Selected Research

Selected research in reversed chronological order. For the full list of my research, please refer to my Google Scholar.
Author ordering in most papers is alphabetical as is convention in OR/IE/MS, while exceptions are marked with ^*.

Machine Learning with Data-Driven Decision Making

• Estimate-Then-Optimize versus Integrated-Estimation-Optimization versus Sample Average Approximation: A Stochastic Dominance Perspective
  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
  Ziyi Huang, Henry Lam, Amirhossein Meisami, Haofeng Zhang
  Advances in Neural Information Processing Systems (NeurIPS), 2023

• Bayesian Bandit Algorithms with Approximate Inference in Stochastic Linear Bandits
  Ziyi Huang, Henry Lam, Haofeng Zhang
  Manuscript
  

Machine Learning with Uncertainty Quantification

• Doubly Robust Stein-Kernelized Monte Carlo Estimator: Simultaneous Bias-Variance Reduction and Supercanonical Convergence
  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
  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
  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
  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
  Ziyi Huang, Henry Lam, Haofeng Zhang
  Manuscript
  

Applied Machine Learning

• 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

• 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