Elham Azizi

Elham Azizi
Azizi in 2024
Born	1986 (age 38–39) Tehran, Iran
Citizenship	United States
Alma mater	Sharif University of Technology Boston University
Awards	Vilcek Prize for Creative Promise in Biomedical Science (2025) Takeda/NYAS Innovators in Science Award (2024) Allen Distinguished Investigator Award (2023) NSF CAREER Award (2022)
Scientific career
Fields	Computational biology, Biomedical engineering, Machine learning, Cancer genomics
Institutions	Columbia University
Thesis	Modeling gene regulatory networks through data integration  (2014)
Doctoral advisor	James Galagan
Other academic advisors	Dana Pe'er
Website	azizilab.com

Elham Azizi (Persian: الهام عزیزی; pronounced /ɛlˈhɑːm æˈziːzi/; born 1986) is an Iranian‑American computational biologist and biomedical engineer focused on cancer research. She is the Herbert & Florence Irving Associate Professor of Cancer Data Research and an Associate Professor of Biomedical Engineering at Columbia University. She is also affiliated with the Department of Computer Science, Irving Institute for Cancer Dynamics (IICD), Data Science Institute, and the Herbert Irving Comprehensive Cancer Center.

Azizi directs the Computational Cancer Biology Lab at Columbia, which focuses on developing artificial intelligence and machine learning frameworks, alongside utilizing single‑cell genomic and imaging techniques to study cancer progression and immunotherapy response. Her awards include the Vilcek Prize for Creative Promise in Biomedical Science (2025) and the Takeda/NYAS Innovators in Science Award (2024).

Early life and education

Azizi was born in Tehran, Iran, in 1986. As a high school student at Tehran Farzanegan School, she became the first Iranian recipient of the First Step to Nobel Prize in Physics, which was awarded for a two‑year experiment and statistical models of the trajectories of falling leaves. In 2008, she earned a B.S. in electrical engineering (signal processing) from the Sharif University of Technology. Afterwards, she immigrated to the United States, where she completed an M.S. in electrical engineering in 2010 and a PhD in bioinformatics at Boston University in 2014. Her thesis, supervised by James Galagan and in collaboration with Edoardo Airoldi, integrated gene‑regulatory network modelling with machine learning.

She conducted research in biomedical engineering at Boston University, in statistics at Harvard University, and computational cancer genomics at Microsoft Research. After this, she joined Columbia University as a postdoctoral research scientist under the mentorship of Dana Pe’er, an expert in computational biology, who transitioned to Memorial Sloan Kettering Cancer Center with her in 2016. In her postdoctoral research, Azizi introduced probabilistic modelling approaches to analyze single-cell genomic data, addressing statistical challenges arising from heterogeneous clinical datasets. She leveraged these computational frameworks to elucidate the landscape of diverse immune cell states within the breast tumor microenvironment and extended their application to various cancer contexts.

Research

The Azizi Lab develops frameworks for machine learning, artificial intelligence, and statistics, enabling the understanding of the complex dynamics of tumor microenvironments. By integrating genomic, spatial, transcriptomic, and imaging data, Azizi's research yields insights into cancer progression, immune evasion, and therapeutic resistance.

The lab employs diverse computational techniques, including probabilistic models, deep generative models, attention-based architectures, causal discovery methods, diffusion, and foundation models. These methods facilitate understanding of co-evolving tumour and immune cells, their spatial and temporal dynamics, cellular plasticity, and regulatory mechanisms driving therapeutic outcomes, directly from patient specimens.

Azizi Lab members (2024). Photo courtesy of the Vilcek Foundation.

Their deep generative model for integrating spatial transcriptomics with histological imaging characterizes spatial niches involving metabolic reprogramming and immune-suppressive environments in aggressive breast cancers, such as triple-negative and metaplastic breast cancers, enabling personalized therapeutic targets and biomarkers.

In particular, their computational modeling of tumour-immune interactions in patient specimens has demonstrated that cells driving the graft-versus-leukemia (GvL) effect in acute myeloid leukemia originate from the donor infusion, but their activation relies on a permissive and immunologically diverse bone marrow microenvironment, highlighting the importance of both cellular state and the surrounding microenvironment in determining immunotherapy outcomes. The lab also employs computational models to further decouple environmental effects from tumor-intrinsic effects, for example, to quantify gene dosage effects on phenotypic plasticity and therapeutic resistance in melanoma patients undergoing immune checkpoint blockade therapy. These models reconstruct clonal evolution, pinpointing genetic drivers of resistance.

The lab has also developed generative models to visualize and align diverging cell trajectories, revealing regulatory networks and aberrant cell-state transitions involved in the initiation of cancer. This work identifies rare leukemia cell states and therapeutic targets linked to disrupted gene expression, with the potential to guide early detection of cancer.

Awards and recognition

Azizi receiving the Takeda/NYAS award (2024). Photo courtesy of Takeda and NYAS.

• Chan-Zuckerberg Initiative Science Leadership Award (2022)
• Allen Distinguished Investigator Award, Allen Institute (2023)
• Takeda and the New York Academy of Sciences Early-Career Innovator in Science Award in Cancer Immunology (2024)
• Vilcek Prize for Creative Promise in Biomedical Science (2025)

Outreach and advocacy

In 2016, Azizi co‑founded the Workshop on Computational Biology held for 8 consecutive years at the International Conference on Machine Learning (ICML). She has also organized the IICD Intensive Workshop: Methods in Single-Cell Data Integration and Optimal Transport at Columbia University Irving Institute for Cancer Dynamics.

Azizi has spoken about the challenges she faced as an Iranian woman in science and her commitment to creating an inclusive environment for trainees. She believes that "creative, collaborative and multidisciplinary scientific research demands talents from diverse backgrounds."

Personal life

Azizi is married to computer scientist and entrepreneur Hossein Azari.

See also

• List of Iranian Americans
• List of famous Iranian women