Lily Xu headshot

she/her, they/them

CV (pdf)

Lily Xu

Postdoc at Oxford, soon Columbia

I am a computer scientist developing AI methods across machine learning, optimization, and causal inference for planetary health challenges, particularly to address environmental challenges such as biodiversity conservation. I will join as an assistant professor at Columbia University in fall 2025, in the department of Industrial Engineering and Operations Research. Until then, I'll be a postdoc at the University of Oxford with the Leverhulme Centre for Nature Recovery, working with Alex Teytelboym.

I co-direct the EAAMO research initiative, which advances computational techniques to improve access to opportunity for historically marginalized communities. Additionally, I partner closely with NGOs to bridge research and practice, serving as AI Lead for the SMART Partnership, where I help build computational and research solutions for effective conservation management.

I received my PhD in computer science from Harvard University, where I was fortunate to be advised by Milind Tambe, and my AB from Dartmouth College, where I studied computer science and Spanish.

News

Research interests

I'll be recruiting PhD students for the December 2024 application cycle.

If you're interested in AI for sustainability, public-sector operations research, or algorithmic decision-making, please send me an email!

Students with a strong background in applied math, optimization, or operations research can apply to Columbia IEOR. Students with a background in computer science can apply to Columbia CS. Students with a background in ecology, economics, or other disciplines can apply to Columbia E3B or the Sustainable Development PhD program at Columbia SIPA, where I may also be able to serve as a co-advisor.

To learn more about my work, see my research statement and teaching statement.

  • Sequential decision making: multi-armed bandits, reinforcement learning, robust planning, game theory
  • Machine learning: ML + causality; ML + optimization; data science; learning in sparse, noisy settings
  • AI for social impact: AI for conservation, bridging research and practice, community building
  • Environmental conservation: nature financing, protected area management, ranger-based monitoring

Working papers

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 Nampindo, Simon and Tambe, Milind and Davies, Andrew B.},
  journal={under review},
  year={2023},
}

working paper

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

Unlocking the value of ranger-based monitoring for biodiversity conservation and protected area management bib

@inproceedings{kuiper2024unlocking,
  title={Unlocking the value of ranger-based monitoring for biodiversity conservation and protected area management},
  author={Kuiper, Tim and Dancer, Anthony and Beale, Colin and Ghoddousi, Arash and Ibbett, Harriet and Joanny, Laure and Kavhu, Blessing and Keane, Aidan and Makaza, Daniel and Milner-Gulland, E.J. and Moore, Jennifer and Xu, Lily},
  booktitle={under review},
  year={2024},
}

under review

Timothy Kuiper, Anthony Dancer, Colin M. Beale, Arash Ghoddousi, Harriet Ibbett, Laure Joanny, Aidan Keane, Blessing Kavhu, Daniel Makaza, E.J. Milner-Gulland, Jennifer F. Moore, and Lily Xu

From Maps to Models: Participation and Contestability in the Dynamic Management of Natural Resources paper bib

@inproceedings{scoville2024from,
  title={From Maps to Models: Participation and Contestability in the Dynamic Management of Natural Resources},
  author={Scoville, Caleb and Amironesei, Razvan and Xu, Lily and Chapman, Melissa and R Record, Nicholas and Boettiger, Carl},
  booktitle={under review},
  year={2024},
}

under review

Caleb Scoville, Razvan Amironesei, Lily Xu, Melissa Chapman, Nicholas R Record, and Carl Boettiger

A Bayesian Approach to Online Learning for Contextual Restless Bandits with Applications to Public Health paper bib

@inproceedings{liang2024bayesian,
  title={A {Bayesian} Approach to Online Learning for Contextual Restless Bandits with Applications to Public Health},
  author={Liang, Biyonka and Xu, Lily and Taneja, Aparna and Tambe, Milind and Janson, Lucas},
  booktitle={arXiv},
  year={2024},
}

under review

Biyonka Liang, Lily Xu, Aparna Taneja, Milind Tambe, Lucas Janson

Reinforcement learning with combinatorial actions for coupled restless bandits paper bib

@inproceedings{xu2023reinforcement,
  title={Reinforcement learning with combinatorial actions for coupled restless bandits},
  author={Xu, Lily and Wilder, Bryan and Khalil, Elias B. and Tambe, Milind},
  booktitle={arXiv},
  year={2023},
}

under review

Lily Xu, Bryan Wilder, Elias B. Khalil, Milind Tambe

Reflections from the Workshop on AI-Assisted Decision Making for Conservation paperbib

@inproceedings{xu2023reflections,
  title={Reflections from the Workshop on {AI}-Assisted Decision Making for
  Conservation},
  author={Xu, Lily and Rolf, Esther and Beery, Sara and Bennett, Joseph R. and Berger-Wolf, Tanya and Birch, Tanya and Bondi-Kelly, Elizabeth and Brashares, Justin and Chapman, Melissa and Corso, Anthony and Davies, Andrew and Garg, Nikhil and Gaylard, Angela and Heilmayr, Robert and Kerner, Hannah and Klemmer, Konstantin and Kumar, Vipin and Mackey, Lester and Monteleoni, Claire and Moorcroft, Paul and Palmer, Jonathan and Perrault, Andrew and Thau, David and Tambe, Milind},
  booktitle={arXiv},
  year={2023},
}

white paper

Lily Xu*, Esther Rolf*, Sara Beery, Joseph R. Bennett, Tanya Berger-Wolf, Tanya Birch, Elizabeth Bondi-Kelly, Justin Brashares, Melissa Chapman, Anthony Corso, Andrew Davies, Nikhil Garg, Angela Gaylard, Robert Heilmayr, Hannah Kerner, Konstantin Klemmer, Vipin Kumar, Lester Mackey, Claire Monteleoni, Paul Moorcroft, Jonathan Palmer, Andrew Perrault, David Thau, Milind Tambe

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},
}

working paper

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

Publications

* indicates equal contribution

High-stakes decisions from low-quality data: AI decision-making for planetary health

paper bib
@phdthesis{xu2024highstakes,
  title={High-stakes decisions from low-quality data: {AI} decision-making for planetary health},
  author={Xu, Lily},
  year={2024},
  month={May},
  address={Cambridge, MA},
  note={Available at \url{https://lily-x.github.io/files/LilyXu_dissertation.pdf}},
  school={Harvard University},
  type={PhD thesis}
}

PhD dissertation

Lily Xu

Biodiversity monitoring for a just planetary future paper bib

@article{chapman2024,
  title={Biodiversity monitoring for a just planetary future},
  author={Chapman, Melissa and Goldstein, Benjamin R. and Schell, Christopher J. and Brashares, Justin S. and Carter, Neil H. and Ellis-Soto, Diego and Faxon, Hilary Oliva and Golstein, Jenny E. and Halpern, Benjamin S. and Longdon, Joycelyn and Norman, Kari EA and O'Rourke, Dara and Scoville, Caleb and Xu, Lily and Boettiger, Carl},
  journal={Science},
  volume={383},
  number={6678},
  pages={34--36},
  year={2024},
  publisher={American Association for the Advancement of Science},
}

Science 2024

Melissa Chapman, Benjamin R. Goldstein, Christopher J. Schell, Justin S. Brashares, Neil H. Carter, Diego Ellis-Soto, Hilary Oliva Faxon, Jenny E. Goldstein, Benjamin S. Halpern, Joycelyn Longdon, Kari EA Norman, Dara O'Rourke, Caleb Scoville, Lily Xu, Carl Boettiger

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)},
  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)},
  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

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 (AAAI)},
  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

Bridging adaptive management and reinforcement learning for more robust decisions paper open-access 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},
  volume={378},
  number={1881},
  pages={20220195},
  year={2023},
  publisher={The Royal Society},
}

Phil Trans B 2023 Philosophical Transactions of the Royal Society B

Melissa Chapman, Lily Xu, Marcus Lapeyrolerie, Carl Boettiger

Environment, Society, and Machine Learning (book chapter) paper open-access bib

@incollection{scoville2023environment,
  author    = {Scoville, Caleb and Faxon, Hilary and Chapman, Melissa and Fried, Samantha Jo and Xu, Lily and Boettiger, Carl and Reed, J. Michael and Lapeyrolerie, Marcus and Van Scoyoc, Amy and Amironesei, Razvan},
  title       = {Environment, Society, and Machine Learning},
  editor      = {Borch, Christian and Pardo-Guerra, Juan Pablo},
  booktitle   = {Oxford Handbook of the Sociology of Machine Learning},
  publisher   = {Oxford University Press},
  year        = {2023},
}

Oxford University Press 2023 Oxford Handbook of the Sociology of Machine Learning

Caleb Scoville, Hilary Faxon, Melissa Chapman, Samantha Jo Fried, Lily Xu, Carl Boettiger, J. Michael Reed, Marcus Lapeyrolerie, Amy Van Scoyoc, and Razvan Amironesei

Restless and Uncertain: Robust Policies for Restless Bandits via Deep Multi-Agent Reinforcement Learning paper code bib

@inproceedings{killian2022restless,
  title={Restless and Uncertain: Robust Policies for Restless Bandits via Deep Multi-Agent 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)},
  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)},
  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{wang2022coordinating,
  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)},
  year={2022},
}

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)},
  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)},
  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)},
  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 Wanyama, Fred and Rwetsiba, Aggrey and Okello, Tom and Enyel, Eric},
  booktitle={Proc.~IEEE 36th International Conference on Data Engineering (ICDE)},
  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

Workshop Papers

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

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

Lily Xu

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

Email
[first].[last initial] at columbia.edu
[first].[last] at economics.ox.ac.uk
Online
Offline
Manor Road Building
Room 249
Oxford OX1 3UQ

Website designed by Lily. © 2024