqi Zeng, Zhicheng Zhang, Ameesh Kapoor, Sean Hudson, Hong Shen, Fei Fang
WWW-24: The 2024 ACM Web Conference

A Recommender System for Crowdsourcing Food Rescue Platforms
Zheyuan Ryan Shi, Leah Lizarondo, Fei Fang
WWW-21: The 2021 ACM Web Conference
Part of book chapter in AI for Social Impact

Improving Efficiency of Volunteer-Based Food Rescue Operations
Zheyuan Ryan Shi*, Yiwen Yuan*, Kimberly Lo, Leah Lizarondo, Fei Fang
IAAI-20: 32nd Annual Conference on Innovative Applications of Artificial Intelligence

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Media Monitoring for Environmental Conservation

Working with World Wildlife Fund, we developed a set of tools powered by cutting edge language models to detect events that could pose a threat to conservation goals. Our tools have been adopted by WWF teams in multiple countries, monitoring 60K+ protected areas worldwide.

Where It Really Matters: Few-Shot Environmental Conservation Media Monitoring for Low-Resource Languages
Sameer Jain, Sedrick Scott Keh, Shova Chhetri, Karun Dewan, Pablo Izquierdo, Johanna Prussmann, Pooja Shrestha, César Suárez, Zheyuan Ryan Shi, Lei Li, Fei Fang
AAAI-24: The 38th Annual AAAI Conference on Artificial Intelligence

NewsPanda: Media Monitoring for Timely Conservation Action
Sedrick Scott Keh*, Zheyuan Ryan Shi*, David J. Patterson, Nirmal Bhagabati, Karun Dewan, Areendran Gopala, Pablo Izquierdo, Debojyoti Mallick, Ambika Sharma, Pooja Shrestha, Fei Fang
IAAI-23: 35th Annual Conference on Innovative Applications of Artificial Intelligence
Winner of IAAI Deployed Application Award

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Use-inspired Technical AI Research

Specializing in multi-agent systems and sequential decision making, we develop generalizable models and methods to tackle the shared pain points we observed in diverse application areas.

Bandit Data-Driven Optimization
Zheyuan Ryan Shi, Zhiwei Steven Wu, Rayid Ghani, Fei Fang
AAAI-22: the 36th AAAI Conference on Artificial Intelligence
[Full version] [Source code]

Designing the Game to Play: Optimizing Payoff Structure in Security Games
Zheyuan Ryan Shi*, Ziye Tang*, Long Tran-Thanh, Rohit Singh, Fei Fang
IJCAI-18: the 27th International Joint Conference on Artificial Intelligence
[Full version] [Source code]

Other Publications

MAVIPER: Learning Decision Tree Policies for Interpretable Multi-Agent Reinforcement Learning
Stephanie Milani, Zhicheng Zhang, Nicholay Topin, Zheyuan Ryan Shi, Charles Kamhoua, Evangelos E Papalexakis, Fei Fang
ECMLPKDD-22: the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases

Pallet Estimation for Food Bank Logistics Management
Alison Hau, Fei Fang, Zheyuan Ryan Shi
COMPASS-21: the 4th ACM SIGCAS Conference on Computing and Sustainable Societies

Draining the Water Hole: Mitigating Social Engineering Attacks with CyberTWEAK
Zheyuan Ryan Shi, Aaron Schlenker, Brian Hay, Daniel Bittleston, Siyu Gao, Emily Peterson, John Trezza, Fei Fang
IAAI-20: 32nd Annual Conference on Innovative Applications of Artificial Intelligence
[Software @Chrome Web Store] [Full version]

Learning and Planning in the Feature Deception Problem
Zheyuan Ryan Shi, Ariel D. Procaccia, Kevin S. Chan, Sridhar Venkatesan, Noam Ben-Asher, Nandi O. Leslie, Charles Kamhoua, Fei Fang
GameSec-20: the 11th Conference on Decision and Game Theory for Security

Deep Reinforcement Learning for Green Security Games with Real-Time Information
Yufei Wang, Zheyuan Ryan Shi, Lantao Yu, Yi Wu, Rohit Singh, Lucas Joppa, Fei Fang
AAAI-19: the 33rd AAAI Conference on Artificial Intelligence
[Full version] [Source code]

Optimizing Peer Teaching to Enhance Team Performance
Zheyuan Ryan Shi, Fei Fang
TEAMAS-17: First International Workshop on Teams in Multiagent Systems, at AAMAS-17
In Autonomous Agents and Multiagent Systems: AAMAS 2017 Workshops, Best Papers, Springer.
Winner of Best Paper

Strategic Reporting in Exponential Family Prediction Markets
Zheyuan Ryan Shi, Sindhu Kutty
URTC-16: 2016 MIT IEEE Undergraduate Research Technology Conference