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 R&D, 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 December 2026, 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.