Advising and Mentoring


Open positions
<a href=Marinka Zitnik" />

Marinka Zitnik

Assistant Professor

<a href=Ada Fang" />

Ada Fang

PhD Student

<a href=Michelle M. Li" />

Michelle M. Li

PhD Student

<a href=Yasha Ektefaie" />

Yasha Ektefaie

PhD Student

<a href=Guadalupe Gonzalez" />

Guadalupe Gonzalez

PhD Student
Imperial College London

<a href=Huan He" />

Huan He

Postdoctoral Fellow

<a href=George Dasoulas" />

George Dasoulas

Postdoctoral Fellow

<a href=Tom Cobley" />

Tom Cobley

Graduate Researcher
MIT

<a href=Yepeng Huang" />

Yepeng Huang

Graduate Researcher

<a href=Owen Queen" />

Owen Queen

Graduate Researcher

<a href=Marie Zhang" />

Marie Zhang

Graduate Researcher

<a href=Diego Trujillo" />

Diego Trujillo

Graduate Researcher

<a href=Jean-Guillaume Brasier" />

Jean-Guillaume Brasier

IACS Graduate Student

<a href=Michelle Dai" />

Michelle Dai

Graduate Researcher

<a href=Nicholas Ho" />

Nicholas Ho

Visiting Fellow

<a href=Isuru Herath" />

Isuru Herath

Visiting Fellow

<a href=Ayush Noori" />

Ayush Noori

Undergraduate Researcher
Harvard

<a href=Ziyuan Zhao" />

Ziyuan Zhao

Undergraduate Researcher
Harvard

<a href=Jiali Cheng" />

Jiali Cheng

Research Fellow

Associate members

<a href=Chirag Agarwal" />

Chirag Agarwal

Research Scientist
Adobe Research

<a href=Xiang Zhang" />

Xiang Zhang

Assistant Professor
UNC Charlotte

<a href=Josh Pan" />

Josh Pan

Research Scientist
DeepMind

Lab alumni

  • Man Qing Liang (HMS, 2022)
  • Satvik Tripathi (Visiting Student 2022)
  • Julia Balla (MIT 2022; Oxford University, Computer Science)
  • Payal Chandak (Visiting Student 2020-2021; Harvard-MIT HST PhD Student)
  • Marissa Sumathipala (Harvard College, 2022; Gates Cambridge Scholarship; Churchill Scholarship; Cambridge University)
  • Xiang Zhang (Postdoctoral Fellow, HMS, 2022; Assistant Professor, UNC Charlotte)
  • Chirag Agarwal (Postdoctoral Fellow, HMS, 2022; Research Scientist, Adobe Research)
  • Josh Pan (Postdoctoral Fellow, Broad Institute, 2022; Research Scientist, DeepMind)
  • Michelle Lu (Harvard College, 2022)
  • Raunak Chowdhuri (MIT, 2022)
  • Varun Tekur (Harvard College, 2022)
  • Lydia Fozo (Johns Hopkins University, 2022)
  • Kexin Huang (Harvard Chan, 2021; CS PhD Student, Stanford)
  • Haoxin Li (Harvard Chan, 2021)
  • Yucong Lin (Harvard Chan, 2021; Beijing Institute of Technology)
  • Mert Erden (Tufts University, 2021)
  • Jingyi Liu (HMS, 2021)
  • Yujie Shao (HMS, 2020)
  • Stone Chen (HMS, 2020)
  • Kathleen Sucipto (HMS, 2020)
  • Min Jean Cho (Brown University, 2020)

Latest News

Jan 2023:   GNNDelete at ICLR 2023

Jan 2023:   New Network Principle for Molecular Phenotypes

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.

Sep 2022:   Multimodal Representation Learning with Graphs

Aug 2022:   On Graph AI for Precision Medicine

The recording of our tutorial on using graph AI to advance precision medicine is available. Tune into four hours of interactive lectures about state-of-the-art graph AI methods and applications in precision medicine.

Aug 2022:   Evaluating Explainability for GNNs

New preprint! We introduce a resource for broad evaluation of the quality and reliability of GNN explanations, addressing challenges and providing solutions for GNN explainability. Project website.

Jul 2022:   New Frontiers in Graph Learning at NeurIPS

Excited to organize the New Frontiers in Graph Learning workshop at NeurIPS.

Jul 2022:   AI4Science at NeurIPS

We are excited to host the AI4Science meeting at NeurIPS discussing AI-driven scientific discovery, implementation and verification of AI in science, the influence AI has on the conduct of science, and more.

Jul 2022:   Graph AI for Precision Medicine at ISMB

Jul 2022:   Welcoming Fellows and Summer Students

Welcoming a research fellow Julia Balla and three Summer students, Nicholas Ho, Satvik Tripathi, and Isuru Herath.

Jun 2022:   Broadly Generalizable Pre-Training Approach

Excited to share a preprint on self-supervised method for pre-training. Project website with evaluation on eight datasets, including electrodiagnostic testing, human daily activity recognition, and health state monitoring.

Jun 2022:   Welcoming New Postdocs

Excited to welcome George Dasoulas and Huan He, new postdocs joining us this Summer.

May 2022:   George Named the 2022 Wojcicki Troper Fellow

May 2022:   New preprint on PrimeKG

New preprint on building knowledge graphs to enable precision medicine applications.

May 2022:   Building KGs to Support Precision Medicine

Zitnik Lab  ·  Artificial Intelligence in Medicine and Science  ·  Harvard  ·  Department of Biomedical Informatics