Xiuyuan Hu （胡修远）
I am a 4th-year Ph.D. candidate in the Department of Electronic Engineering at Tsinghua University, Beijing, advised by Prof. Hao Zhang. Prior to this, I received my Bachelor’s degree also from Dept. EE, THU in 2022. During my Ph.D. study, I had the privilege of working as an intern at Microsoft Research and AstraZeneca, and visiting University of Cambridge and MBZUAI.
My research is mainly focused on machine learning and AI for science (particularly drug discovery). I am also interested in cutting-edge AI topics including AI for medicine and healthcare, large language models, computer vision, neuroscience, and AI for social science.
I have published papers at top-tier machine learning conferences including NeurIPS, ICML, ICLR, AAAI, and served as a reviewer at these conferences.
I expect to graduate in 2027, and now I am actively seeking postdoc and industrial research opportunities around the world.
Email: huxy22 [at] mails.tsinghua.edu.cn
News
- 11/2025: Our paper CycleChemist for organic photovoltaic discovery is accepted by AAAI 2026 for Oral Presentation.
- 04/2025: My first-authored paper ACARL for utilizing activity cliffs in drug design is accepted by Journal of Cheminformatics.
- 01/2025: My first-authored paper 3DMolFormer for structure-based drug discovery is accepted by ICLR 2025.
- 11/2024: I pass my PhD qualifying exam.
- 07/2024: My first-authored paper Hamiltonian Diversity for measuring molecular diversity is accepted by Journal of Cheminformatics.
- 05/2024: Our paper on gradient regularization in deep learning is accepted by ICML 2024.
- 09/2023: My first-authored paper MolRL-MGPT for de novo drug design is accepted by NeurIPS 2023.
- 09/2022: I start to pursue my Ph.D. degree at Tsinghua University, after obtaining my B.E. and minor B.S. degrees here.
- 05/2022: Our paper on gradient norm penalization in deep learning is accepted by ICML 2022.