Eleazar Eskin

Eleazar Eskin is a Professor at the University of California Los Angeles (UCLA) with appointments in Computer Science, Human Genetics, and Computational Medicine. He is affiliated with the Henry Samueli School of Engineering and Applied Science and contributes to interdisciplinary research bridging computational methods with biomedical applications.

• PhD in Computer Science, Stanford University
• Postdoctoral Fellowship, University of Southern California

Eskin’s research focuses on computational genomics, statistical genetics, and machine learning applications in medicine. He develops algorithms for genome-wide association studies (GWAS), structural variant detection, and multi-omics data integration, addressing challenges in population stratification, pleiotropy, and epigenetic regulation.

His recent publications span 2023–2025, emphasizing machine learning in clinical diagnostics, computational reproducibility, and genetic mechanisms in complex traits. Collaborative projects include the GTEx Consortium and UCLA’s Computational Pan-Genomics initiatives.

Scientific awards include the NSF CAREER Award, Alfred P. Sloan Fellowship, and NIH Director’s Pioneer Award. He leads NIH-funded programs like R25GM135043 (Computational Genomics Summer Institute) and R25NS115554 (Undergraduate Neurogenomics Training).

Eskin mentors trainees through NIH T32 grants and co-developed methods like MARS (allelic heterogeneity), PLEIO (pleiotropy analysis), and BayesCCE (epigenetic modeling). His work impacts SARS-CoV-2 testing, neurodevelopmental disorders, and precision medicine.