Current Students & Alumni

Current Students

Beulah Agyemang-Barimah (Mezey) My research is currently centered around human genetics. I use programming languages (mainly R) to write algorithms and code simulations of phylogenetic trees. The point of this research is to estimate the probability of observing the data present and track specific alleles backward in time.

Siddharth Avadhanam (Williams) Interested in developing probabilistic models and inference techniques to better understand human genetic variation and demographic history, and to build faster and more accurate tools for annotating genome data. Currently working on building software tools to address ancestry inference problems.

Ian Caldas (Clark/Messer) Interested in applying computational methods, statistics and machine learning to questions about the evolutionary history of populations and species.

Justin Cha (Rotating)

Sam Champer (Messer) I am working to create high fidelity gene-drive models and am interested in exploring the dynamics of large-scale populations modeled in realistic spaces. I am also interested in augmenting realistic population models with machine-learning meta-models to allow for in-depth assessments of computationally complex models. Vrushali Fangal (rotating)  

Ben Fehr (Buckler)

Taylor Ferebee (Buckler) Interested in both using principles of data fusion, statistical learning theory, and network science to develop cross-tissue, cross-genera, and cross-species methods for modelling transcriptional regulation in the Andropogoneae tribe of grasses, and in exploring biologically-informed priors for utilization in interpretable machine learning models.

Shagun Gupta (Yu) Interested in using statistical and computational methods that leverage data generated from mass spectrometers to gain insight into protein-protein interaction networks.  

Adam He (Danko) My current research focuses on identifying how ba­sic transcriptional processes such as initiation, pausing, and stability are encoded in the genetic sequences of transcriptional regulatory elements (TREs). At present, I am working on developing interpretable models that predict how TRE sequence impacts proximal transcription initiation.

Isabel Kim (Messer) 

Olivia Lang (Pugh)  I build tools for analyzing large genomics datasets and study the relationship between DNA organization and gene expression. More specifically, I investigate the mechanisms of transcription initiation around transcription start sites to develop models for global patterns of gene regulation.

Ian Lee (Rotating)

Yilin Liu (Rotating)

Madhav Mantri (De Vlaminck) Interested in developing computational methods for analysis of single cell transcriptomics data, particularly to understand biological processes like development, immunity, infection, and injury at a single cell resolution.

Nathan Oakes (Messer) Characterizing the dynamics of rapid evolution in complex demographics.

Runxi Shen (Messer) Runxi's research focuses on investigating the pesticide resistance alleles in mosquitoes through a novel method called bulk segregant analysis and building up computational and mathematical models for exploring population genetics.

 Parker Singleton (Kuceyski) Interested in studying the effects of pharmacology and disease on human brain activity/connectivity in order to inform theories of the brain and to better understand, diagnose and treat mental disorders. 

Michael Wang (De Vlaminck) To better understand immune cell dynamics and viral infections through the development of high throughput single cell sequencing technologies and analysis. Shayne Wierbowski (Yu) Interested in studying protein networks, including protein-protein interactions, the structural features relevant to protein interactions, and their functional implications. Particular interest in determining the functional role gene-fusion events in cancer play in re-wiring protein networks.

Weilin Xu (Gu) Interested in studying the genetics of mitochondrial DNA in the context of human diseases with the development of high-throughput sequencing approaches as well as the application of computational and statistical methods.

Hao Xue (Rotating)

Li Yao (Yu) Using statistical and machine learning techniques to study mechanisms of transcription regulation from biological datasets, such as run-on sequencing. Junke Zhang (Yu) Interested in using computational and statistical methods to study protein functions and protein-protein interactions in human diseases. Currently working on questions about gene fusions in cancer.   

Manqi Zhou (Rotating)


Daniel Seidman (Williams) Developing a computational method that finds and gives statistical confidence to IBD segments by comparing their probabilities under an IBD vs nonIBD model using a compressed reference genome set.

Recent Student Publications

  • Meyer, M. J., Beltrán, J. F., Liang, S., Fragoza, R., Rumack, A., Liang, J., ... & Yu, H. (2018). Interactome INSIDER: a structural interactome browser for genomic studies. Nature methods15(2), 107.
  • Wierbowski, S. D., Fragoza, R., Liang, S., & Yu, H. (2018). Extracting Complementary Insights from Molecular Phenotypes for Prioritization of Disease-Associated Mutations. Current Opinion in Systems Biology.
  • Duneau D., Sun H., Revah J., San Miguel K., Kunerth H.D., Caldas I.V., Messer P.W., Scott J.G., and Buchon, N. (2018). Signatures of Insecticide Selection in the Genome of Drosophila melanogaster. G3: Genes, Genomes, Genetics, Early online September 6, 2018.
  • Wei K.H.-C., Lower S.E., Caldas I.V., Sless T.J., Barbash D.A., and Clark, A.G. (2018). Variable Rates of Simple Satellite Gains across the Drosophila Phylogeny. Molecular Biology and Evolution, 35(4) pp. 925-941.
  • Jackson Champer, Jingxian Liu, Suh Yeon Oh, Riona Reeves, Anisha Luthra, Nathan Oakes, Andrew G. Clark, and Philipp W. Messer (2018). Reducing resistance allele formation in CRISPR gene drive. Proceedings of the National Academy of Sciences (PNAS).
  • Tinyi Chu, Edward J. Rice, Gregory T. Booth, H. Hans Salamanca, hong Wang, Leighton J. Core, Sharon L. Longo, Robert J. Corona, Lawrence S. Chin, John T. Lis, Hojoong Kwak, Charles G. Danko, Chromatin run-on and sequencing maps the transcriptional regulatory landscape of glioblastoma multiforme, Nature Genetics (2018).
  • Jacob M. Tome, Nathaniel D. Tippens, John T. Lis, Single-Molecule nascent RNA sequencing identifies regulatory domain architecture at promoters and enhancers, Nature Genetics (2018).
  • Saikia, M., Burnham, P., Keshavjee, S. H., Wang, M. F. Z., Heyang, M., Moral-Lopez, P., Hinchman, M. M., Danko, C. G., Parker, J. S. L. and De Vlaminck, I. (2018). Simultaneous multiplexed amplicon sequencing and transcriptome profiling in single cells. Nature Methods. doi: 10.1038/s41592-018-0259-9, Nature (2018)
  • Borthakur, Ayon, Cleland, Thomas A., A Spike Time-Dependent Online Learning Algorithm Derived From Biological Olfaction, Frontiers in Neuroscience, 2019
  • Borthakur, Ayon, Cleland, Thomas A., Signal Conditioning for Learning in the Wild, DL Association for Computing Machinery, 2019


  • Siqi (Charles) Liang, PhD Computational Biology, Spring 2021
    Advisor: Haiyuan Yu
  • Paul Munn, PhD Computational Biology, Fall 2020
    Advisor: Charles Danko
  • Manisha Munasinghe, PhD Computational Biology, Fall 2020
    Advisor: Andrew Clark
  • Konnor La, PhD Computational Biology & Medicine, Fall 2020
    Advisor: Andrew Clark
  • Afrah Shafquat, PhD Computational Biology, Fall 2020
    Advisor: Jason Mezey|Weill Cornell Medical College
  • Juan Beltran, PhD Computational Biology, Fall 2020
    Advisor: Ilana Brito|Postdoc Brito Lab
  • Melissa Hubisz, PhD Computational Biology, Fall 2019
    Advisor: Adam Siepel/Amy Williams|Program Analyst, Cornell University
  • Tinyi Chu, PhD Computational Biology, Fall 2019
    Advisor: Charles Danko
  • Yiping Wang, PhD Computational Biology, Fall 2019
    Advisor: Zhenglong Gu|Postdoc, Columbia University
  • Lenore Pipes, PhD Computational Biology & Medicine, August 2017,
    Advisor: Adam Siepel/Chris Mason|Postdoctoral Scholar, University of California-Berkeley
  • Nicholas Cheney, PhD Computational Biology, August 2017,
    Advisor: Steven Strogatz/Hod Lipson|Research Assistant Professor, University of Vermont
  • Kelson Zawack, PhD Computational Biology & Medicine, May 2017,
    Advisors: James Booth/Yrjo Grohn|Postdoctoral Fellow, Yale University
  • Monica Ramstetter, PhD Computational Biology, May 2017,
    Advisor: Jason Mezey|Sr. Scientist, Pfizer
  • Feng Gao, PhD Computational Biology, January 2017,
    Advisor: Alon Keinan|Data Scientist
  • Lei Huang, PhD Computational Biology, January 2017,
    Advisor: Chris Myers|Bioinformatics Scientist, Human Longevity, Inc.
  • Michael Meyer, PhD Computational Biology & Medicine, January 2017,
    Advisor: Haiyuan Yu|Senior Scientist, 4Catalyzer
  • Jishnu Das, PhD Computational Biology, August 2016,
    Advisor: Haiyuan Yu|Postdoctoral Associate, MIT/Ragon Institute of MGH
  • Katherine Wilkins, PhD Computational Biology, August 2016,
    Advisor: Adam Bogdanove|Sr. Computational Biologist, Agilent Technologies, Santa Clara
  • Jaaved Mohammed, PhD Computational Biology & Medicine, May 2016,
    Advisors: Adam Siepel/Eric Lai|Postdoctoral Research Fellow, Stanford University
  • Eyal Nitzany, PhD Computational Biology & Medicine, August 2015,
    Advisor: Shimon Edelman|Postdoctoral Researcher, University of Chicago
  • Brandon Barker, PhD Computational Biology & Medicine, August 2014,
    Advisor: Zhenglong Gu|Computational Scientist, Cornell Center for Advanced Computing
  • Diana Chang, PhD Computational Biology & Medicine, August 2014,
    Advisor: Alon Keinan,|Scientist, Genentech, San Francisco
  • Haley Hunter-Zinck, PhD Computational Biology & Medicine, August 2014,
    Advisor: Andy Clark|Health Science Specialist, VA Boston Healthcare System
  • Andre Martins, PhD Computational Biology, August 2014,
    Advisor: Adam Siepel|Sr. Software Development Engineer, Hitachi Vantara
  • Theodore Cornforth, PhD Computational Biology & Medicine, January 2014,
    Advisor: Hod Lipson
  • Chuan Gao, PhD Computational Biology, May 2012,
    Advisor: Jason Mezey|Senior Scientist, Parexel International Corp.
  • Benjamin Logsdon, PhD Computational Biology, January 2011,
    Advisor: Jason Mezey|Director, University of Washington, Brain & Memory Wellness Center
  • Michael Schmidt, PhD Computational Biology, January 2011,
    Advisor: Hod Lipson, Chief Scientist, DataRobot
  • Jeremiah Degenhardt, PhD Computational Biology, May 2010,
    Advisor: Carlos Bustamante|Sr. Director, Translational Oncology & Bioinformatics/Maverick Therapeutics
  • Lin Li, PhD Computational Biology, May 2010,
    Advisor: Carlos Bustamante|Director of Biostatistics & Scientific Operations, Biostat Solutions, Inc
  • Mark Albert, PhD Computational Biology, January 2010,
    Advisor: David Field|Assistant Professor of Computer Science, Loyola University