wang.hanchen at gene.com | hanchenw at cs.stanford.edu |
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My first-author papers (Nature, NeurIPS etc.) are reported by 1000+ tweets, 50+ press including: A special collection of Nature, DeepMind, The Economist, Harvard Medical School, Chemical & Engineering News, Tech Crunch, Yahoo! News, a few Wikipedia pages, Tech Xplore, University of Cambridge, healthcare-in-europe. Besides AI/ML, I'm trained and have published in Physics (my foundation and childhood's favorite, High School Olympiad), Biology (wild learner, also High School Olympiad), Chemistry, Materials / Electronics, Medical Sciences, and Clinical Trials :) |
Postdoc, Aug 2023-26Exploring single-cell genomics and AI to revolutionize therapeutics while building Graph ML methods for data-driven science! |
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Namkyeong Lee, et al., Chanyoung Park# in review |
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Chenyu Wang*, Masatoshi Uehara*, et al., Tommi Jaakkola#, Sergey Levine#, Hanchen Wang#, Aviv Regev# in review |
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Tianyu Liu*, Edward De Brouwer*, et al., Aviv Regev#, Graham Heimberg# RECOMB 2025 |
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Karin Hrovatin*, Lisa Sikkema*, et al., Fabian Theis#, Malte Luecken# Nature Methods 2024, part of Human Cell Atlas collection |
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Hanchen Wang, Jure Leskovec#, Aviv Regev# Nature Biotechnology (in press), <1 month from submission to revision |
PhD, in Machine Learning, Oct 2019-22Doctoral Thesis:During my three-year PhD (with full fellowship), I shifted to AI, published my 1st paper till the end of my 2nd year (ICCV '21). I have been working on data including votes from polls, point clouds, CT/CXR scans, histological and pathological images, molecular and relational graphs, as well as scRNA-seq. I develop methods (many are pre-training) that can learn structures from these data with weak supervisions. Aside from this, I spent some time on quantum computation also did four interns in tech and biotech industries (Google -> Amazon -> BioMap -> Iambic). Back in 2019, I co-founded a startup (as the CTO) with friends from Stanford and Cal, aimed at transforming electronic health records via language models, with partnerships among 37 hospitals. Though things didn't work out then, my commitment to harnessing AI's power in healthcare remains steadfast. |
| Last batch of works are near completion: two cell atlases, a llm for math, a textbook on MLSys, a cell embedding model, a clinical trial on T-cell therapy. Stay tuned!!! |
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Shengchao Liu et al., TMLR 2024 |
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Hanchen Wang et al., Connor Coley, Yoshua Bengio, Marinka Zitnik# [Team] > Nature 2023, accept without revisions |
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Hanchen Wang*, Jean Kaddour*, Shengchao Liu, Jian Tang, Joan Lasenby, Qi Liu NeurIPS 2023, Datasets and Benchmarks Track |
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Jiefeng Gan*, Hanchen Wang*, Hui Yu* et al., Tian Xia# iScience 2023 |
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Dingmin Wang et al., ECAI 2023 |
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Tsinghua University 2023, Table of Contents English version is in press, Springer Nature |
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Hanchen Wang*, M. N.* (in contribution order) ICASSP 2022, invited by editors, with travel award |
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Shengchao Liu, Hanchen Wang, Weiyang Liu, Joan Lasenby, Hongyu Guo, Jian Tang ICLR 2022 |
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Xiang Bai (Prof.)* Hanchen Wang*, Liya Ma*, Yongchao Xu*, Jiefeng Gan* et al., Carola Schönlieb#, Tian Xia# Nature Machine Intelligence 2021 |
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Hanchen Wang, Qi Liu, Xiangyu Yue, Joan Lasenby, Matthew J. Kusner ICCV 2021 |
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Weiyang Liu*, Zhen Liu*, Hanchen Wang*, Liam Paul, Bernhard Schölkopf, Adrian Weller NeurIPS 2021, Spotlight |
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Hanchen Wang, Yunlong Jiao, Jordan Massiah contributed talk at Amazon Machine Learning Conference 2021 |
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Yun-Hao Cao et al., Pattern Recognition 2021 |
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Hanchen Wang, Nina Grgić-Hlača, Preethi Lahoti, Krishna. P. Gummadi, Adrian. V. Weller axXiv, presented at NeurIPS HCML 2019, with travel award |
Undergraduate, in Physics, Sep 2014-18In addition to studying Physics, I researched next-gen electronic devices such as transistors and solar cells, an intersection of Solid-State Physics, Material Sciences and Electrical Engineering. I primarily worked in Xinran Wang's and Ali Javey's groups. I also accumulated experience in the finance sector, initially focusing on bonds then transitioning to roles in quantitative trading of equity and crypto. These diverse experiences ultimately cemented my commitment in advancing Science and Engineering with the aim of improving human life. Finance is boring, technology is fun and the future :) |
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Nature Nanotechnology 2019 |
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Advanced Energy Materials 2019 |
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ACS Energy Letters 2018 |
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Zhihao Yu (Ph.D)*, Hanchen Wang (B.S)* et al., Xinran Wang# IEDM 2017, Oral, NJU's 1st IEDM. It is where Intel, NVIDIA, TSMC, AMD etc sharing their secret sauce on chip design :) |
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Journal of Physical Chemistry B 2017 |
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Scientific Reports 2017 |
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Weisheng Li*, Jian Zhou*, Hanchen Wang* et al., Xinran Wang# Invited Review, Acta Physica Sinica 2017 |