Andrew A. Li

I am an Assistant Professor of Operations Research at CMU Tepper. I completed my Ph.D. at the Operations Research Center at MIT.

My research interests are in statistics, optimization, and machine learning, with applications to operations management and medicine.

I've gotten to work with some fantastic Ph.D. students:

• Lin An
• Tianyi Peng
• Kyra Gan (Assistant Professor, Cornell Tech)
• Su Jia (Research Assistant Professor, Cornell ORIE)
• Melda Korkut (Applied Scientist, Amazon Machine Learning Science)

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Conference Proceedings

• Dynamic Pricing with Monotonicity Constraint under Unknown Parametric Demand Model
  NeurIPS'22
  with Su Jia and R Ravi
• Markovian Interference in Experiments
  NeurIPS'22 Oral Presentation
  with Vivek Farias, Tianyi Peng, and Andrew Zheng
  Winner, INFORMS Applied Probability Society Best Student Paper Prize, 2022
  Winner, INFORMS RM&P Student Paper Award, 2022
• Uncertainty Quantification for Low-Rank Matrix Completion with Heterogeneous and Sub-Exponential Noise
  AISTATS'22
  with Vivek Farias and Tianyi Peng
• Greedy Approximation Algorithms for Active Sequential Hypothesis Testing
  NeurIPS'21
  with Kyra Gan and Su Jia
• Learning Treatment Effects in Panels with General Intervention Patterns
  NeurIPS'21 Oral Presentation (< 1%)
  with Vivek Farias and Tianyi Peng
• Causal Inference with Selectively-Deconfounded Data
  AISTATS'21
  with Kyra Gan, Zachary Lipton, and Sridhar Tayur
• Near-Optimal Entrywise Anomaly Detection for Low-Rank Matrices with Sub-Exponential Noise
  ICML'21
  with Vivek Farias and Tianyi Peng
• Disposable Linear Bandits for Online Recommendations
  AAAI'21
  with Melda Korkut
• Optimizing Offer Sets in Sub-linear Time
  EC'20
  with Vivek Farias and Deeksha Sinha
• Optimal Recovery of Tensor Slices
  AISTATS'18
  with Vivek Farias

Completed Articles

• Toward a Liquid Biopsy: Greedy Approximation Algorithms for Active Sequential Hypothesis Testing
  Submitted
  with Kyra Gan, Su Jia, and Sridhar Tayur
  Co-winner, Pierskalla Best Paper Award, 2021
• Learning Treatment Effects in Panels with General Intervention Patterns
  Submitted
  with Vivek Farias and Tianyi Peng
  Finalist, MSOM Best Student Paper Prize, 2022
• Solving the Phantom Inventory Problem
  Submitted
  with Vivek Farias and Tianyi Peng
• Markdown Pricing Under Unknown Demand
  Major Revision in Management Science
  with Su Jia and R Ravi
• Causal Inference with Selectively-Deconfounded Data
  Major Revision in Management Science
  with Kyra Gan, Zachary Lipton, and Sridhar Tayur
• Optimizing Offer Sets in Sub-linear Time
  Major Revision in Management Science
  with Vivek Farias and Deeksha Sinha
  Finalist, INFORMS RM&P Student Paper Award, 2020
• Learning Preferences with Side Information
  Management Science, 2021
  with Vivek Farias
  First Place, Nicholson Student Paper Competition, 2017
  Finalist, INFORMS Applied Probability Society Best Student Paper Prize, 2017
• Machine Learning Algorithms for Predicting Hospital Re-admissions in Sickle Cell Disease
  British Journal of Haematology, 2021
  with Arisha Patel, Kyra Gan, Jeremy Weiss, Seyed Nouraie, Sridhar Tayur, and Enrico Novelli
• Analysis of the Human Plasma Proteome Using Multi-Nanoparticle Protein Corona Characterization for Detection of Alzheimer’s Disease
  Advanced Healthcare Materials, 2020
  with Claudia Corbo et al.
• Optimal Resource Consumption with an Application to Cloud Infrastructure via Data-Driven Prophet Inequalities
  with Muhammad Amjad, Vivek Farias, and Devavrat Shah
• Staffing to Stabilize Blocking in Loss Models with Time-Varying Arrival Rates
  Probability in the Engineering and Informational Sciences, 2016
  with Ward Whitt and Jingtong Zhao
• Approximate Blocking Probabilities in Loss Models with Independence and Distribution Assumptions Relaxed
  Performance Evaluation, 2014
  with Ward Whitt
• Ordered Multiplicity Lists for Eigenvalues of Symmetric Matrices Whose Graph is a Linear Tree
  Discrete Mathematics, 2014
  with Charles Johnson and Andrew Walker