Yan Han 韩焱 Ph.D. student Department of Electrical and Computer Engineering University of Texas at Austin Email: yh9442 at utexas dot edu

"There is nothing as practical as a good theory." - Kurt Lewin
"The test of all knowledge is experiment." - Richard Feynman

Biography

I got Ph.D. degree from Decision, Information, and Communications Engineering(DICE) of Department of Electrical and Computer Engineering, The University of Texas at Austin in 2023, under supervision of Prof. Ahmed Tewfik, Prof. Ying Ding and Prof. Atlas Wang. I got B.Eng. degree from School of Electrical Information and Electrical Engineering, Shanghai Jiao Tong University in 2017.

I have broad research interests in Deep Learning , Knowledge Graph, and AI in health, whether it be in their development, inference, or more generally their foundations for computational and statistical analysis.

Experience

• Applied Science Research Intern, Amazon A9, Feb. 2022 - Dec. 2022

Manager/Mentor(s): Dr. Karthik Subbian, Dr. Atlas Wang, Dr. Eddie Huang

• Machine Learning Research Intern, LinkedIn, Jun. 2021 - Dec. 2021

Manager/Mentor(s): Dr. Qi He, Dr. Jaewon Yang, Dr. Baoxu Shi, Dr. Ji Yan

• Research Intern, AbbVie, Feb. 2021 - May. 2021

Manager/Mentor(s): Dr. Abhik Seal

Publication

• 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), 2024.
  

• 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 Experiences

Teaching Assistant, EE312 (Software Design and Implement), UT-Austin, Summer 2020.

Teaching Assistant, EE385V (Brain Computer Interaction), UT-Austin, Spring 2020.

Teaching Assistant, EE371R (Digital Image/Video Process), UT-Austin, Fall 2019.

Teaching Assistant, EE381J (Probability and Random Process), UT-Austin, Spring 2019.

Miscellany

Hobbies: Guitar, PC Games.

Last Updated by Yan: Aug. 13 2023