Ethos
- I enjoy reading history (civilization, nation, corporation, person), at a rate of 5-20 books per year since age 16.
- I value method's practical performance and insights over decorative theories or hypes.
- I believe one remarkable is way valuable than thousands of mediocre.
- I spent 3 years for PhD, and 2 years for High School.
- I favor risky and rewarding stuff (YOLO, e/acc).
- I hire slow and fire fast.
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Academic Service
Teaching Assistant - Michaelmas/Lent are Fall/Spring semesters at Cambridge
- Statistical Inference, Lent '20 & '21
- Lab: Spectrum Analysis, Michaelmas '20
- Statistical Signal Processing, Michaelmas '19 & '20
Reviewer
- Proposals: workshops at NeurIPS '21, '23, '24, '25
- Conferences: ICLR, ICML, NeurIPS, ISMB, CVPR, AISTATS, KDD, AAAI etc
- Journals: Nature Methods, Nature Machine Intelligence, Nature Electronic, Nature Communications, IEEE TPAMI etc
- Textbooks: Immunology / Reproductive Medicine for Springer Nature
Area Chair
- ICLR '26
Organizer
- Symposium on AI Agents and Scientific Discovery, AAAI '25
- Workshop on ML for Material Discovery, ICLR '23
- Workshop on AI for Science, NeurIPS '21 & '22; ICML '22
Member
- Human Cell Atlas, Data Integration Team
- Chan Zuckerberg Initiative, Virtual Cell Team, AI Resident, Faculty Applicant Bootcamp
- UCSF Gladstone Institute, Trainee-to-Tenure Track Program
- Pipeline Club, Genentech
Mentor
- I host RAs, interns and technicians at Jure's Group at Stanford AI Lab and Aviv's Lab at Genentech. I'm fortunate to work with:
Sessen Iohannes (CSHL Biology PhD),
Chang Ma (HKU CS PhD),
Namkyeong Lee (KAIST CS PhD),
Ziyu Lu (Rockefeller Biology PhD),
Jordan Rossen (Harvard Epidemiology PhD),
Shuvom Sadhuka (MIT CSAIL PhD),
Serena Zhang (Stanford CS BS-MS),
Yichun He (Harvard Bioengineering PhD),
Chenyu Wang (MIT CSAIL PhD),
Nikil Ravi (Stanford CS MS).
- I advise early-stage reviewers (BS to PostDoc) via official programs at venues including ML4H & Nature Communications.
Guest Lecturer
- Stanford Bio 114, Winter '24
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Invited Talk
- [25.11] Broad Institute
- [25.10] Cold Spring Harbor Laboratory
- [25.08] Agentic AI Summit, UC Berkeley
- [25.05] Stanford; Penn; Danaher; UCLA; Roche; Nature Publishing Group; 10x Genomics; Tsinghua; Yale; NIH / NCI, Harvard
- [25.04] AAAI Spring Symposium
- [24.11] Princeton, Yale
- [23.11] Human Cell Atlas
- [23.06] Tsinghua, Peking, Westlake; Cambridge ML Group; Microsoft AI4Science; Sanger Institute; EMBL-EBI
- [23.04] Swarma Pattern
- [22.09] Genentech
- [22.06] Lennard-Jones Centre, Cambridge
- [22.02] ML/NLP Seminar, Oxford
- [21.10] Amazon Machine Learning Conference
- [21.07] Amazon-UCL Seminar
- [19.10] HackBridge Demo Day
- [19] call/pitch/pre on ''Cantab Care'', a startup I co-founded
- [18.07] Awardee Representative Speech, Cathy Xu Fellowship Awarding Event
- [18.06] Commencement Speech (Valedictorian), KYM Honors School, Nanjing University
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Funding and Grants
- PI: Genentech Internal Funding for AI Agents: $250k/year for computation, $250k/year for hiring.
- PI: OpenAI Researcher Access Program: $10k
- Postdoc: Supported by a 4-year fellowship
- PhD: Funded by two fellowships, a few scholarships, cash awards, student grant, and travel awards
- Undergraduate: Received multiple awards and was the commencement speaker of the talented program
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Equity Commitment
- Volunteer: Data Science & Machine Learning Professional Certificate Program, San Francisco State University, '24-'25
- Mentor: Undergraduate Mentoring Pilot Program, on Becoming a Latino Scientist, UC Davis, '25
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Digital Nomad
I’ve lived and worked in Xuzhou, Suzhou, Nanjing, Berkeley, Tokyo, Shanghai (ChangNing), Cambridge, London (Westminster),
Beijing (HaiDian), Los Angeles (Arcadia), San Diego (La Jolla), Beijing (HaiDian), Manhattan, and Bay Area (Menlo Park 🌲).
I was born in Xuzhou, where the Han dynastry thrived, a city founded in 221 BC.
I spent most of my teenage in Suzhou, a city thriving since 514 BC, now ranked 14th globally by GDP, and the major Asian R&D and manufacturing sites for leading pharmas including AstraZeneca, Eli Lilly, GSK, Pfizer, and Roche.
Acknowledgement
The website design is inspired by Jon Barron and Dani Yogatama. Thank you!
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