Selected Research

Selected research in reversed chronological order. For the full list of my research, please refer to my Google Scholar.
Papers marked with (α-β) use alphabetical author ordering, which is a common convention in OR/IE/MS.

Data-Driven Decision Making

• Dissecting the Impact of Model Misspecification in Data-Driven Optimization
  (α-β) Adam N. Elmachtoub, Henry Lam, Haixiang Lan, Haofeng Zhang
  International Conference on Artificial Intelligence and Statistics (AISTATS), 2025

• Estimate-Then-Optimize versus Integrated-Estimation-Optimization versus Sample Average Approximation: A Stochastic Dominance Perspective
  (α-β) Adam N. Elmachtoub, Henry Lam, Haofeng Zhang, Yunfan Zhao
  Under revision in Operations Research
  

  Finalist, INFORMS George Nicholson Student Paper Competition 2023

• Optimal Regret Is Achievable with Bounded Approximate Inference Error: An Enhanced Bayesian Upper Confidence Bound Framework
  (α-β) Ziyi Huang, Henry Lam, Amirhossein Meisami, Haofeng Zhang
  Advances in Neural Information Processing Systems (NeurIPS), 2023

• The Bias-Variance Tradeoff in Data-Driven Optimization: A Local Misspecification Perspective
  Haixiang Lan, Luofeng Liao, Adam N. Elmachtoub, Christian Kroer, Henry Lam, Haofeng Zhang
  Manuscript

• Bayesian Bandit Algorithms with Approximate Inference in Stochastic Linear Bandits
  (α-β) Ziyi Huang, Henry Lam, Haofeng Zhang
  Manuscript

Prediction and Uncertainty Quantification

• Doubly Robust Stein-Kernelized Monte Carlo Estimator: Simultaneous Bias-Variance Reduction and Supercanonical Convergence
  (α-β) Henry Lam, Haofeng Zhang
  Journal of Machine Learning Research (JMLR), 2023
  

  New England Statistics Symposium Student Paper Award 2022

• Efficient Uncertainty Quantification and Reduction for Over-Parameterized Neural Networks
  (α-β) Ziyi Huang, Henry Lam, Haofeng Zhang
  Advances in Neural Information Processing Systems (NeurIPS), 2023

  Previous manuscript: Quantifying Epistemic Uncertainty in Deep Learning

• Prediction Intervals for Simulation Metamodeling
  (α-β) Henry Lam, Haofeng Zhang
  Under revision in ACM Transactions on Modeling and Computer Simulation (TOMACS)

  Conference version: Neural Predictive Intervals for Simulation Metamodeling, Winter Simulation Conference (WSC), 2021

• Learning Prediction Intervals for Regression: Generalization and Calibration
  (α-β) Haoxian Chen, Ziyi Huang, Henry Lam, Huajie Qian, Haofeng Zhang
  International Conference on Artificial Intelligence and Statistics (AISTATS), 2021

• Evaluating Aleatoric Uncertainty via Conditional Generative Models
  (α-β) Ziyi Huang, Henry Lam, Haofeng Zhang
  Manuscript

• Forecasting with Pure Time Features
  (α-β) Ziyi Huang, Haofeng Zhang
  Manuscript

Applications

• Push the Boundary of SAM: A Pseudo-label Correction Framework for Medical Segmentation
  Ziyi Huang, Hongshan Liu, Haofeng Zhang, Xueshen Li, Haozhe Liu, Fuyong Xing, Andrew Laine, Elsa Angelini, Christine Hendon, Yu Gan
  Manuscript
  

• Near-Infrared Spectroscopy Technique and Its Application in Biomedical Fields
  (α-β) Ziyi Huang, Haofeng Zhang
  Chapter of Infrared Spectroscopy - Biotechnological Applications, 2025
  

• Cardiac Adipose Tissue Segmentation via Image-Level Annotations
  Ziyi Huang, Yu Gan, Theresa Lye, Yanchen Liu, Haofeng Zhang, Andrew Laine, Elsa Angelini, Christine Hendon
  IEEE Journal of Biomedical and Health Informatics (JBHI), 2023

• Co-Seg: An Image Segmentation Framework against Label Corruption
  Ziyi Huang, Haofeng Zhang, Andrew Laine, Elsa Angelini, Christine Hendon, Yu Gan
  IEEE International Symposium on Biomedical Imaging (ISBI), 2021

• Heterogeneity Measurement of Cardiac Tissues Leveraging Uncertainty Information from Image Segmentation
  Ziyi Huang, Yu Gan, Theresa Lye, Haofeng Zhang, Andrew Laine, Elsa Angelini, Christine Hendon
  International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2020