About Me
I am currently a postdoctoral researcher at the Dept. of Computer Science and Engineering, The Ohio State University. I'm fortunate to work with Wei-Lun Chao, Yu Su and Tanya Berger-Wolf. I obtained my Ph.D. in 2024 from College of Control Science and Engineering, Zhejiang University, Hangzhou, China. I was supervised by Wei Jiang. Previously, I received my B.Eng. in Zhejiang University in 2019. During Sep. 2022 - Oct. 2023, I was a visiting scholar at HPC AI Lab, National University of Singapore, under the supervision of Yang You.
Research Interest
- Interpretable and Explainable AI for Science
- Data-centric Efficient Training
- Computer Vision
Selected Publications
A full publication list is available in my google scholar page.
(* denotes equal contribution)
BioCAP: Exploiting Synthetic Captions Beyond Labels in Biological Foundation Models
Integrate instance-level synthetic captions in multimodal alignment and demonstrate rich understanding of biological semantics.
Ziheng Zhang, Xinyue Ma, Arpita Chowdhury, Elizabeth G Campolongo, Matthew J Thompson, Net Zhang, Samuel Stevens, Hilmar Lapp, Tanya Berger-Wolf, Yu Su, Wei-Lun Chao, and Jianyang Gu.
BioCLIP 2: Emergent Properties from Scaling Hierarchical Contrastive Learning
Extend species classification training to emergent properties of inter-species ecological alignment and intra-species variation separation.
Jianyang Gu, Samuel Stevens, Elizabeth G Campolongo, Matthew J Thompson, Net Zhang, Jiaman Wu, Andrei Kopanev, Zheda Mai, Alexander E White, James Balhoff, Wasila Dahdul, Daniel Rubenstein, Hilmar Lapp, Tanya Berger-Wolf, Wei-Lun Chao, and Yu Su.
Finer-CAM: Spotting the Difference Reveals Finer Details for Visual Explanation
Compare the target class with similar classes for more fine-grained and discriminative explanation.
Ziheng Zhang*, Jianyang Gu*, Arpita Chowdhury, Zheda Mai, David Carlyn, Tanya Berger-Wolf, Yu Su, and Wei-Lun Chao.
Prompt-CAM: Making Vision Transformers Interpretable for Fine-Grained Analysis.
Arpita Chowdhury, Dipanjyoti Paul, Zheda Mai, Jianyang Gu, Ziheng Zhang, Kazi Sajeed Mehrab, Elizabeth G Campolongo, Daniel Rubenstein, Charles V Stewart, Anuj Karpatne, Tanya Berger-Wolf, Yu Su, and Wei-Lun Chao.
Static Segmentation by Tracking: A Frustratingly Label-Efficient Approach to Fine-Grained Segmentation.
Zhenyang Feng, Zihe Wang, Jianyang Gu, Saul Ibaven Bueno, Tomasz Frelek, Advikaa Ramesh, Jingyan Bai, Lemeng Wang, Zanming Huang, Jinsu Yoo, Tai-Yu Pan, Arpita Chowdhury, Michelle Ramirez, Elizabeth G. Campolongo, Matthew J. Thompson, Christopher G. Lawrence, Sydne Record, Neil Rosser, Anuj Karpatne, Daniel Rubenstein, Hilmar Lapp, Charles V. Stewart, Tanya Berger-Wolf, Yu Su, and Wei-Lun Chao.
Efficient Dataset Distillation via Minimax Diffusion
Efficiently distill ImageNet and generate representative and diverse images, yielding state-of-the-art validation performance.
Jianyang Gu, Saeed Vahidian, Vyacheslav Kungurtsev, Haonan Wang, Wei Jiang, Yang You and Yiran Chen.
Summarizing Stream Data for Memory-Restricted Online Continual Learning
Summarize the information flow in online continual learning into informative samples and significantly improve the replay effects under tight memory.
Jianyang Gu, Kai Wang, Wei Jiang, and Yang You.
DREAM: Efficient Dataset Distillation by Representative Matching
Improve the training efficiency by only calculating matching metrics with representative samples.
Yanqing Liu*, Jianyang Gu*, Kai Wang, Zheng Zhu, Wei Jiang, and Yang You.
Taming Diffusion for Dataset Distillation with High Representativeness.
Lin Zhao, Yushu Wu, Xinru Jiang, Jianyang Gu, Yanzhi Wang, Xiaolin Xu, Pu Zhao, and Xue Lin.
Group Distributionally Robust Dataset Distillation with Risk Minimization.
Saeed Vahidian*, Mingyu Wang*, Jianyang Gu*, Vyacheslav Kungurtsev, Wei Jiang and Yiran Chen.
InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning.
Ziheng Qin*, Kai Wang*, Zangwei Zheng, Jianyang Gu, Xiangyu Peng, Zhaopan Xu, Daquan Zhou, Lei Shang, Baigui Sun, Xuansong Xie, Yang You.
Dataset Quantization.
Daquan Zhou*, Kai Wang*, Jianyang Gu*, Dongze Lian, Xiangyu Peng, Yifan Zhang, Yang You, and Jiashi Feng.
Color Prompting for Data-Free Continual Unsupervised Domain Adaptive Person Re-Identification
Learn the task-conditioned color distribution to reduce forgetting and enhance generalization without storing previous images.
Jianyang Gu, Hao Luo, Kai Wang, Wei Jiang, Yang You, and Jian Zhao.
MSINet: Twins Contrastive Search of Multi-Scale Interaction for Object ReID
Search the optimal interaction between multi-scale branches and yield better supervised and unsupervised performance with limited parameter size.
Jianyang Gu, Kai Wang, Hao Luo, Chen Chen, Wei Jiang, Yuqiang Fang, Shanghang Zhang, Yang You, and Jian Zhao.
Multi-View Evolutionary Training for Unsupervised Domain Adaptive Person Re-Identification
Effectively reduce the clustering noise from the dimensions of snapshot quality and temporal consistency in unsupervised domain adaptation.
Jianyang Gu, Weihua Chen, Hao Luo, Fan Wang, Hao Li, Wei Jiang, and Weijie Mao.
Transformer-Based Domain-Specific Representation for Unsupervised Domain Adaptive Vehicle Re-Identification.
Ran Wei, Jianyang Gu, Shuting He, and Wei Jiang.
An efficient global representation constrained by Angular Triplet loss for vehicle re-identification.
Jianyang Gu, Wei Jiang, Hao Luo, and Hongyan Yu.
1st Place Solution to VisDA-2020: Bias Elimination for Domain Adaptive Pedestrian Re-identification.
Jianyang Gu, Hao Luo, Weihua Chen, Yiqi Jiang, Yuqi Zhang, Shuting He, Fan Wang, Hao Li, and Wei Jiang.
Experience
-
OPPO Research Intern
Nov. 2021 - Jun. 2022. Focused on domain generalizable person re-identification and video action recognition.
-
Alibaba Research Intern
Jun. 2020 - Apr. 2021. Focused on unsupervised domain adaptive person re-identification. Awarded as the annual outstanding research intern in 2020.
-
Yitu Tech. CI Intern
May. 2018 - Sept. 2018. Helped build up the continuous integration pipeline of products.
Competitions & Awards
-
NeurIPS Scholar Award
2025.
-
OSU CSE Research Staff Award
2025.
-
AAAI Scholarship
2024.
-
ActivityNet Temporal Action Localization Challenge
Third Place. CVPR Workshop 2022.
-
SoccerNet Challenge
Third Place. CVPR Workshop 2022.
-
AICity Challenge
First Place. CVPR Workshop 2021.
-
National AI Challenge
Second Prize. 2020.
-
Visual Domain Adaptation Challenge
First Place. ECCV Workshop 2020.
-
Robocup Montreal
First Place. 2018.
Academic Service
-
Workshop Organization
Lead organizer. Third Workshop on Imageomics @ NeurIPS2025
Co-organizer. Second Workshop on Imageomics @ AAAI2025
Co-organizer. Anomaly Detection in Scientific Domains Workshop @ AAAI2025
PC Member. First Workshop on Dataset Distillation @ CVPR2024
-
Conference Area Chair
ICLR 2026, ICML 2026
-
Conference Reviewer
CVPR, ICCV, ECCV, ICLR, ICML, NeurIPS, ACMMM, WACV, ACCV
-
Journal Reviewer
PNAS, IEEE TPAMI, PR, CVIU, IEEE TCSVT
Other Information
-
President, Student AI Association of Zhejiang University, Aug. 2020 - Jun. 2021
-
Part of my photography works.
Contact Me
You are welcome to contact me via Email.