Yan Han

Yan Han ιŸ©η„±

Applied Scientist @ Amazon

Ph.D., Department of Electrical and Computer Engineering
University of Texas at Austin

Experience β€’ Publications β€’ Teaching β€’ Misc
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About Me

I obtained my Ph.D. degree from the Decision, Information, and Communications Engineering (DICE) track of the Department of Electrical and Computer Engineering at The University of Texas at Austin in 2023. I was supervised by Prof. Ahmed Tewfik, Prof. Ying Ding, and Prof. Atlas Wang.

Previously, I received my B.Eng. degree from the School of Electrical Information and Electrical Engineering at Shanghai Jiao Tong University in 2017.

My research interests span Large Language Model (LLM), Agentic AI, Deep Learning, Recommendation System, and Graph Neural Network, focusing on their development, inference, and foundations for computational and statistical analysis.

Experience

Applied Science Research Intern

Amazon A9
Feb. 2022 - Dec. 2022

Machine Learning Research Intern

LinkedIn
Jun. 2021 - Dec. 2021

Research Intern

AbbVie
Feb. 2021 - May. 2021

Publications

Stepwise Perplexity-Guided Refinement for Efficient Chain-of-Thought Reasoning in Large Language Models
Yingqian Cui, Pengfei He, Jingying Zeng, Hui Liu, Xianfeng Tang, Zhenwei Dai, Yan Han, Chen Luo, Jing Huang, Zhen Li, Suhang Wang, Yue Xing, Jiliang Tang, Qi He
Findings of ACL 2025 (Long Paper)
Turning A Curse into A Blessing: Data-Aware Memory-Efficient Training of Graph Neural Networks by Dynamic Exiting
Yan Han, Kaiqi Chen, Shan Li, Ji Yan, Baoxu Shi, Lei Zhang, Fei Chen, Jaewon Yang, Yunpeng Xu, Xiaoqiang Luo, Qi He, Ying Ding, Zhangyang Wang
Companion Proceedings of the ACM Web Conference 2024 (WWW)
Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling
Haotao Wang, Ziyu Jiang, Yuning You, Yan Han, Gaowen Liu, Jayanth Srinivasa, Ramana Rao Kompella, Zhangyang Wang
Conference on Neural Information Processing Systems (NeurIPS), 2023
Vision HGNN: An Image is More than a Graph of Nodes
Yan Han, Peihao Wang, Souvik Kundu, Ying Ding, Zhangyang Wang
IEEE International Conference on Computer Vision (ICCV), 2023 Oral
Graph Contrastive Learning: An Odyssey towards Generalizable, Scalable and Principled Representation Learning on Graphs
Yan Han, Yuning You, Wenqing Zheng, Scott Hoang, Tianxin Wei, Majdi Hassan, Tianlong Chen, Ying Ding, Yang Shen, Zhangyang Wang
IEEE Data Engineering Bulletin, Vol.47 No.2 June 2023
PINAT: A Permutation INvariance Augmented Transformer for NAS Predictor
Shun Lu, Yu Hu, Peihao Wang, Yan Han, Jianchao Tan, Jixiang Li, Sen Yang, Ji Liu
AAAI Conference on Artificial Intelligence (AAAI), 2023
Search Behavior Prediction: A Hypergraph Perspective
Yan Han, Eddie Huang, Wenqing Zheng, Nikhil Rao, Zhangyang Wang, Karthik Subbian
ACM International Conference on Web Search and Data Mining (WSDM), 2023
Radiomics-Guided Global-Local Transformer for Weakly Supervised Pathology Localization in Chest X-Rays
Yan Han, Gregory Holste, Ying Ding, Ahmed Tewfik, Yifan Peng, Zhangyang Wang
IEEE Transactions on Medical Imaging (TMI), 2022
Knowledge-Augmented Contrastive Learning for Abnormality Classification and Localization in Chest X-rays with Radiomics using a Feedback Loop
Yan Han, Chongyan Chen, Ahmed Tewfik, Benjamin Glicksberg, Ying Ding, Yifan Peng, Zhangyang Wang
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2022
SCALP - Supervised Contrastive Learning for Cardiopulmonary Disease Classification and Localization in Chest X-rays using Patient Metadata
Ajay Jaiswal, Tianhao Li, Cyprian Zander, Yan Han, Justin F. Rousseau, Yifan Peng, Ying Ding
IEEE International Conference on Data Mining (ICDM), 2021
Using Radiomics as Prior Knowledge for Thorax Disease Classification and Localization in Chest X-rays
Yan Han, Chongyan Chen, Liyan Tang, Mingquan Lin, Ajay Jaiswal, Song Wang, Ahmed Tewfik, George Shih, Ying Ding, Yifan Peng
AMIA Annual Symposium Proceedings (AMIA), 2021
Pneumonia Detection on Chest X-ray using Radiomic Features and Contrastive Learning
Yan Han, Chongyan Chen, Ahmed H Tewfik, Ying Ding, Yifan Peng
The IEEE International Symposium on Biomedical Imaging (IEEE ISBI), 2021
Robust End-to-End Speaker Verification Using EEG
Yan Han, Gautam Krishna, Co Tran, Mason Carnahan, Ahmed H Tewfik
European Signal Processing Conference (EUSIPCO), 2020
Generating EEG features from Acoustic features
Gautam Krishna, Co Tran, Yan Han, Mason Carnahan, Ahmed H Tewfik
European Signal Processing Conference (EUSIPCO), 2020
Speech Synthesis using EEG
Gautam Krishna, Co Tran, Yan Han, Mason Carnahan, Ahmed H Tewfik
International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020
Fault Clustering Technique for 3D Memory BISR
Tianjian Li, Yan Han, Xiaoyao Liang, Hsien-Hsin S.Lee, Li Jiang
Proceedings of the Conference on Design, Automation & Test in Europe (DATE), 2017

Teaching Experience

EE312: Software Design and Implementation
Teaching Assistant
UT-Austin, Summer 2020
EE385V: Brain Computer Interaction
Teaching Assistant
UT-Austin, Spring 2020
EE371R: Digital Image/Video Process
Teaching Assistant
UT-Austin, Fall 2019
EE381J: Probability and Random Process
Teaching Assistant
UT-Austin, Spring 2019

Miscellaneous

Hobbies: Guitar, PC Games.

Fun Fact: I co-own a cattery in the Bay Area 🐱. You can visit us at BestBritishCats.com.