Ethos
- I value performance and scientific insights over decorative theories or model hypes.
- I believe one remarkable is way valuable than thousands of mediocres.
- 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 & Area Chair
- Workshop proposals: 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
Co-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 and Interns at Jure's Group at Stanford AI Lab and Regev'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),
Zihan Xu (Rockefeller Biology PhD),
Serena Zhang (Stanford CS BS-MS),
Harrison Zhang (Stanford MD-PhD),
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
Junior Editor
- forthcoming!
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Invited Talk
- [25.05] Stanford; UPenn; Danaher Coporation; 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
- 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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I’ve lived and worked in Xuzhou, Suzhou, Nanjing, Palo Alto, Berkeley, Tokyo (Chiba), Shanghai (ChangNing), Cambridge, London (Westminster), Cherry Hinton, 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 founded in 514 BC, where leading pharmas, including AstraZeneca, Eli Lilly, GSK, Pfizer, and Roche/Genentech, built their main R&D and manufacturing hubs in Asia.
Acknowledgement
The website design is inspired by Jon Barron and Dani Yogatama. Thank you!
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