Sriram Sankararaman

Professor Computer Science Department Department of Human Genetics Department of Computational Medicine Bioinformatics Interdepartmental Graduate Program University of California, Los Angeles Email: sriram [@] cs [DOT] ucla [DOT] edu Lab website: Machine Learning and Genomics Lab

About me

I am a Professor of Computer Science, Human Genetics, and Computational Medicine at UCLA. I am broadly interested in problems at the intersection of computer science, statistics, and biomedicine. Here are recent videos that summarize work from our lab:

• Scaling statistical models to millions of genomes@IMSI

• Archaic admixture in human history@Radcliffe Institute

• Signals of Ghost Archaic DNA in Present-Day West African Populations

• Recovering signals of ghost archaic introgression in African populations@CARTA

Selected publications

• A Scalable adaptive quadratic kernel method for interpretable epistasis analysis in complex traits, Genome Research (2024)

• A scalable and robust variance components method reveals insights into the architecture of gene-environment interactions underlying complex traits, The American Journal of Human Genetics (2024)

• Deep learning-based phenotype imputation on population-scale biobank data increases genetic discoveries, Nature Genetics (2023)

• Fast kernel-based association testing of non-linear genetic effects for biobank-scale data, Nature Communications (2023)

• The lingering effects of Neanderthal introgression on human complex traits, eLife (2023)

• Leveraging family data to design Mendelian Randomization that is provably robust to population stratification, Genome Research (2023)
  

• Inferring population structure in biobank-scale genomic data, The American Journal of Human Genetics (2022)

• Marginal Contribution Feature Importance – an axiomatic approach for the natural case, ICML (2021)

• Advancing admixture graph estimation via maximum likelihood network orientation, Bioinformatics (special issue of ISMB/ECCB) (2021)

• Quantifying the contribution of dominance effects to complex trait variation in biobank-scale data, The American Journal of Human Genetics (2021)

• Efficient variance components analysis across millions of genomes, Nature Communications (2020)

• Scalable probabilistic PCA for large-scale genetic variation data, PLoS Genetics (2020)

• Recovering signals of ghost archaic introgression in African populations, Science Advances (2020)

• The combined landscape of Denisovan and Neanderthal ancestry in present-day humans, Current Biology (2016)

• Genetic and socioeconomic study of mate choice in Latinos reveals novel assortment patterns, PNAS (2016)

• The genomic landscape of Neanderthal ancestry in present-day humans, Nature (2014)

• Genomic privacy and limits of individual detection in a pool, Nature genetics (2009)

• Estimating local ancestry in admixed populations, The American Journal of Human Genetics (2008)

Honors and Awards

• NSF Career Award (2020)

• Microsoft Investigator Fellow (2019)

• Northrop Grumman Excellence in Teaching Award, UCLA (2019)

• Okawa Foundation Research Grant (2017)

• UCLA Hellman Fellow (2017)

• Alfred P. Sloan Fellow (2017)

• NIH Pathway to Independence Award (2014)

• Fellow, Simons Institute for the Theory of Computing, Berkeley (2014)

• Harvard Science of the Human Past fellow (2012)

• Visvesvaraya medal for highest CGPA in the graduating class, IIT Madras (2004)