About Me
Hi, I’m Zhichun Guo! I am currently a postdoctoral researcher at Baker Lab at the University of Washington. In Fall 2025, I will be joining the Department of Computer Science at Emory University as a tenure-track assistant professor. I received my Ph.D. from the Department of Computer Science and Engineering at the University of Notre Dame in May 2024, where I was advised by Prof. Nitesh Chawla (ACM/IEEE/AAAI Fellow). Before that, I earned my bachelor’s degree in Computer Science from Fudan University.
My research interests span artificial intelligence, machine learning, and data science. During my Ph.D., I focused on enhancing graph neural networks for real-world applications, particularly in chemistry and link prediction tasks. Recently, I’ve begun exploring large language models (LLMs) and machine learning models for broader scientific applications, such as bioinformatics.
[Prospective PhD Students and Interns] I am actively seeking highly-motivated Ph.D. students and interns to work on machine learning and AI4Science problems. If you are interested in working with me, please send me an email at zcguo[at]uw[dot]edu with your CV, transcripts, and a brief introduction of your research interests and experience.
News
- 09/2024: One paper accepted by NeurIPS 2024 Datasets and Benchmarks Track on LLMs for chemistry.
- 09/2024: Two papers accepted by NeurIPS 2024 on link prediction and recsys.
- 07/2024: Excited to start my PostDoc at Baker Lab@UW.
- 05/2024: Thrilled to receive my Ph.D. degree from CS@Notre Dame. Deeply appreciate the acknowledgement!
- 03/2024: Thrilled to pass my Ph.D. Defense.
- 03/2024: Delighted to give an invited talk at CS@Emory University.
- 03/2024: Delighted to give an invited talk at CS@Michigan State University.
- 02/2024: Delighted to give an invited talk at CS@UT Dallas.
- 02/2024: Delighted to give an invited talk at CS@Virginia Tech.
- 02/2024: Delighted to give an invited talk at CS@Florida State University.
- 02/2024: Delighted to give an invited talk at CS@University of Houston.
- 09/2023: One paper accepted by NeurIPS 2023 Datasets and Benchmarks Track.
More
- 06/2023: Thrilled to be back at Snap Inc. for a summer internship.
- 04/2023: One paper accepted by ICML 2023, on knowledge distillation for link prediction. See you in Hawaii!
- 04/2023: One paper accepted by IJCAI 2023 Survey Track, on graph-based molecular representation learning. See you in Macao!
- 03/2023: One paper accepted by Chemical Science.
- 01/2023: Two papers accepted by ICLR'23.
- 12/2022: Thrilled to receive [Snap Research Fellowship]. Thanks, Snap!
- 11/2022: Two papers accepted by LoG'22.
- 11/2022: One paper accepted by AAAI'23. See you in Washington DC!
- 08/2022: Thrilled to receive IEEE VIS Inclusivity & Diversity Scholarship! Thanks VIS!
- 06/2022: Thrilled to start my summer internship at Snap Inc..