Xiaotian Han

Max Han

Hi there!

I am an Assistant Professor of Computer Science at Case Western Reserve University from Fall 2024. I completed my Ph.D. at Texas A&M University. My research focuses on artificial intelligence, machine learning, data science, and, more recently, large language models (LLMs). You can contact me via xhan (at) case.edu.

google scholar / \(\mathbb{X}\) / bluesky / github / cv

[Prospective Students] I’m seeking multiple self-motivated students (Ph.D., Internship) for Fall 2025. If you’re interested in LLM and AI4Sci, please email me at xhan.hire@gmail.com with your CV and transcripts after you submitted the application. For more details, refer to here.

News

Blogs

Publications

  • On the Equivalence of Graph Convolution and Mixup [pdf]
    • Xiaotian Han, Hanqing Zeng, Yu Chen, Shaoliang Nie, Jingzhou Liu, Kanika Narang, Zahra Shakeri, Karthik Abinav Sankararaman, Song Jiang, Madian Khabsa, Qifan Wang, Xia Hu
    • TMLR2024, LoG2024 TMLR Track Oral Presentation
  • PokeMQA: Programmable knowledge editing for Multi-hop Question Answering [pdf]
    • Hengrui Gu, Kaixiong Zhou, Xiaotian Han, Ninghao Liu, Ruobing Wang, Xin Wang
    • ACL2024
  • LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning [pdf][code]
    • Hongye Jin*, Xiaotian Han*, Jingfeng Yang, Zhimeng Jiang, Zirui Liu, Chia-Yuan Chang, Huiyuan Chen, Xia Hu
    • ICML2024, Spotlight (3.5%)
  • FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods [pdf] [code]
    • Xiaotian Han, Jianfeng Chi, Yu Chen, Qifan Wang, Han Zhao, Na Zou, Xia Hu.
    • ICLR2024
  • Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond [pdf] [code]
    • Jingfeng Yang*, Hongye Jin*, Ruixiang Tang*, Xiaotian Han*, Qizhang Feng*, Haoming Jiang, Bing Yin, Xia Hu
    • TKDD, 2023
  • Chasing Fairness under Distribution Shift: a Model Weight Perturbation Approach [pdf]
    • Xiaotian Han*, Zhimeng Jiang*, Hongye Jin, Guanchu Wang, Rui Chen, Na Zou, Xia Hu.
    • NeurIPS2023
  • Marginal Nodes Matter: Towards Structure Fairness in Graphs. [pdf]
    • Xiaotian Han, Kaixiong Zhou, Ting-Hsiang Wang, Jundong Li, Fei Wang, Na Zou
    • KDD Explorations, 2022
  • Does Synthetic Data Generation of LLMs Help Clinical Text Mining? [pdf]
    • Xiaotian Han*, Ruixiang Tang*, Xiaoqian Jiang, Xia Hu
    • AMIA, 2023
  • Retiring \(\Delta\)DP: New Distribution-Level Metrics for Demographic Parity. [pdf]
    • Xiaotian Han*, Zhimeng Jiang*, Hongye Jin*, Zirui Liu, Na Zou, Qifan Wang, Xia Hu
    • TMLR, 2023
  • MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization. [pdf][code]
    • Xiaotian Han, Tong Zhao, Yozen Liu, Xia Hu, Neil Shah
    • ICLR2023
  • \(\mathcal{G}\)-Mixup: Graph Augmentation for Graph Classification. [pdf]
    • Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Xia Hu.
    • ICML2022, Outstanding Paper Award
  • Geometric Graph Representation Learning via Maximizing Rate Reduction. [pdf] [code]
    • Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Qingquan Song, Jundong Li, Xia Hu.
    • TheWebConf2022
  • Aspect-Level Deep Collaborative Filtering via Heterogeneous Information Networks. [pdf] [code]
    • Xiaotian Han, Chuan Shi, Senzhang Wang, S Yu Philip, Li Song.
    • IJCAI2018
  • Representation Learning with Depth and Breadth for Recommendation using Multi-view Data. [pdf]
    • Xiaotian Han, Chuan Shi, Lei Zheng, S Yu Philip, Jianxin Li, Yuanfu Lu.
    • APWeb-WAIM2018
  • Chasing Fairness in Graphs: A GNN Architecture Perspective
    • Zhimeng Jiang, Xiaotian Han, Chao Fan, Zirui Liu, Na Zou, Ali Mostafavi, Xia Hu.
    • AAAI, 2024, Special Track on Safe, Robust and Responsible AI (SRRAI).
  • Generalized Demographic Parity for Group Fairness. [pdf]
    • Zhimeng Jiang, Xiaotian Han, Chao Fan, Fan Yang, Ali Mostafavi, Xia Hu.
    • ICLR2022
  • AutoRec: An Automated Recommender System. [pdf] [code]
    • Ting-Hsiang Wang, Qingquan Song, Xiaotian Han, Zirui Liu, Jin Haifeng, Xia Hu.
    • Recsys2020, Demo
  • FlowScope: Spotting Money Laundering Based on Graphs. [pdf]
    • Xiangfeng Li, Shenghua Liu, Zifeng Li, Xiaotian Han, Chuan Shi, Bryan Hooi, He Huang, Xueqi Cheng.
    • AAAI2020
  • Embedding Geographic Information for Anomalous Trajectory Detection. [pdf]
    • Ding Xiao, Li Song, Ruijia Wang, Xiaotian Han, Yanan Cai, Chuan Shi.
    • World Wide Web 2020
  • Metapath-guided Heterogeneous Graph Neural Network for Intent Recommendation. [pdf]
    • Shaohua Fan, Junxiong Zhu, Xiaotian Han, Chuan Shi, Linmei Hu, Biyu Ma, Yongliang Li.
    • KDD2019
  • Deep Collaborative Filtering with Multi-aspect Information in Heterogeneous Networks. [pdf]
    • Chuan Shi, Xiaotian Han, Li Song, Xiao Wang, Senzhang Wang, Junping Du, Philip, S Yu.
    • TKDE2019
  • Anomalous Trajectory Detection Using Recurrent Neural Network. [pdf]
    • Li Song, Ruijia Wang, Ding Xiao, Xiaotian Han, Yanan Cai, Chuan Shi.
    • ADMA2018, Best Paper Award

Preprints

  • Do We Really Achieve Fairness with Explicit Sensitive Atrributes?,
    • Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Na Zou, Qifan Wang, Xia Hu
  • You Only Debias Once: Towards Flexible Accuracy-Fairness Trade-offs at Inference Time,
    • Xiaotian Han, Tianlong Chen, Kaixiong Zhou, Zhimeng Jiang, Zhangyang Wang, Xia Hu
  • GrowLength: Accelerating LLMs Pretraining by Progressively Growing Training Length [pdf],
    • Xiaotian Han , Hongye Jin, Jingfeng Yang, Zhimeng Jiang, Chia-Yuan Chang, Xia Hu
  • Fair Graph Message Passing with Transparency, Zhimeng Jiang,
    • Xiaotian Han, Chao Fan, Zirui Liu, Na Zou, Ali Mostafavi, Xia Hu
  • Towards Assumption-free Bias Mitigation,
    • Chia-Yuan Chang, Yu-Neng Chuang, Kwei-Herng Lai, Xiaotian Han, Xia Hu, Na Zou
  • Gradient Rewiring for Editable Graph Neural Network Training,
    • Zhimeng Jiang, Zirui Liu, Xiaotian Han, Qizhang Feng, Hongye Jin, Qiaoyu Tan, Kaixiong Zhou, Na Zou, Xia Hu
  • Beyond Fairness: Age-Harmless Parkinson’s Detection via Voice,
    • Yicheng Wang, Xiaotian Han, Leisheng Yu, Na Zou
  • Reducing Communication Overhead in Distributed GNN Training via Client-Server Knowledge Distillation,
    • Song Jiang, Xiaotian Han, Yinglong Xia, Qifan Wang, Yizhou Sun

Educations

  • Aug. 2019 - Aug. 2024, Ph.D., Computer Science, Texas A&M University.
  • Sept. 2016 - Jun. 2019, Master Degree, Computer Science, Beijing Univ. of Posts and Telecommunications.
  • Sept. 2011 - Jun. 2015, Bacheler Degree, Communication Engineering, Shandong University.

Internships

  • Amazon, Palo Alto, CA. May 2023 – Aug 2023
  • Meta, Menlo Park, CA. Sept. 2022 – April 2023
    • Research Intern
    • Understanding graph neural networks
    • Work with Qifan Wang
  • Snap Research, Seattle, WA. Mar. 2022 - Aug. 2022
    • Research Intern
    • Graph neural network training acceleration.
    • Work with Neil Shah, Tong Zhao, Yozen Liu
  • Microsoft Research Asia, Beijing, China. Mar. 2019 - May. 2019
    • Research Intern
    • Hyperparameter Optimization and AutoML.
  • Alibaba Group, Hangzhou, China. Jun. 2018 - Sept. 2018
    • Research Intern
    • Query recomendataion in Taobao App.

Awards & Honors

  • Jane Street Graduate Research Fellowship Award Honorable Mention, 2024
  • Outstanding Paper Award, ICML2022
  • Excellent Ph.D. Student Award (One Per Year), Department of CSE, Texas A&M University, 2023
  • NeurIPS2023 Scholar Award
  • Grad School Research and Presentation Travel Award, Texas A&M University, 2023
  • Best Paper Awards, ADMA2018
  • Travel Grant, Department of Computer Science & Engineering, Texas A&M University, 2022, 2023
  • Travel Award, ICML2022.
  • Outstanding Reviewer Award, ICML2022.
  • Best Reviewer Award, CCF Transactions on Pervasive Computing and Interaction 2020

Professional Acitivities

  • Reviewer ICLR2023,2024; ICML2022,2023,2024; NeurIPS2022,2023,2024; AAAI2021,2022,2023,2024; WWW2023; WSDM2024; CIKM2023; IJCAI2021,2023; EMNLP2023; ICDM2022;
  • Session Chair WWW2023, ICML2022

Copyright © 2025 Xiaotian Han; last updated on 01/22/2025