Hi there!

I am currently a final-year Ph.D. student in the Department of Computer Science and Engineering at Texas A&M University. I am working at the DATA Lab under the supervision of Prof. Xia (Ben) Hu since 2019. My research interests lie in the general area of artifiicial intelligence, machine learning and data science, and recently Large Language Models (LLM). Here is my CV.


I’ll join the Department of Computer and Data Sciences at Case Western Reserve University as a tenure-track assistant professor in Fall 2024.

[Prospective Students] I’m seeking multiple self-motivated students (Ph.D., Internship) for Fall 2024, Spring/Fall 2025. If you’re interested in Efficient LLM, Understanding LLM, LLM Agents, Graph Foundation Models, please email me at xhan.hire@gmail.com with your CV and transcripts, for more details, refer to Group.


News

Publications

  • ACL2024 PokeMQA: Programmable knowledge editing for Multi-hop Question Answering [PDF]
    • Hengrui Gu, Kaixiong Zhou, Xiaotian Han, Ninghao Liu, Ruobing Wang, Xin Wang
    • ACL2024
  • ICML2024 LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning [PDF][Github]
    • Hongye Jin*, Xiaotian Han*, Jingfeng Yang, Zhimeng Jiang, Zirui Liu, Chia-Yuan Chang, Huiyuan Chen, Xia Hu
    • ICML2024
  • ICLR2024 FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods [PDF] [Github]
    • Xiaotian Han, Jianfeng Chi, Yu Chen, Qifan Wang, Han Zhao, Na Zou, Xia Hu.
    • ICLR2024
  • TKDD Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond [PDF] [Github]
    • Jingfeng Yang*, Hongye Jin*, Ruixiang Tang*, Xiaotian Han*, Qizhang Feng*, Haoming Jiang, Bing Yin, Xia Hu
    • TKDD, 2023
  • NeurIPS2023 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
  • KDDExp2022 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
  • AMIA2023 Does Synthetic Data Generation of LLMs Help Clinical Text Mining? [PDF]
    • Xiaotian Han*, Ruixiang Tang*, Xiaoqian Jiang, Xia Hu
    • AMIA, 2023
  • TMLR2023 Retiring ∆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
  • ICLR2023 MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization. [PDF] [SLIDES][CODE]
    • Xiaotian Han, Tong Zhao, Yozen Liu, Xia Hu, Neil Shah
    • ICLR2023
  • ICML2022 $\mathcal{G}$-Mixup: Graph Augmentation for Graph Classification. [PDF] [SLIDES]
    • Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Xia Hu.
    • ICML2022, Outstanding Paper Award
  • WWW2022 Geometric Graph Representation Learning via Maximizing Rate Reduction. [PDF] [SLIDES] [CODE]
    • Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Qingquan Song, Jundong Li, Xia Hu.
    • TheWebConf2022
  • IJCAI2018 Aspect-Level Deep Collaborative Filtering via Heterogeneous Information Networks. [PDF] [CODE]
    • Xiaotian Han, Chuan Shi, Senzhang Wang, S Yu Philip, Li Song.
    • IJCAI2018
  • APWeb2018 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
  • AAAI2024-SRRAI 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).
  • ICLR2022 Generalized Demographic Parity for Group Fairness. [PDF]
    • Zhimeng Jiang, Xiaotian Han, Chao Fan, Fan Yang, Ali Mostafavi, Xia Hu.
    • ICLR2022
  • Recsys2020 AutoRec: An Automated Recommender System. [PDF] [CODE]
    • Ting-Hsiang Wang, Qingquan Song, Xiaotian Han, Zirui Liu, Jin Haifeng, Xia Hu.
    • Recsys2020, Demo
  • AAAI2020 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
  • WWWJ2020 Embedding Geographic Information for Anomalous Trajectory Detection. [PDF]
    • Ding Xiao, Li Song, Ruijia Wang, Xiaotian Han, Yanan Cai, Chuan Shi.
    • World Wide Web 2020
  • KDD2019 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
  • TKDE2019 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
  • ADMA2018 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 - now, Ph.D. Student, 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
    • Publication: MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization (ICLR2023)
  • 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

Last updated on June 09, 2024.