E-mail: firstname dot lastname at gmail dot com
I am a research scientist at Facebook working on experimentation methodology and machine learning for News Feed. Before that, I was a postdoctoral researcher at Stanford University and HHMI working with Jonathan Pritchard
on statistical models and inference algorithms for genomics applications.
Prior to that, I was a JSPS postdoctoral fellow
graciously hosted by Hideki Innan
at the Graduate University for Advanced Studies
in Hayama, Japan, and a Simons-Berkeley research fellow in the semester-long program on Evolutionary Biology and the Theory of Computing
at the Simons Institute for the Theory of Computing.
I received my PhD in Computer Science at the University of California, Berkeley where I worked with Yun S. Song
on mathematical genetics.
Before that, I received my B.S. and M.Eng. degrees in Computer Science from Cornell University, and an M.A. in Statistics from Berkeley.
I also spent two wonderful years in boarding school
while studying in the 11th
grades in Raffles Junior College
I develop and apply techniques from statistics, computer science, and applied mathematics to problems in experimentation methodology and ML model interpretability. I am particularly interested in experiment design for measuring network effects.
In my graduate and postdoctoral research, I have built statistical models and inference methods that utilize large-scale genomic datasets to address fundamental scientific questions such as the genetic basis of disease, human demographic history, and forensic genetics, among others. My work has involved developing analysis methods using techniques from statistics, applied mathematics, and computer science, and developing software that can be applied to genomic datasets for scientific discovery.
Geometry of the sample frequency spectrum and the perils of demographic inference
Rosen Z.*, Bhaskar A.*, Roch S., Song Y.S.
Genetics, 210(2):665–682, 2018
Inferring relevant cell types for complex traits by using single-cell gene expression
Calderon D., Bhaskar A., et al.
The American Journal of Human Genetics 101.5:686–699, 2017
Novel probabilistic models of spatial genetic ancestry with applications to stratification correction in genome-wide association studies
Bhaskar A.*, Javanmard A.*, Courtade T.A., Tse D.
Bioinformatics, btw720, 2016
Mutation rate variation is a primary determinant of the distribution of allele frequencies in humans
Harpak A.*, Bhaskar A.*, Pritchard J.
PLoS Genetics, 12(12):e1006489, 2016
Efficient inference of population size histories and locus-specific mutation rates from large-sample genomic variation data
Bhaskar A., Wang Y.X.R., Song Y.S.
Genome Research, 25(2):268–279, 2015
Descartes' rule of signs and the identifiability of population demographic models from genomic variation data
Bhaskar A. and Song Y.S.
Annals of Statistics, 42(6):2469–2493, 2014
A novel spectral method for inferring general selection from time series genetic data
Steinrücken M.*, Bhaskar A.*, Song Y.S.
Annals of Applied Statistics, 8(4):2203–2222, 2014
Distortion of genealogical properties when the sample is very large
Bhaskar A., Clark A.G., Song Y.S.
PNAS, 111(6):2385–2390, 2014
Approximate sampling formulas for general finite-alleles models of mutation
Bhaskar A., Kamm J.A., Song Y.S.
Advances in Applied Probability, 44:408–428, 2012
Closed-form asymptotic sampling distributions under the coalescent with recombination for an arbitrary number of loci
Bhaskar A. and Song Y.S.
Advances in Applied Probability, 44:391–407, 2012
Confidently estimating the number of DNA Replication Origins
Bhaskar A. and Keich U.
Statistical Applications in Genetics and Molecular Biology, Vol. 9: Iss. 1, Article 28, 2010
A comprehensive genome-wide map of Autonomously Replicating Sequences in a naive genome
Liachko I., Bhaskar A., Li C., Chung S.C.C., Tye B.K., Keich U.
PLoS Genetics, 6(5):e1000946, 2010
Computational detection of significant variation in binding affinity across two sets of sequences with application to the analysis of replication origins in yeast
Keich U., Gao H., Garretson JS., Bhaskar A., Liachko I., Donato J., Tye B.
BMC Bioinformatics, 9:372, 2008
Conference Publications and Technical Reports
A model and framework for reliable build systems
Coetzee D., Bhaskar A., Necula G.
EECS Department, University of California, Berkeley, Technical Report No. UCB/EECS-2012-27, 2012
Multi-locus match probability in a finite population: A fundamental difference between the Moran and Wright-Fisher models
Bhaskar A. and Song Y.S.
Proceedings of ISMB 2009.
Also published in Bioinformatics, 25(12):i187–i195, 2009
Efficient keyword search over virtual XML views
Shao F., Guo L., Botev C., Bhaskar A., Chettiar M., Yang F., Shanmugasundaram J.
VLDB Conference, 2007
Also invited for publication in the VLDB Journal, 2009.
Quark: An efficient XQuery full-text implementation
Bhaskar A., Botev C., Muthaia Chettiar M., Guo L., Shanmugasundaram J., Shao F.,Yang F.
ACM SIGMOD Conference, 2006
Statistical, algorithmic, and robustness aspects of population demographic inference from genomic variation data
Ph.D. dissertation. Computer Science, UC Berkeley, 2013
Approximate sampling formulas under the coalescent with finite-alleles models of mutation
M.A. thesis. Statistics, UC Berkeley, 2012
Quantum reading group Fall '09
, Spring '10