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Xingjian "Jimmy" Zhang 张行健

School of Information, University of Michigan

ABOUT ME

I am a third-year Ph.D. candidate at the University of Michigan, advised by Prof. Qiaozhu Mei. My research interests lie in AI for Science. Specifically, I am interested in the following:

  • Quantitative evaluation of AI systems' innovative ability.
  • AI tools that assist human researchers to automate scientific research workflows.
  • Reasoning capabilities of AI in non-standard tasks (e.g., beyond math and coding).

Prior to my Ph.D., I received my bachelor's degree in Computer Science from the University of Michigan.


SELECTED PAPERS

Map2Text: New Content Generation from Low-Dimensional Visualizations
Xingjian Zhang, Ziyang Xiong, Shixuan Liu, Yutong Xie, Tolga Ergen, Dongsub Shim, Hua Xu, Honglak Lee, Qiaozhu Mei
arXiv preprint, 2024
paper code
MASSW: A New Dataset and Benchmark Tasks for AI-Assisted Scientific Workflows
Xingjian Zhang*, Yutong Xie*, Jin Huang, Jinge Ma, Zhaoying Pan, Qijia Liu, Ziyang Xiong, Tolga Ergen, Dongsub Shim, Honglak Lee, et al.
NAACL Findings, 2025
paper code
Can LLMs effectively leverage graph structural information: when and why
Jin Huang, Xingjian Zhang, Qiaozhu Mei, Jiaqi Ma
TMLR, 2024
paper code

For more details about my research, please visit my research page.

HONORS & AWARDS

  • Precandidate Rackham Graduate Student Research Grant (2024)
  • PhD Fellowship (2022)
  • Tang Junyuan Scholarship (2020-2021)
  • John Wun & Jan Sun Sunshine Scholarship (2019)

SERVICE

Workshop Organizer

  • LLMIGS (2024)
  • LoG Local Meetup (2023)
  • GLB (2023)

Program Committee

  • KDD (2025)
  • WWW (2023-2025)
  • IEEE BigData (2023-2024)

NEWS

  • 💼 Excited to return to Google DeepMind as a Research Intern this summer! (Mar 2025)
  • 📝 Paper accepted by NAACL 2025! (Jan 2025)
  • 📝 Paper accepted by NeurIPS 2024 D&B Track as a spotlight! (Oct 2024)
  • 📝 Paper accepted by TMLR! (Jun 2024)
  • 🎯 We are organizing the 1st Workshop on Large Language Models for Individuals, Groups, and Society (LLMIGS 2024) in conjunction with WSDM 2024! (Dec 2023)
  • 💼 Interning @ Google DeepMind! (May 2023)
  • 🎯 We are organizing the 3rd Workshop on Graph Learning Benchmarks (GLB 2023) in conjunction with KDD 2023! (Apr 2023)
  • 📝 Paper accepted by LOG 2022 for oral presentation! (Nov 2022)