University Paul Sabatier (BS) INSA Toulouse (MS) University of Paris Dauphine (MS) University of Montpellier (PhD)
Known for
AI applications in oncology; leadership of the Englander Institute for Precision Medicine
Awards
NSF CAREER Award (2012) Walter B. Wriston Research Scholar (2016–2019) Clarivate Highly Cited Researcher (2019–2024)
Scientific career
Fields
Artificial intelligence; oncology; computational biology; genomics; precision medicine
Institutions
Weill Cornell Medicine
Olivier Elemento is a French-American computational biologist who directs the Caryl and Israel Englander Institute for Precision Medicine (EIPM) atWeill Cornell Medicine in New York City.[1] As of June 2025 he has authored more than 500 peer-reviewed publications and is listed as aClarivate Highly Cited Researcher.[2] Elemento's work has been profiled inThe New York Times Magazine, NPR,Wired, and other national outlets.[3][4][5]
Elemento earned a bachelor's degree in mechanical engineering from theUniversité Paul Sabatier in Toulouse.[6] He obtained master's degrees from INSA Toulouse (mechanical engineering) and the University of Paris Dauphine (intelligent systems), then completed a doctorate incomputational biology at the University of Montpellier/CNRS in 2003 underOlivier Gascuel and Marie-Paule Lefranc.[6] He carried out post-doctoral research at Princeton University's Lewis-Sigler Institute for Integrative Genomics.[6]
Elemento joined Weill Cornell Medicine in 2008 and became full professor of physiology andbiophysics in 2019.[6] In September 2017 he was appointed director of the Englander Institute for Precision Medicine, succeeding founding director Mark Rubin.[1] He also serves as co-director of the WorldQuant Initiative for Quantitative Prediction alongsideChristopher E. Mason.[7]
In 2020 Elemento launched a hospital-wide whole-genome-sequencing (WGS) initiative withNewYork-Presbyterian Hospital and Illumina.Genetic Engineering & Biotechnology News described it as "the largest clinical WGS effort of its kind in the United States,"[8] andThe New York Times Magazine featured the program in a major article about the transformative potential of genomic sequencing.[3]
Elemento has served as a public voice on the adoption and responsible development of precision oncology and medical AI. In March 2018Wired reported on Medicare's decision to reimburse genomic cancer testing and quoted Elemento on the mainstreaming of sequencing in care,[9] and he later argued in aWall Street Journal op-ed that regulation should not slow access to sequencing-based diagnostics.[10] In 2025, he published an opinion piece inSTAT News advocating for randomized controlled trials in medical AI implementation, arguing that Silicon Valley companies should be held to the same rigorous standards as traditional medical interventions.[11]
In September 2022 Elemento and otolaryngologist Yaël Bensoussan became co-principal investigators ofVoice as a Biomarker of Health, aNational Institutes of Health Bridge2AI consortium.[4]The Verge characterized the effort as "an attempt to turn the human voice into a new vital sign."[12]
In 2024, Elemento co-chaired a workshop with Regina Barzilay convened by theNational Cancer Institute, ARPA-H, and Department of Energy on "Using AI Approaches to Target Undruggable Cancer Targets," which brought together leading scientists to address one of oncology's most challenging problems.[13] The insights from this workshop led to a publishedNature Biotechnology commentary on redefining druggable targets with artificial intelligence.[14]
Outside academia Elemento co-founded Volastra Therapeutics withLewis C. Cantley and Samuel Bakhoum. Volastra is developing treatments targeting chromosomal instability in cancer, with two small molecules currently in Phase 1 clinical trials. The company raised $44 million in seed funding before securing an additional $60 million in Series A financing in 2023, along with a strategic partnership with Microsoft to leverage AI in addressing cancer metastasis.[15][16]
Three of his doctoral students have been recognized onForbes 30 Under 30: Tomer Yaron-Barir, Kaitlyn Gayvert, Neel Madhukar. Kaitlyn Gayvert and Neel Madhukar were named to the Healthcare list in 2016 for work completed in his lab.[17] Tomer Yaron-Barir was recognized onForbes "30 Under 30: Science" in 2024 for co-inventing the Kinase Library under the joint supervision of Elemento andLewis C. Cantley.[18]
Elemento's laboratory combines high-throughput sequencing, single-cell technologies and machine learning.
Artificial-intelligence approaches in oncology – Developed the machine-learning model PrOCTOR for predicting clinical-trial toxicity.[19] He presented related work in the opening-plenary lecture at AACR Virtual Annual Meeting II (June 22, 2020).[20]
AI embryo assessment – Contributed to STORK, a computer-vision system (led by Iman Hajirasouliha) that outperformed embryologists at grading IVF embryos; the study was profiled inWired.[5]
Spatial-omics of disease – Led development of UTAG, an unsupervised algorithm for tissue-architecture mapping.[21] He also co-led aNature atlas of COVID-19 lung pathology.[22] In 2025,amfAR INNOVATIONS interviewed Elemento about applying these AI and spatial-omics methods to HIV research.[23]
Elemento O.; Khozin S.; Sternberg C.N. (2025). "The Use of Artificial Intelligence for Cancer Therapeutic Decision-Making."NEJM AI. doi:10.1056/AIra2401164.
Akinsanya K.; AlQuraishi M.; Boija A.; et al. (2025). "Redefining druggable targets with artificial intelligence."Nature Biotechnology. doi:10.1038/s41587-025-02770-1.
Bhinder B.; Gilvary C.; Madhukar N.S.; Elemento O. (2021). "Artificial Intelligence in Cancer Research and Precision Medicine."Cancer Discovery11: 900–915. doi:10.1158/2159-8290.CD-21-0090.
Rendeiro A.F.; Ravichandran H.; Bram Y.; Chandar V.; Kim J.; Meydan C.; Park J.; Foox J.; Hether T.; Warren S.; Kim Y.; Reeves J.; Salvatore S.; Mason C.E.; Swanson E.C.; Borczuk A.C.; Elemento O.; Schwartz R.E. (2021). "The spatial landscape of lung pathology during COVID-19 progression."Nature593: 564–569. doi:10.1038/s41586-021-03475-6.
Gayvert K.; Madhukar N.S.; Elemento O. (2016). "A data-driven approach to predicting successes and failures of clinical trials."Cell Chemical Biology23 (10): 1294–1301. doi:10.1016/j.chembiol.2016.07.023.
