Marinka Zitnik

Research:

AI holds tremendous promise in enabling scientific breakthroughs and discoveries in diverse areas. Dr. Zitnik investigates machine learning with a current focus on networked systems that require infusing structure and domain knowledge. This research is theoretically grounded and spans several areas of informatics.

Zitnik's research strategy is to create foundational models, including pre-trained models, self-supervised models, general-purpose models, multi-purpose models, and multi-modal models, trained on broad data at scale. To this end, Dr. Zitnik and her team: (1) invent ways to infuse domain knowledge & structure into complex and heterogeneous datasets to reduce uncertainty and enable generalization to entirely new scenarios not seen during training; (2) Develop methods that produce actionable & trustworthy representations and can reason over massive datasets, and (3) Translate machine learning research into innovative applications and solutions for open questions.

This research creates new avenues for network biology, developing safe & effective medicines, and giving the right patient the right treatment at the right time to have medicinal effects that are consistent from person to person and with results in the laboratory.

Bio:

Dr. Zitnik is an Assistant Professor at Harvard with appointments in the Department of Biomedical Informatics, Broad Institute of MIT and Harvard, and Harvard Data Science. Before Harvard, she was a postdoctoral fellow in Computer Science at Stanford and also a member of the Chan Zuckerberg Biohub. Dr. Zitnik has published extensively in top ML venues (e.g., NeurIPS, ICLR, ICML) and leading journals (e.g., Nature Methods, Nature Communications, PNAS). She has organized numerous workshops and tutorials in the nexus of AI, deep learning, drug discovery, and medical AI at leading conferences (e.g., NeurIPS, ICLR, ICML, ISMB, AAAI, WWW), where she is also in the organizing committees.

Dr. Zitnik's algorithms have had a tangible impact, which has garnered the interests of government, academic, and industry researchers and has put new tools in the hands of practitioners. Her methods are used by major biomedical institutions and the pharmaceutical industry. Dr. Zitnik's research recently won best paper and research awards from the International Society for Computational Biology, Bayer Early Excellence in Science Award, Amazon Faculty Research Award, Roche Alliance with Distinguished Scientists Award, a Rising Star Award in EECS, and a Next Generation Recognition in Biomedicine, being the only young scientist who received such recognition in both EECS and Biomedicine.