About Me
I am Jing Zhu, a final year PhD student at the University of Michigan, with Danai Koutra.
Before that, I obtained my B.S.E. from both the University of Michigan and Shanghai Jiao Tong University, and I worked with Andrew Owens.
My research focuses on end-to-end LLM post-training, spanning SFT, synthetic data generation, RL, and multimodal learning (both inputs and outputs).I am on the industry job market!
Research Interns
[Google DeepMind]:   2025/05 - Present
[AWS AI]:                         2022/05 - 2022/11
News
- [2025/08] DISCO Balances the Scales: Adaptive Domain- and Difficulty-Aware Reinforcement Learning on Imbalanced Data is accepted at EMNLP'25!
- [2025/08] LinkGPT: Leveraging Large Language Models for Enhanced Link Prediction in Text-Attributed Graphs is accepted at CIKM'25!
- [2025/02] Mosaic of Modalities: A Comprehensive Benchmark for Multimodal Graph Learning is accepted at CVPR'25!
- [2024/09] On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks is accepted at NeurIPS'24!
- [2024/09] Multi-Stage Balanced Distillation: Addressing Long-Tail Challenges in Sequence-Level Knowledge Distillation is accepted at EMNLP'24!
- [2024/04] TouchUp-G: Improving Feature Representation through Graph-Centric Finetuning is accepted at SIGIR'24!
- [2023/10] Pitfalls in Link Prediction with Graph Neural Networks: Understanding the Impact of Target-link Inclusion & Better Practices is accepted at WSDM'24!
- [2022/09] Touch and Go: Learning from Human-Collected Vision and Touch is accepted at NeurIPS'22!
- [2022/08] CAPER: Coarsen, Align, Project, Refine - A General Multilevel Framework for Network Alignment is accepted at CIKM'22!
- [2021/08] NegatER: Unsupervised Discovery of Negatives in Commonsense Knowledge Bases is accepted at EMNLP'21!
- [2020/12] Node Proximity Is All You Need: A Unified Framework for Proximity-Preserving and Structural Node and Graph Embedding is accepted at SDM'21!
Book Chapter
Fact Summarization for Personalized Knowledge Graphs
Danai Koutra, Davide Mottin, Jing Zhu
Personal Knowledge Graphs (PKGS): Methodology, Tools and Applications
Publications
- Best paper award at MLoG [Slides]
- DEI Award, CVPR 2024
- Best paper Award, MLoG 2024
- Two Sigma Fellowship Finalist
- CIKM Travel Award, SIGIR. Oct. 2022
- KDD Travel Award, SIGKDD. Aug. 2022
- CSE fellowship, University of Michigan. 2021-2022
- Rackham Travel Grant, University of Michigan. Nov. 2021.
- SDM Travel Award, SIAM. Apr. 2021.
- James B. Angell Scholar, University of Michigan. Mar. 2021.
- Jackson and Muriel Lum Scholarship, University of Michigan. 2019-2021
- Excellent Undergraduate Scholarship, Shanghai Jiao Tong University. Nov. 2018, Nov. 2019.
- EECS476 Data Mining, University of Michigan. 2021 Winter.
- EECS496 Major Design Experience-Professionalism, University of Michigan. 2020 Fall.
- VV285 Honors Mathematics III, Shanghai Jiao Tong University. 2019 Summer.
- VV186 Honors Mathematics II, Shanghai Jiao Tong University. 2018 Fall.
- Review: NeurIPS, ICLR, CVPR, ICML, NLP series ARR, KDD, ECML-PKDD, LoG, AAAI, SDM
[12] DISCO Balances the Scales: Adaptive Domain- and Difficulty-Aware Reinforcement Learning on Imbalanced Data. [link] [code]
Yuhang Zhou*, Jing Zhu*, Shengyi Qian, Zhuokai Zhao,
Xiyao Wang, Xiaoyu Liu, Ming Li, Paiheng Xu,
Wei Ai, Furong Huang
EMNLP 2025 Findings
[11] Mosaic of Modalities: A Comprehensive Benchmark for Multimodal Graph Learning. [link] [code]
CVPR 2025
[10] Beyond Unimodal Boundaries: Generative Recommendation with Multimodal Semantics. [link] [code]
[9] LinkGPT: Teaching Large Language Models To Predict Missing Links. [link] [code]
Zhongmou He, Jing Zhu, Shengyi Qian, Joyce Y. Chai,
Danai Koutra                                                    
CIKM 2025
[8] On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks. [link] [code]
Jiong Zhu*, Gaotang Li, Yao-An Yang, Jing Zhu,
Xuehao Cui, Danai Koutra                                                      
NeurIPS 2024
[7] Multi-Stage Balanced Distillation: Addressing Long-Tail Challenges in Sequence-Level Knowledge Distillation. [link] [code]
EMNLP 2024 Findings
[6] TouchUp-G: Improving Feature Representation through Graph-Centric Finetuning. [link] [code]
SIGIR 2024
[5] Pitfalls in Link Prediction with Graph Neural Networks: Understanding the Impact of Target-link Inclusion & Better Practices.[link] [code]
WSDM 2024
[4] Touch and Go: Learning from Human-Collected Vision and Touch. [link] [code]
NeurIPS 22 Dataset and Benchmark
[3] CAPER: Coarsen, Align, Project, Refine - A General Multilevel Framework for Network Alignment. [link] [code]
Jing Zhu, Danai Koutra, Mark Heimann
CIKM 2022
[2] NegatER: Unsupervised Discovery of Negatives in Commonsense Knowledge Bases. [link] [code]
Tara Safavi, Jing Zhu, Danai Koutra
EMNLP 2021
[1] Node Proximity Is All You Need: A Unified Framework for Proximity-Preserving and Structural Node and Graph Embedding. [link] [code]
Jing Zhu*, Xingyu Lu*, Mark Heimann, Danai Koutra
SDM 2021