I am the Frank A. and Helen E. Risch 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 am currently funded by an NSF CAREER Award.
Finally, I've gotten to work with some fantastic Ph.D. students:
Conference Proceedings
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Short-lived High-volume Bandits
ICML'23
with Su Jia, Nishant Oli, Ian Anderson, Paul Duff, and R Ravi
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Dynamic Pricing with Monotonicity Constraint under Unknown Parametric Demand Model
NeurIPS'22
with Su Jia and R Ravi
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Markovian Interference in Experiments
NeurIPS'22 Oral Presentation (< 2%)
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
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Uncertainty Quantification for Low-Rank Matrix Completion with Heterogeneous and Sub-Exponential Noise
AISTATS'22
with Vivek Farias and Tianyi Peng
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Greedy Approximation Algorithms for Active Sequential Hypothesis Testing
NeurIPS'21
with Kyra Gan and Su Jia
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Learning Treatment Effects in Panels with General Intervention Patterns
NeurIPS'21 Oral Presentation (< 1%)
with Vivek Farias and Tianyi Peng
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Causal Inference with Selectively-Deconfounded Data
AISTATS'21
with Kyra Gan, Zachary Lipton, and Sridhar Tayur
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Near-Optimal Entrywise Anomaly Detection for Low-Rank Matrices with Sub-Exponential Noise
ICML'21
with Vivek Farias and Tianyi Peng
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Disposable Linear Bandits for Online Recommendations
AAAI'21
with Melda Korkut
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Optimizing Offer Sets in Sub-linear Time
EC'20
with Vivek Farias and Deeksha Sinha
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Optimal Recovery of Tensor Slices
AISTATS'18
with Vivek Farias
Completed Articles
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Online Resource Allocation with Predictions under Unknown Arrival Model
Submitted
with Lin An, Ben Moseley, and Gabriel Visotsky
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Markdown Pricing Under Unknown Demand
Submitted
with Ningyuan Chen, Su Jia and R Ravi
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Markdown Pricing Under an Unknown Parametric Demand Model
Major Revision in Management Science
with Su Jia and R Ravi
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Learning Treatment Effects in Panels with General Intervention Patterns
Major Revision in Operations Research
with Vivek Farias and Tianyi Peng
Finalist, MSOM Best Student Paper Prize, 2022
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Short-lived High-volume Multi-A(rmed)/B(andits) Testing
Major Revision in Operations Research
with Su Jia, Nishant Oli, Ian Anderson, Paul Duff, and R Ravi
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The Nonstationary Newsvendor with (and without) Predictions
Major Revision in Manufacturing & Service Operations Management
with Lin An, Ben Moseley, and R Ravi
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Causal Inference with Selectively-Deconfounded Data
Major Revision in Management Science
with Kyra Gan, Zachary Lipton, and Sridhar Tayur
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Toward a Liquid Biopsy: Greedy Approximation Algorithms for Active Sequential Hypothesis Testing
Management Science
with Kyra Gan, Su Jia, and Sridhar Tayur
Co-winner, Pierskalla Best Paper Award, 2021
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Optimizing Offer Sets in Sub-linear Time
Management Science, 2024
with Vivek Farias, Deeksha Sinha, and Andrew Zheng
Finalist, INFORMS RM&P Student Paper Award, 2020
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Solving the Phantom Inventory Problem
Manufacturing & Service Operations Management, 2024
with Vivek Farias and Tianyi Peng
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Protein Corona Sensor Array Nanosystem for Detection of Coronary Artery Disease
Small, 2024
with Gha Young Lee, Claudia Corbo et al.
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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
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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
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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, Omid Farokhzad et al.
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Optimal Resource Consumption with an Application to Cloud Infrastructure via Data-Driven Prophet Inequalities
with Muhammad Amjad, Vivek Farias, and Devavrat Shah
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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
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Approximate Blocking Probabilities in Loss Models with Independence and Distribution Assumptions Relaxed
Performance Evaluation, 2014
with Ward Whitt
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Ordered Multiplicity Lists for Eigenvalues of Symmetric Matrices Whose Graph is a Linear Tree
Discrete Mathematics, 2014
with Charles Johnson and Andrew Walker