\(^\dagger\), * denote equal contributions
name denotes members of the lab


  1. Albert Xue, Jingyou Rao, Sriram Sankararaman\(^\dagger\), Harold Pimentel\(^\dagger\)
    dotears: Scalable, consistent DAG estimation using observational and interventional data

  2. Meihua Dang, Anji Liu, Xinzhu Wei, _Sriram Sankararaman\(^\dagger\), Guy Van den Broeck\(^\dagger\)
    Tractable and Expressive Generative Models of Genetic Variation Data
    RECOMB (2022)

  3. Brunilda Balliu, Chris Douglas, Liat Shenhav, Yue Wu, Darsol Seok, Doxa Chatzopoulou, Bill Kaiser, Victor Chen, Jennifer Kim, Sandeep Deverasetty, Inna Arnaudova, Robert Gibbons, Eliza Congdon, Michelle G. Craske, Nelson Freimer, Eran Halperin, Sriram Sankararaman, Jonathan Flint
    Personalized Mood Prediction from Patterns of Behavior Collected with Smartphones
    medRxiv (2022)

  4. Sajad Darabi, Shayan Fazeli, Ali Pazokitoroudi, Sriram Sankararaman, Majid Sarrafzadeh
    Contrastive Mixup: Self- and Semi-Supervised learning for Tabular Domain
    arXiv (2021)

  5. Robert Brown, Sriram Sankararaman Bogdan Pasaniuc
    Haplotype-based eQTL mapping finds evidence for complex gene regulatory regions poorly tagged by marginal SNPs
    bioRxiv (2018)



  1. Andrew Dahl*, Michael Thompson, Ulzee An, Morten Krebs, Vivek Appadurai, Richard Border, Silviu-Alin Bacanu, Thomas Werge, Jonathan Flint, Andrew J. Schork, Sriram Sankararaman, Kenneth Kendler, Na Cai*
    Phenotype integration improves power and preserves specificity in biobank-based genetic studies of Major Depressive Disorder
    Nature Genetics (to appear) (2023)

  2. Ulzee An, Ali Pazokitoroudi, Marcus Alvarez, Lianyun Huang, Silviu Alin-Bacanu, Andrew J. Schork, Kenneth Kendler, Paivi Pajukanta, Jonathan Flint, Noah Zaitlen, Na Cai, Andy Dahl, Sriram Sankararaman
    Deep Learning-based Phenotype Imputation on Population-scale Biobank Data Increases Genetic Discoveries
    Nature Genetics (to appear) (2023) Preliminary version presented at RECOMB (2022)

  3. Boyang Fu, Ali Pazokitoroudi, Mukund Sudarshan, Lakshminarayanan Subramanian, Sriram Sankararaman
    Fast kernel-based association testing of non-linear genetic effects for biobank-scale data
    Nature Communications (to appear) (2023)

  4. Shuyu Lin, et al.
    Non-invasive touch-based lithium monitoring using an organohydrogel-based sensing interface
    Advanced Materials Technologies (2022)

  5. Xinzhu Wei*, Christopher Robles*, Ali Pazokitoroudi, Andrea Ganna, Alexander Gusev, Arun Durvasula, Steven Gazal, Po-Ru Loh, David Reich, Sriram Sankararaman
    The lingering effects of Neanderthal introgression on human complex traits
    eLife (2023)

  6. Kangcheng Hou, et al.
    Causal effects on complex traits are similar across segments of different continental ancestries within admixed individuals
    Nature Genetics (2023)

  7. Xinjun Zhang, Bernard Kim, Armaan Singh, Sriram Sankararaman, Arun Durvasula, Kirk E. Lohmueller
    MaLAdapt reveals novel targets of adaptive introgression from Neanderthals and Denisovans in worldwide human populations
    Molecular Biology and Evolution (2023)

  8. Nathan LaPierre*, Boyang Fu*, Steven Turnbull, Eleazar Eskin, Sriram Sankararaman
    Leveraging family data to design Mendelian Randomization that is provably robust to population stratification
    Genome Research (2023)
    Preliminary version presented at RECOMB (2023)

  9. Aditya Gorla, Sriram Sankararaman, Esteban Burchard, Jonathan Flint, Noah Zaitlen, Elior Rahmani
    Phenotypic subtyping via contrastive learning
    RECOMB (2023)


  1. Richard Border, et al.
    Cross-trait assortative mating is widespread and inflates genetic correlation estimates
    Science (2022)

  2. Haisong Lin, et al.
    Autonomous wearable sweat rate monitoring based on digitized microbubble detection
    Lab on a Chip (2022)

  3. Oren Avram, et al.
    Detecting risk factors for age-related macular degeneration from limited volumetric optical coherence tomography data by transfer learning and vision transformers
    ML4H (2022)

  4. Jeffrey Chiang, et al.
    Automated Identification of Incomplete and Complete Retinal Epithelial Pigment and Outer Retinal Atrophy Using Machine Learning
    Opthalmology Retina (2022)

  5. Ulzee An*, Liat Shenav*, Christine Olson, Elaine Hsiao, Eran Halperin\(^\dagger\), Sriram Sankararaman\(^\dagger\)
    STENSL: microbial Source Tracking with ENvironment SeLection
    mSystems (2022)

  6. Ruth Johnson, et al.
    Leveraging genomic diversity for discovery in an EHR-linked biobank: the UCLA ATLAS Community Health Initiative
    Genome Medicine [medRxiv] (2022)

  7. Mike Thompson*, Brian Hill*, et al.
    Methylation risk scores are associated with a collection of phenotypes within electronic health record systems
    NPJ Genomic Medicine [medRxiv] (2022)

  8. Jennifer Zou, Jinjing Zhou, Sarah Faller, Robert Brown, Sriram Sankararaman, Eleazar Eskin
    Accurate modeling of replication rates in genome-wide association studies by accounting for Winner’s Curse and study-specific heterogeneity
    G3: Genes, Genomes, and Genetics [bioRxiv] (2022)

  9. Hillary Coller, et al.
    Bruins-in-Genomics: Evaluation of the Impact of a UCLA Undergraduate Summer Program in Computational Biology on Participating Students
    PLoS One (2022)

  10. Alec Chiu, Erin Molloy, Zilong Tan, Ameet Talwalkar, Sriram Sankararaman
    Inferring population structure in biobank-scale genomic data
    The American Journal of Human Genetics (2022) [PDF]

  11. Leah Briscoe, Brunilda Balliu, Sriram Sankararaman, Eran Halperin, Nandita Garud
    Correcting for Background Noise Improves Phenotype Prediction from Human Gut Microbiome Data
    PLoS Computational Biology (2022)

  12. Carlos Cinelli, Nathan LaPierre, Brian Hill, Sriram Sankararaman, Eleazar Eskin
    Robust Mendelian randomization in the presence of residual population stratification, batch effects and horizontal pleiotropy
    Nature Communications (2022)


  1. Yi Ding*, Kangcheng Hou*, Kathryn Burch, Sandra Lapinska, Sriram Sankararaman, Bogdan Pasaniuc
    Large uncertainty in individual PRS estimation impacts PRS-based risk stratification
    Nature Genetics (2021)

  2. Yue Wu, Kathryn Burch, Andrea Ganna, Paivi Pajukanta, Bogdan Pasaniuc, Sriram Sankararaman
    Fast estimation of genetic correlation for Biobank-scale data
    The American Journal of Human Genetics (2021) [PDF]

  3. Ruth Johnson, Kathryn Burch, Kangcheng Hou, Mario Paciuc, Bogdan Pasaniuc, Sriram Sankararaman
    A scalable method for estimating the regional polygenicity for complex traits
    PLoS Computational Biology (2021) [PDF ]
    Preliminary version presented at RECOMB (2020)

  4. Brandon Jew*, Jiajin Li*, Sriram Sankararaman, Jae Hoon Sul
    An efficient linear mixed model framework for meta-analytic association studies across multiple contexts
    Workshop on Algorithms in Bioinformatics (WABI) (2021)

  5. Anthony Findley, et al.
    Functional dynamic genetic effects on gene regulation are specific to particular cell types and environmental conditions
    eLife (2021)

  6. Amnon Catav, Boyang Fu, Jason Ernst, Sriram Sankararaman, Ran Gilad-Bachrach
    Marginal Contribution Feature Importance – an Axiomatic Approach for The Natural Case
    ICML (2021) [arXiv]

  7. Erin Molloy, Arun Durvasula, Sriram Sankararaman
    Advancing admixture graph estimation via maximum likelihood network orientation
    Bioinformatics (special issue of ISMB/ECCB) (2021) [PDF]

  8. Nadav Rakocz, et al.
    Automated identification of clinical biomarkers from sparsely annotated 3-dimensional medical imaging
    NPJ Digital Medicine (2021) [PDF]

  9. Ali Pazokitoroudi, Alec Chiu, Kathryn Burch, Bogdan Pasaniuc, Sriram Sankararaman
    Quantifying the contribution of dominance effects to complex trait variation in biobank-scale data
    The American Journal of Human Genetics (2021) [PDF, Supporting Information]

  10. Mukund Sudarshan, Aahlad Manas Puli, Lakshmi Subramanian, Sriram Sankararaman, Rajesh Ranganath
    CONTRA: Contrarian statistics for controlled variable selection
    AISTATS (Proceedings of The 24th International Conference on Artificial Intelligence and Statistics) (2021). [PDF]


  1. Arunabha Majumdar, Kathryn Burch, Sriram Sankararaman, Bogdan Pasaniuc, James Gauderman, John Witte
    A two-step approach to testing overall effect of gene-environment interaction for multiple phenotypes
    Bioinformatics (2020) [bioRxiv].

  2. Nadav Rakocz, Boyang Fu, Eran Halperin\(^\dagger\), Sriram Sankararaman\(^\dagger\)
    A Statistical Model for Quantifying the Needed Duration of Social Distancing for the COVID-19 Pandemic
    [KDD 2020 - AI For COVID-19] (2020) [PDF]

  3. Sriram Sankararaman
    Methods for detecting introgressed archaic sequences
    Current Opinions in Genetics and Development (2020) [PDF]

  4. Ali Pazokitoroudi, Yue Wu, Kathryn Burch, Kangcheng Hou, Aaron Zhou, Bogdan Pasaniuc, Sriram Sankararaman
    Efficient variance components analysis across millions of genomes
    Nature Communications (2020) [PDF, Supporting Information]
    Preliminary version presented at RECOMB (2019) and NeurIPS Machine Learning in Computational Biology Workshop (2019).

  5. Ruth Johnson, Kathryn Burch, Kangcheng Hou, Mario Paciuc, Bogdan Pasaniuc, Sriram Sankararaman
    A scalable method for estimating the regional polygenicity for complex traits
    RECOMB (2020) [bioRxiv]

  6. Gregory Plumb, Jonathan Terhorst, Sriram Sankararaman, Ameet Talwalkar
    Explaining Groups of Points in Low-Dimensional Representations
    ICML (Proceedings of the 37th International Conference on Machine Learning) (2020) [PDF]

  7. Yue Wu, Eleazar Eskin\(^\dagger\), Sriram Sankararaman\(^\dagger\)
    A unifying framework for imputing summary statistics in Genome-wide Association Studies
    Journal of Computational Biology (2020) [PDF]
    Preliminary version presented at RECOMB (2018)

  8. Aman Agrawal*, Alec M. Chiu*, Minh Le, Eran Halperin, Sriram Sankararaman
    Scalable probabilistic PCA for large-scale genetic variation data
    PLoS Genetics (2020) [PDF, Supporting Information]

  9. Arun Durvasula, Sriram Sankararaman
    Recovering signals of ghost archaic introgression in African populations
    Science Advances (2020) [PDF, Supporting Information]


  1. Brian Hill*, Robert Brown*, Eilon Gabel, Christine Lee, Maxime Cannesson, Loes Olde Loohuis, Ruth Johnson, Brandon Jew, Uri Maoz, Aman Mahajan, Sriram Sankararaman\(^\dagger\), Ira Hofer\(^\dagger\), Eran Halperin\(^\dagger\)
    Preoperative predictions of in-hospital mortality using electronic medical record data
    British Journal of Anaesthesia (2019) [PDF, Supporting Information]

  2. Kangcheng Hou*, Kathryn Burch*, Arunabha Majumdar, Huwenbo Shi, Nicholas Mancuso, Yue Wu, Sriram Sankararaman, Bogdan Pasaniuc
    Accurate estimation of SNP-heritability from biobank-scale data irrespective of genetic architecture
    Nature Genetics (2019) [PDF, Supporting Information]

  3. Yue Wu, Anna Yaschenko, Mohammadreza Heydary, Sriram Sankararaman
    Fast estimation of genetic correlation for Biobank-scale data
    RECOMB (2019) [bioRxiv]

  4. Elior Rahmani, Regev Schweiger, Brooke Rhead, Lindsey Criswell, Lisa Barcellos, Eleazar Eskin, Saharon Rosset, Sriram Sankararaman, Eran Halperin
    Cell-type-specific resolution epigenetics without the need for cell sorting or single-cell biology
    Nature Communications (2019) [PDF, Supporting Information]
    Preliminary version presented at RECOMB (2018)

  5. Arun Durvasula, Sriram Sankararaman
    A statistical model for reference-free inference of archaic local ancestry
    PLoS Genetics (2019) [PDF, Supporting Information]


  1. Yue Wu, Sriram Sankararaman
    A scalable estimator of SNP heritability for biobank-scale data
    Bioinformatics (special issue of ISMB) (2018) [PDF]

  2. Ruth Johnson, Huwenbo Shi, Bogdan Pasaniuc\(^\dagger\), Sriram Sankararaman\(^\dagger\)
    A unifying framework for joint trait analysis under a non-infinitesimal model
    Bioinformatics (special issue of ISMB) (2018) [PDF]

  3. Molly Schumer, et al.
    Natural selection interacts with recombination to shape the evolution of hybrid genomes
    Science (2018) [PDF, Supporting Information]

  4. Charleston Chiang, Serghei, Mangul, Christopher Robles, Sriram Sankararaman
    A comprehensive map of genetic variation in the world's largest ethnic group - Han Chinese
    Molecular Biology and Evolution (2018) [PDF]


  1. Farhad Hormozdiari, et al.
    Widespread allelic heterogeneity in complex traits
    The American Journal of Human Genetics (2017) [PDF]

  2. Bernard Jegou, Sriram Sankararaman, Antoine Rolland, David Reich, and Frederic Chalmel
    Meiotic genes are enriched in regions of reduced archaic ancestry
    Molecular Biology and Evolution (2017) [PDF]


  1. Sriram Sankararaman, Swapan Mallick, Nick Patterson, David Reich
    The combined landscape of Denisovan and Neanderthal ancestry in present-day humans
    Current Biology (2016) [PDF]

  2. Priya Moorjani, Sriram Sankararaman, Qiaomei Fu, Molly Przeworski, Nick Patterson, David Reich
    A genetic method for dating ancient genomes provides a direct estimate of human generation interval in the last 45,000 years
    Proceedings of the National Academy of Sciences (2016) [PDF]

  3. Farhad Hormozdiari, Martijn Van De Bunt, Ayellet Segre, Xiao Li, Jong Wha Joo, Michael Bilow, Jae Hoon Sul, Sriram Sankararaman, Bogdan Pasaniuc Eleazar Eskin
    Colocalization of GWAS and eQTL signals detects target genes
    The American Journal of Human Genetics (2016) [PDF]

  4. James Zou, Danny Park, Esteban Burchard, Dara Torgerson, Maria Pino-Yanes, Yun Song, Sriram Sankararaman\(^\dagger\), Eran Halperin\(^\dagger\), Noah Zaitlen\(^\dagger\)
    Genetic and socioeconomic study of mate choice in Latinos reveals novel assortment patterns
    Proceedings of the National Academy of Sciences (2016) [PDF]

  5. Swapan Mallick, Heng Li, Mark Lipson, et al.
    The Simons genome diversity project: 300 genomes from 142 diverse populations
    Nature (2016) [PDF]

Before 2016

  1. Mark Lipson, Po-Ru Loh, Sriram Sankararaman, Nick Patterson, Bonnie Berger, David Reich
    Calibrating the human mutation rate via ancestral recombination density in diploid genomes
    PLoS genetics (2015) [PDF]

  2. Fernando Racimo,Sriram Sankararaman, Rasmus Nielsen, Emilia Huerta-Sanchez
    Evidence for archaic adaptive introgression in humans
    Nature Reviews Genetics (2015) [PDF]

  3. James Zou, Eran Halperin, Esteban Burchard, Sriram Sankararaman
    Inferring parental genomic ancestries using pooled semi-Markov processes
    Bioinformatics (special issue of ISMB) (2015) [PDF]

  4. Pier Francesco Palamara, Laurent Francioli, et al.
    Leveraging distant relatedness to quantify human mutation and gene-conversion rates
    The American Journal of Human Genetics (2015) [PDF]

  5. Kay Prufer, Fernando Racimo, Nick Patterson, Flora Jay, Sriram Sankararaman, et al.
    The complete genome sequence of a Neanderthal from the Altai Mountains
    Nature (2014) [PDF]

  6. Sriram Sankararaman, Swapan Mallick, Michael Dannemann, Kay Prufer, Janet Kelso, Svante Paabo, Nick Patterson, David Reich
    The genomic landscape of Neanderthal ancestry in present-day humans
    Nature (2014) [PDF]

  7. The SIGMA Type 2 Diabetes Consortium
    Sequence variants in SLC16A11 are a common risk factor for type 2 diabetes in Mexico
    Nature (2014) [PDF]

  8. Noah Zaitlen, Bogdan Pasaniuc, Sriram Sankararaman, Gaurav Bhatia, et al.
    Leveraging population admixture to characterize the heritability of complex traits
    Nature Genetics (2014) [PDF]

  9. Bogdan Pasaniuc*, Sriram Sankararaman*, Dara Torgerson, et al.
    Analysis of Latino populations from GALA and MEC studies reveals genomic loci with biased local ancestry estimation
    Bioinformatics (2013) [PDF]

  10. Gaurav Bhatia, Nick Patterson, Sriram Sankararaman, Alkes Price
    Estimating and interpreting \(F_{ST}\): the impact of rare variants
    Genome Research (2013) [PDF]

  11. Alexandre Bouchard-Cote, Sriram Sankararaman, Michael Jordan
    Phylogenetic inference via sequential Monte Carlo
    Systematic biology (2012) [PDF]

  12. Sriram Sankararaman, Jay Chen, Lakshminarayanan Subramanian and Venugopalan Ramasubramanian
    TrickleDNS: Bootstrapping DNS security using social trust
    International Conference on Communication Systems and Networks (COMSNETS) (2012) [PDF]

  13. Yael Baran*, Bogdan Pasaniuc*, Sriram Sankararaman*, et al.
    Fast and accurate inference of local ancestry in Latino populations
    Bioinformatics (2012) [PDF]

  14. Sriram Sankararaman, Nick Patterson, Heng Li, Svante Paabo, David Reich
    The date of interbreeding between Neandertals and modern humans
    PLoS Genetics (2012) [PDF]

  15. Michael Turchin, Charleston Chiang, Cameron Palmer, Sriram Sankararaman, David Reich, Joel Hirschhorn, Genetic Investigation of ANthropometric Traits (GIANT) Consortium et al.
    Evidence of widespread selection on standing variation in Europe at height-associated SNPs
    Nature genetics (2012) [PDF]

  16. Sriram Sankararaman, Fei Sha, Jack F Kirsch, Michael I Jordan, Kimmen Sjolander
    Active site prediction using evolutionary and structural information
    Bioinformatics (2010) [PDF]

  17. Colin Hodgkinson, Mary-Anne Enoch, Vibhuti Srivastava, et al.
    Genome-wide association identifies candidate genes that influence the human electroencephalogram
    Proceedings of the National Academy of Sciences (2010) [PDF]

  18. Sriram Sankararaman*, Guillaume Obozinski*, Michael Jordan, Eran Halperin
    Genomic privacy and limits of individual detection in a pool
    Nature genetics (2009) [PDF]

  19. Bogdan Pasaniuc*, Sriram Sankararaman*, Gad Kimmel, Eran Halperin
    Inference of locus-specific ancestry in closely related populations
    Bioinformatics (special issue of ISMB) (2009) [PDF]

  20. Sriram Sankararaman, Bryan Kolaczkowski, Kimmen Sjolander
    INTREPID: a web server for prediction of functionally important residues by evolutionary analysis
    Nucleic acids research (2009) [PDF]

  21. Ron Alterovitz, Aaron Arvey, Sriram Sankararaman, Carolina Dallett, Yoav Freund, Kimmen Sjolander
    ResBoost: characterizing and predicting catalytic residues in enzymes
    BMC bioinformatics (2009) [PDF]

  22. Sriram Sankararaman*, Gad Kimmel*, Eran Halperin, Michael Jordan
    On the inference of ancestries in admixed populations
    Genome Research (2008) [PDF]
    Preliminary version in RECOMB (2008)

  23. Sriram Sankararaman, Srinath Sridhar, Gad Kimmel, Eran Halperin
    Estimating local ancestry in admixed populations
    The American Journal of Human Genetics (2008) [PDF]

  24. Sriram Sankararaman, Kimmen Sjolander
    INTREPID:INformation-theoretic TREe traversal for Protein functional site IDentification
    Bioinformatics (2008) [PDF]

  25. Christine F Skibola, et al.
    Polymorphisms in the estrogen receptor 1 and vitamin C and matrix metalloproteinase gene families are associated with susceptibility to lymphoma
    PloS one (2008)

  26. S Sriram, Tamma Bheemarjuna Reddy, BS Manoj, C Siva Ram Murthy
    The influence of QoS routing on the achievable capacity in TDMA-based ad hoc wireless networks
    Wireless Networks (2008) [PDF]

  27. Tyson Condie Varun, Varun Kacholia, Sriram Sankararaman, Joseph M Hellerstein, Petros Maniatis
    Induced churn as shelter from routing-table poisoning
    Network and Distributed System Security Symposium (NDSS) (2006) [PDF]

  28. T Bheemarjuna Reddy, S Sriram, BS Manoj, C Siva Ram Murthy
    MuSeQoR: Multi-path failure-tolerant security-aware QoS routing in Ad hoc wireless networks
    Computer Networks (2006)

  29. S Sriram, T Bheemarjuna Reddy, BS Manoj, C Siva Ram Murthy
    On the end-to-end call acceptance and the possibility of deterministic QoS guarantees in ad hoc wireless networks
    ACM International Symposium on Mobile ad hoc Networking and Computing (MobiHoc) (2005) [PDF]

  30. S Sriram, T Bheemarjuna Reddy, BS Manoj, C Siva Ram Murthy
    MuSeQoR: multi-path failure-tolerant security-aware QoS routing in ad hoc wireless networks
    International Conference on High-Performance Computing (2004)

  31. S Sriram, Tamma Bheemarjuna Reddy, BS Manoj, C Siva Ram Murthy
    The influence of QoS routing on the achievable capacity in TDMA-based ad hoc wireless networks
    IEEE Global Telecommunications Conference (GLOBECOM) (2004) [PDF]

  32. Sougata Mukherjea, L Venkata Subramaniam, Gaurav Chanda, Sriram Sankararaman, Ravi Kothari, Vishal Batra, Deo Bhardwaj, Biplav Srivastava
    Enhancing a biomedical information extraction system with dictionary mining and context disambiguation
    IBM Journal of Research and Development (2004)