Amy L. Williams
Dept. of Biological Statistics and Computational Biology
Nancy and Peter Meinig Family Investigator in Life Science and Technology
Amy holds Ph.D. and S.M. degrees in computer science from Massachusetts Institute of Technology, and dual B.S. degrees in computer science and mathematics from the University of Utah.
CV available here. Email: awilliams at cornell.edu.
Ramya’s work focuses on using genetic data to infer relationships between individuals and on efficient pedigree reconstruction. She received a B.S. in Bioengineering from the University of Illinois, Urbana-Champaign and intends to pursue her education further upon graduation from Cornell. Outside of research, her hobbies include reading and cross-stitching.
Co-advised with Adam Siepel
Melissa is generally interested in uncovering the forces which shaped the evolution of species and populations. Her dissertation work involves using the ancestral recombination graph to infer demographic histories and identify regions of the genome under different types of natural selection. She has a B.S. in engineering from Caltech and an M.S. in human genetics from the University of Chicago.
Ying is interested in developing and applying statistical and machine learning methods to analyze genetic data and explore biological problems, and is currently working on inferring relationship types within population genetic sample data. She received her B.S. degree in in Applied Mathematics from Zhejiang University in China.
Monica is interested in creating and applying statistical and machine learning methods that will allow us to infer otherwise unknown relationships between individuals. This is necessary for finding links between the genome and phenotypes via association studies, another interest of hers. She has a B.S. in applied mathematics, a B.A. in quantitative economics from UC Irvine, and recently completed her Ph.D. in computational biology at Cornell.
Jens has an interest in studying evolution and genetics at the population scale. He is currently performing analyses of the factors influencing the location of crossovers and non-crossovers. He received his Sc.B. in Applied Mathematics and Biology from Brown University. Outside of the lab, Jens enjoys reading indiscriminately and most sorts of puzzle solving.
Daniel N. Seidman
Daniel focuses on algorithmic design and implementation for analysis of genetic data, predominantly identical by descent segments. He received a B.S. in computational biology from Brown University, and intends to continue in academia when he completes his Ph.D. He loves marine biology, a leftover passion from a former intended career path.
Sayantani was a postdoctoral associate in the lab from Feb 2015-Jan 2017 and worked on a method for inferring the parnet-of-origin of haplotypes using data from a set of siblings. She received her Ph.D. in Biology from the University of Paris-SUD XI in Orsay, France and is currently a postdoctoral fellow at the University of California San Francisco.
Arjun graduated from Cornell University with a B.S. in Computer Science in 2015. He was an undergraduate researcher and worked on comparing methods for detecting identity by descent segments. He is currently a PhD student in Human Genetics at the University of Chicago.
Ryan graduated from Cornell University with a M.Eng. in Computer Science. He was a research assistant in the lab from August 2015-December 2016 and worked on a method for inferring pedigree relationships using large genotype datasets. He is currently a PhD student in Electrical Engineering at Cornell.