Chunhui Zhang

Greetings! I am Chunhui Zhang (pronounced as Ch'un-hui Chang/张春晖), a Ph.D. student in Computer Science at Dartmouth🌲, fortunately working with 🌟Professor Soroush Vosoughi.

I earned my MSCS degree and was honored with the GSAS Fellowship at Brandeis University. My research journey began at Northeastern University, where I obtained a Bachelor's degree in CS and received the Outstanding Honor Thesis Award.

/ / / / CV / Google Scholar

Research

My past research investigates intrinsic properties of deep learning behind the phenomena across diverse modalities, then driving trustworthy real-world applications:

Posts

[Aug 31, 2023] Happily start my Ph.D. journey at Dartmouth College!
I have bravely persevered through a difficult period in my life, and am brave enough to break the collaboration with the former advisor. I am grateful to the Brandeis CS department for their kind support and humanitarian assistance to me during this time. I am looking forward to a new chapter of my life!

Papers

	Efficient and Effective Training: Visual Conditioned Language Generation by LLM In submission achieved 6× training speed improvement for SOTA multi-modal generative model with 7 Billion parameters, cutting training time from 100 to 16 GPU hours through efficient visual redundancy reduction.
	Aligning Relational Learning with Lipschitz Fairness {Yaning Jia, Chunhui Zhang}, Soroush Vosoughi International Conference on Learning Representations (ICLR), 2024. Jia is a master student who was mentored by me. Thanks Jia for this pleasant mentoring experience. I highly recommend my friend to any professor seeking an outstanding candidate! project page / preprint
	Mitigating Emergent Robustness Degradation on Graphs while Scaling Up {Xiangchi Yuan, Chunhui Zhang}, Yijun Tian, Yanfang Ye, et al. International Conference on Learning Representations (ICLR), 2024. Yuan is a master student who was mentored by me. Thanks Yuan for this pleasant mentoring experience. I highly recommend my friend to any professor seeking the best candidates! project page / preprint
	GCVR: Reconstruction from Cross-View Enable Sufficient and Robust Graph Contrastive Learning Qianlong Wen, Zhongyu Ouyang, Chunhui Zhang, Yiyue Qian, Chuxu Zhang, Yanfang Ye The 40th Conference on Uncertainty in Artificial Intelligence (UAI), 2024. project page / preprint
	How to Improve Representation Alignment and Uniformity in Graph-based Collaborative Filtering? Zhongyu Ouyang, Chunhui Zhang, Shifu Hou, Chuxu Zhang, Yanfang Ye International AAAI Conference on Web and Social Media (ICWSM), 2024. project page / preprint
	Breaking the Trilemma of Privacy, Utility, and Efficiency via Controllable Machine Unlearning {Zheyuan Liu, Guangyao Dou}, Yijun Tian, Chunhui Zhang, Eli Chien, Ziwei Zhu ACM International World Wide Web Conference (The Web Conference/WWW), 2024. project page / preprint
	When Sparsity Meets Contrastive Models: Less Data Can Bring Better Class-Balanced Representations Chunhui Zhang, Chao Huang, Yijun Tian, Qianlong Wen, Zhongyu Ouyang, Youhuan Li, Yanfang Ye, et al. Fortieth International Conference on Machine Learning (ICML), 2023. project page / preprint
	Chasing All-Round Graph Representation Robustness: Model, Training, and Optimization Chunhui Zhang, Yijun Tian, Mingxuan Ju, Zheyuan Liu, Yanfang Ye, Nitesh Chawla, et al. The 11th International Conference on Learning Representations (ICLR), 2023. project page / preprint
	Mind the Gap: Mitigating the Distribution Gap in Graph Few-shot Learning Chunhui Zhang, Hongfu Liu, Jundong Li, Yanfang Ye, et al. Transactions on Machine Learning Research (TMLR), 2023. project page / preprint
	Fair Graph Representation Learning via Diverse Mixture-of-Experts Zheyuan Liu, Chunhui Zhang* (Co-first author in alphabetical order), Yijun Tian, Erchi Zhang, Chao Huang, Yanfang Ye, et al. International World Wide Web Conference (WWW), 2023. project page / preprint Co-first author Liu is an undergraduate mentored by me. A pleasant first experience. Thanks Liu.*
	Boosting Graph Neural Networks via Adaptive Knowledge Distillation Zhichun Guo, Chunhui Zhang, Yujie Fan, Yijun Tian, et al. Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), 2023. project page / preprint
	Heterogeneous Graph Masked Autoencoders Yijun Tian, Kaiwen Dong, Chunhui Zhang, et al. Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), 2023. project page / preprint
	Heterogeneous Temporal Graph Neural Network Explainer Jiazheng Li, Chunhui Zhang, et al. ACM International Conference on Information and Knowledge Management (CIKM), 2023. project page / preprint
	Label-invariant Augmentation for Semi-Supervised Graph Classification Han Yue, Chunhui Zhang, Chuxu Zhang, and Hongfu Liu Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2022. project page / preprint
	Co-Modality Imbalanced Graph Contrastive Learning Yiyue Qian, Chunhui Zhang, Yiming Zhang, Qianlong Wen, Yanfang Ye, et al. Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2022. project page / preprint
	Diving into Unified Data-Model Sparsity for Class-Imbalanced Graph Representation Learning Chunhui Zhang, Chao Huang, Yijun Tian, Qianlong Wen, Zhongyu Ouyang, Youhuan Li, Yanfang Ye, et al. Thirty-sixth Conference on Neural Information Processing Systems-New Frontiers in Graph Learning Workshop (NeurIPS GLFrontiers Workshop) 2022 & 37th AAAI Conference on Artificial Intelligence-Workshop on DL-Hardware Co-Design for AI Acceleration (AAAI DCAA workshop), Best Paper Runner-up Award 2023. project page / preprint
	GraphBERT: Bridging Graph and Text for Malicious Behavior Detection on Social Media Jiele Wu, Chunhui Zhang, Zheyuan Liu, Erchi Zhang, Steven Wilson, et al. IEEE International Conference on Data Mining (ICDM), 2022. project page / preprint
	Look Twice as Much as You Say: Scene Graph Contrastive Learning for Self-Supervised Image Caption Generation Chunhui Zhang, Chao Huang, Youhuan Li, Xiangliang Zhang, Yanfang Ye, et al. ACM International Conference on Information and Knowledge Management (CIKM), 2022. project page / slides / poster / preprint Note: The case study of this paper is funny! It first finds that language representation can emerge from a purely image-pretrained model.
	AdaSearch: Many-to-One Unified Neural Architecture Search via A Smooth Curriculum Chunhui Zhang, Yongyuan Liang, and Yifan Jiang* AAAI-22 Workshop: Learning Network Architecture During Training. project page / slides / preprint
	Towards Tailored Models on Private AIoT Devices: Federated Direct Neural Architecture Search Chunhui Zhang, Xiaoming Yuan, Qianyun Zhang, Guangxu Zhu, Lei Cheng, and Ning Zhang IEEE Internet of Things Journal (IoTJ), Feb. 2022. project page / preprint A fun fact: Corresponding author Dr. Lei Cheng is the best professor I have ever met. As a fresh researcher, grateful for his very nice trust and professional advice.

To all students/friends

Feel free to drop me an email if you're up for a laid-back chat about life, career, or research. I'm dedicating (at-least) 30 minutes each week for these discussions, and I'm particularly eager to connect with students from underrepresented backgrounds or those dealing with challenges or inequity. Just reach out – I'm here to listen!

Fun Stuff

Racing - a happy part of my life. I particularly enjoy go-karting and circuit racing (some fun facts: 1st and 2nd place at Supercharged). But there is one type of racing that I have yet to try - my favorite rally driving (My favorite rally driver is Han Han).

Design and source code from this cool guy.