Hanchen Wang     24-year-old digital nomad

Hey! I am a third-year PhD in Machine Learning at Cambridge, working with Prof. Joan Lasenby from Trinity. During PhD, I also spend some time at Isaac Newton Institute & Faculty of Math, Google Research, Amazon Alexa, BioMap, Entos, and Caltech.

I earned a Physics BS from Nanjing University (2018), visited Stanford & Cal, worked in Finance (S&T, Quant), co-founded a Startup on Digitial Health.

CV |  Twitter |  Google Scholar

profile photo
Research Interest

I work on 3D and Graph structures, emphasizing Representation Learning & Health topics.
I also spent time on Federated Learning, Quantum Computing and Signal Processing.
I will be on the job market, academia/startup/industry, in early or mid '23.
I am now most interested in Genomes and Oncology.

News, not Papers [sweetness in my life] >>>

[Nov' 21] apply grants from CZ Initiative on 3D Genome as co-PI, with Sanger and EMBL-EBI
[Sep'  21] nominated from Cambridge for PhD Fellowship from Apple and JPMC
[Aug' 21] will co-organise a workshop on AI4Science at NeurIPS '21
[Jun'  21] join Stanford Bio-X

Selected Publications [Full List] >

* denotes the joint first authorship

Facilitating Fundamental Science with AI
AI4Sci Open Community (Yoshua Bengio et al)
working review & perspective paper, intend for Nature
Deep Learning for Tumor Mutation Burden Prediction via Sub-type Lesion Identification
Jiefeng Gan*, Yaobing Chen*, Hanchen Wang*, et al
working research paper, intend for Annals of Oncology
Open Problems in Federated Digital Health
Hanchen Wang, Chaoyang He, James Zou
revising comment paper for Nature Machine Intelligence
Pre-training Molecular Graph Representation with 3D Geometry
Shengchao Liu, Hanchen Wang, Weiyang Liu, Joan Lasenby, Hongyu Guo, Jian Tang
in review for ICLR, also presented at 2nd SSL NeurIPS 2021
code  |  bibtex
Matching Point Sets with Quantum Circuits Learning
Hanchen Wang*, M. N.* (in contribution order)
ICASSP 2022, Invited by Editors
project page  |  code  |  bibtex
Iterative Teaching by Label Synthesis
Weiyang Liu*, Zhen Liu*, Hanchen Wang*, Liam Paul, Bernhard Schölkopf, Adrian Weller
NeurIPS 2021, Spotlight
openreview  |  bibtex
Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence
Xiang Bai* Hanchen Wang*, Liya Ma*, Yongchao Xu*, Jiefeng Gan*, ..., Carola Schönlieb, Tian Xia
Nature Machine Intelligence 2021
project page  |  code  |  bibtex-paper  |  bibtex-code
Media coverage: HUST, Cambridge, Horizon Magazine, Tech Xplore, MIT Technology Review, Synced, [upcoming...]
Unsupervised Point Cloud Pre-training via Occlusion Completion
Hanchen Wang, Qi Liu, Xiangyu Yue, Joan Lasenby, Matthew J. Kusner
ICCV 2021, also presented at WeaSul ICLR 2021
project page  |  code  |  bibtex
Negative Capacitance 2D MoS2 Transistors with Sub-60mV/dec Subthreshold Swing over 6 Orders,
250 μA/μm Current Density, and Nearly-Hysteresis-Free

Zhihao Yu*, Hanchen Wang*, ..., Xinran Wang
IEDM 2017, Oral
Open Source Contribution [GitHub] >
deeplearning.ai: give internal feedback on the newly publicized courses on Natural Language Processing and TensorFlow2.

PyTorch3D: A library for 3D deep learning developed by talents from Facebook AI Research.

metric-learn: Supervised and weakly-supervised Mahalanobis metric learning algorithms.

Teaching Assistant, Demonstrator and Grader
- Mathematics of Machine Learning (Math Department), Lent 2022
- Inference (Engineering Department), Lent 2020 and 2021
- Lab Part IB I1: Spectrum Analysis (Engineering Department), Michaelmas 2020
- Statistical Signal Processing (Engineering Department), Michaelmas 2019 and 2020

Reviewer: Papers | Event Proposals
- ICLR, ECCV, NeurIPS, CVPR, Nature Electronic, ... | NeurIPSW

- Workshop on "AI for Science: Mind the Gaps", NeurIPS'21, Twitter, LinkedIn
        sponsored by Microsoft Research Cambridge/Amsterdam, BioMap and DeepMind.

- Puria Radmard, InfoEng, Trinity' 22, "Generative Models on Satellite images"
- a Group of Berkeley EECS MEng '22, "Continual Segmentation Adaptation"

Talks and Pres
Research, Startup,
& Trading
- [18-21] quite a bite on some QishiCPC (Premium Member) seminars
- [19. xx] call/pitch/pres on ''Cantab Care'', a startup I co-founded

- [21.10] Graph Denoising via Edge Editing, Amazon Machine Learning Conference
- [21.07] Self-Supervised Learning on 3D Vision, Amazon-UCL Seminar
- [21.07] Modeling Protein with Transformers @ Genetics, Cam
- [21.06] Panel Discussion on AIoT, hosted by Dr. Juejia Zhou, Director of Xiaomi Corp
- [21.03] Neural Volume Rendering @ SigProc, Cam
- [20.08] A Collaborative AI Engine for CT-based COVID-19 Diagnosis @ {CMIH, InfoEng}, Cam
- [20.04] Machine Learning on Sets @ MLG, Cam
- [20.02] 3D Deep Learning Meets Points Cloud @ St Edmund's College, Cam
- [19.10] Federated ML with Differential Privacy @ HackBridge Demo Day
- [18.07] Acceptance Speech (Awardee Representative) @ Cathy Xu Fellowship Awarding Event
- [18.06] Commencement Speech (Valedictorian) @ KYM Honours School, NJU

- Role models: Neil Shen, Kai-Fu Lee
- Love Reading, Noting, Travelling, Cooking & Exercising
- Achieved the 3rd level of National Athlete in 400 metres
- Know a whit about Classical Chinese, Japanese and French
- Used to be Vice President of Cambridge Algorithmic Trading Society
- Won the 2nd prizes in both China High School Biology and Physics Olympiad
- Used to play instruments incl. Erhu (10 years) and Ocarina, achieved the highest level at 11
- Trade on Crypto (since '19) and US/CN Equity (since '18), sometimes in automated high-freq manners

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