Marinka Zitnik" />
Assistant Professor
Ada Fang" />
PhD Student
Michelle M. Li" />
PhD Student
Yasha Ektefaie" />
PhD Student
Guadalupe Gonzalez" />
PhD Student
Imperial College London
Valentina Giunchiglia" />
PhD Student
Imperial College London
George Dasoulas" />
Postdoctoral Fellow
Harvard Data Science Fellow
Huan He" />
Postdoctoral Fellow
Ruth Johnson" />
Postdoctoral Fellow
Harvard Berkowitz Fellow
Tianlong Chen" />
Postdoctoral Fellow
Shen Wanxiang" />
Postdoctoral Fellow
Yepeng Huang" />
Graduate Researcher
Tom Cobley" />
Graduate Researcher
MIT
Owen Queen" />
Graduate Researcher
Diego Trujillo" />
Graduate Researcher
Michelle Dai" />
Graduate Researcher
Jean-Guillaume Brasier" />
IACS Graduate Student
Varun Ullanat" />
Graduate Researcher
Zaixi Zhang" />
Visiting Fellow
Isuru Herath" />
Visiting Fellow
Ayush Noori" />
Undergraduate Researcher
Harvard
Ziyuan Zhao" />
Undergraduate Researcher
Harvard
Chirag Agarwal" />
Research Scientist
Adobe Research
Xiang Zhang" />
Assistant Professor
UNC Charlotte
Josh Pan" />
Research Scientist
DeepMind
Lab alumni
2023:- Ziyuan Zhao (Undergraduate Researcher → Systems Biology PhD Student, Harvard Medical School)
- Nicholas Ho (Undergraduate Researcher → Computer Science PhD Student, Carnegie Mellon University)
- Yepeng Huang (Graduate Researcher at Harvard Chan → Biological and Medical Sciences PhD Student, Harvard Medical School)
- Marissa Sumathipala (Undergraduate Researcher at Harvard College; Gates Cambridge Scholarship; Churchill Scholarship; Cambridge University → Neuroscience PhD Student, Harvard University)
- Julia Balla (Undergraduate Researcher at MIT → Computer Science PhD Student, MIT)
- Jiali Cheng (Undergraduate Researcher → Computer Science PhD Student, UMass Lowell)
- Marie Zhang (HMS)
- Man Qing Liang (HMS → Data Scientist, Dandelion)
- Payal Chandak (Undergraduate Researcher → Harvard-MIT HST PhD Student, Harvard University & MIT)
- Xiang Zhang (Postdoctoral Fellow, HMS → Assistant Professor, UNC Charlotte)
- Chirag Agarwal (Postdoctoral Fellow, HMS → Research Scientist, Adobe Research)
- Josh Pan (Postdoctoral Fellow, Broad Institute → Research Scientist, DeepMind)
- Michelle Lu (Harvard College)
- Raunak Chowdhuri (MIT)
- Marie Zhang (HMS)
- Satvik Tripathi (Undergraduate Researcher, Drexel University)
- Varun Tekur (Undergraduate Researcher)
- Lydia Fozo (Undergraduate Researcher, Johns Hopkins University)
- Kexin Huang (Harvard Chan → Computer Science PhD Student, Stanford University)
- Haoxin Li (Harvard Chan)
- Yucong Lin (Harvard Chan → Beijing Institute of Technology)
- Mert Erden (Tufts University)
- Jingyi Liu (HMS)
- Yujie Shao (HMS)
- Stone Chen (HMS)
- Kathleen Sucipto (HMS)
- Min Jean Cho (Undergraduate Researcher, Brown University)
Latest News
May 2023: Congratulations to Ada and Michelle
Congrats to PhD student Michelle on being selected as the 2023 Albert J. Ryan Fellow and also to participate in the Heidelberg Laureate Forum. Congratulations to PhD student Ada for being selected as the Kempner Institute Graduate Fellow!
Apr 2023: Universal Domain Adaptation at ICML 2023
New paper introducing the first model for closed-set and universal domain adaptation on time series accepted at ICML 2023. Raincoat addresses feature and label shifts and can detect private labels. Project website.
Apr 2023: Celebrating Achievements of Our Undergrads
Undergraduate researchers Ziyuan, Nick, Yepeng, Jiali, Julia, and Marissa are moving onto their PhD research in Computer Science, Systems Biology, Neuroscience, and Biological & Medical Sciences at Harvard, MIT, Carnegie Mellon University, and UMass Lowell. We are excited for the bright future they created for themselves.
Apr 2023: Welcoming a New Postdoctoral Fellow
An enthusiastic welcome to Tianlong Chen, our newly appointed postdoctoral fellow.
Apr 2023: New Study in Nature Machine Intelligence
New paper in Nature Machine Intelligence introducing the blueprint for multimodal learning with graphs.
Mar 2023: Precision Health in Nature Machine Intelligence
New paper with NASA in Nature Machine Intelligence on biomonitoring and precision health in deep space supported by artificial intelligence.
Mar 2023: Self-Driving Labs in Nature Machine Intelligence
New paper with NASA in Nature Machine Intelligence on biological research and self-driving labs in deep space supported by artificial intelligence.
Mar 2023: TxGNN - Zero-shot prediction of therapeutic use
New study on zero-shot prediction of therapeutic use with geometric deep learning and clinician centered design. Check out our project website and TxGNN Explorer.
Mar 2023: GraphXAI published in Scientific Data
Our approach evaluating explainability of geometric deep learning models is published in Scientific Data. Project website.
Feb 2023: Welcoming New Postdoctoral Fellows
A warm welcome to postdoctoral fellows Wanxiang Shen and Ruth Johnson. Congratulations to Ruthie for being named a Berkowitz Fellow.
Feb 2023: New Preprint on Distribution Shifts
Feb 2023: PrimeKG published in Scientific Data
Our multimodal knowledge graph for precision medicine is published in Scientific Data. Project website.
Jan 2023: GNNDelete published at ICLR 2023
New paper on machine unlearning for graph neural networks accepted at ICLR 2023. Project website.
Jan 2023: New Network Principle for Molecular Phenotypes
New paper introducing mutual interactor-based GNN for molecular phenotype prediction at PSB. Project website.
Dec 2022: Can we shorten rare disease diagnostic odyssey?
New preprint! Geometric deep learning for diagnosing patients with rare genetic diseases. Implications for using deep learning on sparsely-labeled medical datasets. Thankful for this collaboration with Zak Lab. Project website.
Nov 2022: Can AI transform the way we discover new drugs?
Our conversation with Harvard Medicine News highlights recent developments and new features in Therapeutics Data Commons.
Oct 2022: New Paper in Nature Biomedical Engineering
New paper on graph representation learning in biomedicine and healthcare published in Nature Biomedical Engineering.
Sep 2022: New Paper in Nature Chemical Biology
Our paper on artificial intelligence foundation for therapeutic science is published in Nature Chemical Biology.
Sep 2022: Self-Supervised Pre-Training at NeurIPS 2022
New paper on self-supervised contrastive pre-training accepted at NeurIPS 2022. Project page. Thankful for this collaboration with the Lincoln National Laboratory.
Sep 2022: Best Paper Honorable Mention Award at IEEE VIS
Our paper on user-centric AI of drug repurposing received the Best Paper Honorable Mention Award at IEEE VIS 2022. Thankful for this collaboration with Gehlenborg Lab.
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