People
Vagheesh M. Narasimhan (vagheesh@utexas.edu)
Principal Investigator
Vagheesh Narasimhan is an Assistant Professor in the Departments of Integrative Biology, Statistics and Data Science, as well as Population Health at The University of Texas at Austin. He received his Ph.D. in Mathematical Genomics and Medicine from the University of Cambridge and the Wellcome Trust Sanger Institute and later completed a post-doctoral research fellowship at the Department of Genetics, Harvard Medical School with David Reich and Nick Patterson.
Emily Javan (emjavan@utexas.edu)
PhD Student (primarily advised by Dr. Lauren Ancel Meyers)
Emily Javan is a PhD student in Evolution, Ecology, and Behavior and part of the UT COVID-19 Modeling Consortium. She is currently working to identify recessive variants in the human genome associated with disease using exome sequencing and electronic health record data, but broadly interested in how diseases spread and manifest from genetic and environmental factors. She received her BS in Applied Mathematics from UC Davis with a minor in Evolution, Ecology, and Biodiversity and her MS in Population and Conservation Biology from Texas State University.
Eucharist Kun (eucharistkun@utexas.edu)
PhD Student
Eucharist Kun is a PhD student in the Biochemistry graduate program. He received his Bachelor's of Science in Biochemistry from the University of Texas at Austin. Prior to returning to the University of Texas at Austin for the Biochemistry graduate program, he worked at MD Anderson in the Gynecology Oncology and Reproductive Medicine Department focusing on Low Grade Serous Ovarian Cancer. Eucharist is currently working on developing machine learning methods to improve medical imaging diagnostics.
Devansh Pandey (devanshpandeyiitkgp@gmail.com)
PhD Student
Devansh Pandey is a PhD in the Cell and Molecular Biology graduate program at UT Austin. He has a BTech-MTech dual degree student from the Indian Institute of Technology Kharagpur majoring in Biotechnology and Biochemical engineering. He is currently working on deep learning methods for genomic sequence datasets.
Michael Schwab (schwob@utexas.edu)
PhD Student (primarily advised by Mevin Hooten)
Michael Schwob is a PhD student in the Department of Statistics and Data Sciences. He received his Bachelor of Science in Mathematical Sciences at the University of Nevada, Las Vegas. He is currently developing statistical methodology that explores ancient human population dynamics through space and time. His research is funded by a NSF Graduate Research Fellowship.
Olivia Smith (osmith@utexas.edu)
PhD Student
Olivia Smith is a PhD student in the Cell and Molecular Biology graduate program (Bioinformatics and Computational Biology track) on an NSF Graduate Research Fellowship. She received her Bachelor of Science in Biochemistry and Biomedical Engineering (Honors) at Colorado State University. Prior to joining the lab she worked at Ginkgo Bioworks and Joyn Bio developing their next generation sequencing analysis platforms. She is currently working on developing methods for analysis of DNA methylation information from ancient DNA
Joyce Wang (joyce.wang@utexas.edu)
PhD Student
Joyce Wang is a PhD student in the Cell and Molecular Biology graduate program (Bioinformatics and Computational Biology track). She received her Bachelor of Science in (Computational) Biology at UT Austin. Prior to joining the lab she worked in the labs of Becca Young and Hans Hoffman.
Megan Le (meganle@utexas.edu)
Masters Student
Megan Le is an integrated BS/MS student double majoring Computer Science and Mathematics at The University of Texas at Austin and is a Teaching Assistant for Principles of Computer Systems (CS 439). She is a recipient of the TIDES Summer Research Fellowship and an Endowed Presidential Fellowship. She is working on understanding natural selection in humans from time series data of ancient DNA.
Alaukik Gupta is an undergraduate majoring in Biomedical Engineering at the University of Texas at Austin. Outside of the lab, he is involved in Texas Engineering World Health (TEWH) as an officer and team lead. Currently, he is working with computer vision to develop an algorithm that can detect Leukemia (ALL) in blood cells. Alaukik is also interested in applying machine learning to genetic editing in the medical field and utilizing ancient DNA to map the spread of hereditary disease.
Alumni
Annie Zhou (azhou@utexas.edu)
PhD Student (primarily advised by Dr. Andrew Dunn)
Annie Zhou was a PhD student in Biomedical Engineering with a focus in optical imaging. She completed her BS in Biomedical Engineering at the University of California, Davis. Her work in the lab focused on deep learning to develop novel algorithmic approaches for increasing two-photon scanning speeds for in vivo neuro-vasculature studies. She is now at Verily Life Sciences as a Research Scientist
