Amin Emad

Amin Emad is an AI researcher and associate professor at McGill whose group applies machine learning to biology and medicine. He earned electrical-engineering degrees at Sharif and Alberta, completed a PhD at Illinois, and worked at NIH's KnowEnG center before joining McGill. His work includes ProGENI for gene prioritization, MARSY for drug-synergy prediction, and CLASP for multimodal protein representation. In September 2026, he coauthored DiffDose for individualized drug-regimen design; he directs the COMBINE Lab and is an associate academic member of Mila.

Now at: McGill University and Mila
Works: 95
Citations: 773
h-index: 12
Links: Website and Google Scholar

Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

2014–2015

CompGen fellowship at Illinois

In 2014–2015, he is a CompGen fellow enrolled in Illinois' ECE PhD program. His degrees include a B.S. in electrical engineering from Sharif University of Technology, an M.S. in electrical engineering from the University of Alberta, and a PhD from UIUC.
2017

ProGENI for chemoresistance

In 2017, he coauthors a Genome Biology paper on ProGENI, which combines transcriptomic data with prior network information to prioritize genes for chemoresistance research.
2018–2020

KnowEnG and McGill

In 2018, he is a KnowEnG postdoc at Illinois preparing to join McGill as tenure-track faculty. By January 2020, he is an assistant professor of electrical and computer engineering at McGill and co-first authors a paper introducing KnowEnG's cloud platform for genomic analysis.
2020

Mila associate membership

In February 2020, Mila welcomes him as an Associate Academic Member among four new members.
2023

MARSY predicts drug synergy

In 2023, he coauthors MARSY, a deep-learning tool for predicting drug-combination synergy scores in cancer.
2025

Protein representations with CLASP

In 2025, he coauthors CLASP, a tri-modal contrastive-learning framework that represents protein structure, sequence and descriptions in one shared space for retrieval and zero-shot classification.
September 2026

Personalized dosing with DiffDose

In September 2026, he coauthors DiffDose, a differentiable-programming framework that uses automatic differentiation to optimize individualized drug regimens, including dose amounts and administration times.
As of October 2026

Associate professor at McGill

As of October 2026, he is an associate professor in McGill's Department of Electrical and Computer Engineering, directs the COMBINE Lab, and is an Associate Academic Member of Mila. His group develops deep-learning and network-representation methods for biomedical research, including foundation models and generative AI.