Lily Xu headshot

she/her, they/them

CV (pdf)

Lily Xu

PhD student at Harvard

I am a PhD student in computer science at Harvard University, advised by Prof. Milind Tambe. My research focuses on advancing AI methods in machine learning and game theory to address environmental challenges, particularly wildlife conservation through poaching prevention.

I co-organize the Mechanism Design for Social Good (MD4SG) research initiative with Francisco Marmolejo Cossío, Charles Cui, George Obaido, Matthew Olckers, and Ana-Andreea Stoica. Additionally, I serve as AI Lead for the SMART Partnership, helping to build computational and research solutions for effective conservation management.

News

  • October 2023: I'm serving as co-chair of social events at EAAMO 2023. Submit your work by May 10 and come discuss opportunities to bridge research and practice!
  • July 2023: I'll be attending the International Congress for Conservation Biology (ICCB 2023) in Kigali, Rwanda and presenting in a symposium on protected area management, hosted by the SMART Partnership.
  • July 2023: Speaking at the Harvard Kennedy School class on Leading in Artificial Intelligence: Exploring Technology and Policy.
  • Spring 2023: I'll be giving guest lectures at Harvard, MIT, and Cornell, and *in-person* talks at Berkeley and Brown!
  • April 2023: I'll be giving a talk at the WWF Fuller Seminar Series. (Watch the recording on Vimeo)
  • November 2022: I'm grateful to host Ed Lada from Goodwill Keystone Area at the MD4SG colloquium. Ed will be discussing Goodwill's work on labor empowerment, supply chain, and sustainability, and opportunities for computational research. Watch the recording of Ed's talk!
  • October 2022: Organizing the workshop on AI-Assisted Decision Making for Conservation with Esther Rolf and Milind Tambe. I'm very excited to bring ecologists, computer scientists, and conservation practitioners all in a room together!
  • Fall 2022: I'll be giving talks at the Universität Tübingen (virtual), Sony CSL Paris (virtual), MIT, Ohio State University, Wellesley College, and Georgia Tech!
  • July 2022: I'm excited to moderate a panel on "Building Bridges Between AI Research and Policy" at the Hertz workshop! Panelists are Julie Owono, Jessica Fjeld, and Jacob Steinhardt.

Research interests

  • Sequential decision making: multi-armed bandits, reinforcement learning, robust planning, game theory
  • Machine learning: causal inference; data science; learning in sparse, noisy settings
  • AI for social impact: AI for conservation, bridging research and practice, community building

Publications

* indicates equal contribution

Artificial Replay: A Meta-Algorithm for Harnessing Historical Data in Bandits paper code bib 

@inproceedings{banerjee2023artificial,
  title={Artificial Replay: A Meta-Algorithm for Harnessing Historical Data in Bandits},
  author={Banerjee, Siddhartha and Sinclair, Sean R. and Tambe, Milind and Xu, Lily and Yu, Christina Lee},
  booktitle={arXiv},
  year={2023},
}

under review

(alphabetical) Siddhartha Banerjee, Sean R. Sinclair, Milind Tambe, Lily Xu, Christina Lee Yu

Ranger patrols deter poaching: first causal insights for improving protected area management bib 

@article{guo2023ranger,
  title={Ranger patrols deter poaching: first causal insights for improving protected area management},
  author={Guo, Rachel and Xu, Lily and Perrault, Andrew and Miratrix, Luke W. and Plumptre, Andrew J. and Mabonga, Joshua and Kitimbo, Herbert and Wanyama, Fredrick and Tambe, Milind and Davies, Andrew B.},
  journal={under review},
  year={2023},
}

under review

Rachel Guo*, Lily Xu*, Andrew Perrault, Luke W. Miratrix, Andrew J. Plumptre, Joshua Mabonga, Herbert Kitimbo, Fredrick Wanyama, Milind Tambe, Andrew B. Davies

Bridging adaptive management and reinforcement learning for more robust decisions paper bib 

@article{chapman2023bridging,
  title={Bridging adaptive management and reinforcement learning for more robust decisions},
  author={Chapman, Melissa and Xu, Lily and Lapeyrolerie, Marcus and Boettiger, Carl},
  journal={Philosophical Transactions of the Royal Society B},
  year={2023},
}

Phil Trans B Philosophical Transactions of the Royal Society B

Melissa Chapman, Lily Xu, Marcus Lapeyrolerie, Carl Boettiger

Flexible Budgets in Restless Bandits: A Proximal Primal-Dual Algorithm for Efficient Budget Allocation paper bib 

@inproceedings{rodriguez2023online,
title={Flexible Budgets in Restless Bandits: A Proximal Primal-Dual Algorithm for Efficient Budget Allocation},
author={Rodriguez Diaz, Paula and Killian, Jackson A. and Xu, Lily and Taneja, Aparna and Suggala, Arun Sai and Tambe, Milind},
booktitle={Proc.~Thirty-Seventh AAAI Conference on Artificial Intelligence},
year={2023},
}

AAAI 2023 37th AAAI Conference on Artificial Intelligence

Paula Rodriguez Diaz, Jackson A. Killian, Lily Xu, Aparna Taneja, Arun Sai Suggala, Milind Tambe

Optimistic Whittle Index Policy: Online Learning for Restless Bandits paper code bib 

@inproceedings{wang2023online,
  title={Optimistic Whittle Index Policy: Online Learning for Restless Bandits},
  author={Wang, Kai and Xu, Lily and Taneja, Aparna and Tambe, Milind},
  booktitle={Proc.~Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-23)},
  year={2023},
}

AAAI 2023 37th AAAI Conference on Artificial Intelligence

Kai Wang*, Lily Xu*, Aparna Taneja, Milind Tambe

Robust Planning over Restless Groups: Engagement Interventions for a Large-Scale Maternal Telehealth Program paper talk bib 

@inproceedings{killian2023groups,
  title={Robust Planning over Restless Groups: Engagement Interventions for a Large-Scale Maternal Telehealth Program},
  author={Killian, Jackson A. and Biswas, Arpita and Xu, Lily and Verma, Shresth and Nair, Vineet and Taneja, Aparna and Hegde, Aparna and Madhiwalla, Neha and Rodriguez Diaz, Paula and Johnson-Yu, Sonja and Tambe, Milind},
  booktitle={Proc.~Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-23)},
  year={2023},
}

AAAI 2023 37th AAAI Conference on Artificial Intelligence

Jackson A. Killian*, Arpita Biswas*, Lily Xu*, Shresth Verma*, Vineet Nair, Aparna Taneja, Aparna Hegde, Neha Madhiwalla, Paula Rodriguez Diaz, Sonja Johnson-Yu, Milind Tambe

Robust Restless Bandits: Tackling Interval Uncertainty with Deep Reinforcement Learning paper code bib 

@inproceedings{killian2022robust,
  title={Robust Restless Bandits: Tackling Interval Uncertainty with Deep Reinforcement Learning},
  author={Killian, Jackson A. and Xu, Lily and Biswas, Arpita and Tambe, Milind},
  booktitle={Proc.~38th Conference on Uncertainty in Artificial Intelligence (UAI 2022)},
  year={2022},
}

UAI 2022 38th Conference on Uncertainty in Artificial Intelligence

Jackson A. Killian, Lily Xu, Arpita Biswas, Milind Tambe

Ranked Prioritization of Groups in Combinatorial Bandit Allocation paper code talk bib 

@inproceedings{xu2022ranked,
  title={Ranked Prioritization of Groups in Combinatorial Bandit Allocation},
  author={Xu, Lily and Biswas, Arpita and Fang, Fei and Tambe, Milind},
  booktitle={Proc.~31st International Joint Conference on Artificial Intelligence (IJCAI-22)},
  year={2022},
}

IJCAI 2022 31st International Joint Conference on Artificial Intelligence

Lily Xu, Arpita Biswas, Fei Fang, Milind Tambe

Coordinating Followers to Reach Better Equilibria: End-to-End Gradient Descent for Stackelberg Games paper code bib 

@inproceedings{wang2021coordinating,
  title={Coordinating Followers to Reach Better Equilibria: End-to-End Gradient Descent for {Stackelberg} Games},
  author={Wang, Kai and Xu, Lily and Perrault, Andrew and Reiter, Michael K. and Tambe, Milind},
  booktitle={Proc.~36th AAAI Conference on Artificial Intelligence (AAAI-22)},
  year={2021},
}

AAAI 2022 36th AAAI Conference on Artificial Intelligence

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

Robust Reinforcement Learning Under Minimax Regret for Green Security paper code talk bib 

@inproceedings{xu2021robust,
  title={Robust Reinforcement Learning Under Minimax Regret for Green Security},
  author={Xu, Lily and Perrault, Andrew and Fang, Fei and Chen, Haipeng and Tambe, Milind},
  booktitle={Proc.~37th Conference on Uncertainty in Artificial Intelligence (UAI-21)},
  year={2021},
}

UAI 2021 37th Conference on Uncertainty in Artificial Intelligence

Lily Xu, Andrew Perrault, Fei Fang, Haipeng Chen, Milind Tambe
★ Oral Presentation

Envisioning Communities: A Participatory Approach Towards AI for Social Good paper talk bib 

@inproceedings{bondi2021envisioning,
  title={Envisioning Communities: A Participatory Approach Towards {AI} for Social Good},
  author={Bondi, Elizabeth and Xu, Lily and Acosta-Navas, Diana and Killian, Jackson A.},
  booktitle={Proc.~4th AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES-21)},
  year={2021},
}

AIES 2021 4th AAAI/ACM Conference on AI, Ethics, and Society

Elizabeth Bondi*, Lily Xu*, Diana Acosta-Navas, Jackson A. Killian

Dual-Mandate Patrols: Multi-Armed Bandits for Green Security paper code talk bib 

@inproceedings{xu2021dual,
  title={Dual-Mandate Patrols: Multi-Armed Bandits for Green Security},
  author={Xu, Lily and Bondi, Elizabeth and Fang, Fei and Perrault, Andrew and Wang, Kai and Tambe, Milind},
  booktitle={Proc.~35th AAAI Conference on Artificial Intelligence (AAAI-21)},
  year={2021}
}

AAAI 2021 35th AAAI Conference on Artificial Intelligence

Lily Xu, Elizabeth Bondi, Fei Fang, Andrew Perrault, Kai Wang, Milind Tambe
★ Best Paper Award Runner Up

Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations paper code talk bib 

@inproceedings{xu2020stay,
  title={Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations},
  author={Xu, Lily and Gholami, Shahrzad and Mc Carthy, Sara and Dilkina, Bistra and Plumptre, Andrew and Tambe, Milind and Singh, Rohit and Nsubuga, Mustapha and Mabonga, Joshua and Driciru, Margaret and others},
  booktitle={Proc.~IEEE 36th International Conference on Data Engineering (ICDE-20)},
  year={2020}
}

ICDE 2020 36th IEEE International Conference on Data Engineering

Lily Xu*, Shahrzad Gholami*, Sara Mc Carthy, Bistra Dilkina, Andrew Plumptre, Milind Tambe, Rohit Singh, Mustapha Nsubuga, Joshua Mabonga, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Tom Okello, Eric Enyel

Preprints

Learning, Optimization, and Planning Under Uncertainty for Wildlife Conservation paper talk

Preprint, for the INFORMS Doing Good with Good OR Competition 2021

Lily Xu

A High-Performance Graph Model for Near-Optimal Payments for Ecosystem Services paper

Preprint, appeared at Mechanism Design for Social Good Workshop (MD4SG 2020)

Florian Berlinger*, Lily Xu*, Yiling Chen

Enhancing Poaching Predictions for Under-Resourced Wildlife Conservation Parks Using Remote Sensing Imagery paper bib 

@inproceedings{guo2020enhancing,
  title={Enhancing Poaching Predictions for Under-Resourced Wildlife Conservation Parks Using Remote Sensing Imagery},
  author={Guo, Rachel and Xu, Lily and Plumptre, Andrew and Cronin, Drew and Okeke, Francis and Tambe, Milind},
  booktitle={NeurIPS Workshop on Machine Learning for the Developing World},
  year={2020}
}

ML4D 2020 NeurIPS Workshop on Machine Learning for Development

Rachel Guo, Lily Xu, Andrew Plumptre, Drew Cronin, Francis Okeke, Milind Tambe

Selected Media


Talks and recordings

Contact

I am happy to chat about grad school, AI for social impact, and AI for conservation. Feel free to drop me an email.

Email
[first]_[last] at g.harvard.edu
Online Mastodon: @lilyxu@hci.social
Offline
Harvard SEC Room 2.106
150 Western Avenue
Allston, MA 02134