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Current Students

COMPUTATIONAL BIOLOGY

RESEARCH FOCUS
Beulah Agyemang-Barimah 1st Year - Rotating
Siddharth Avadhanam (Williams)  
Juan Beltran (tbd) Interested in reapplications of machine learning algorithms in cross-domain or sparse environments, particularly towards a better understanding of functional genomics.
Ayon Borthakur (Cleland) Developing neuroscience inspired low power embedded processor algorithms for solving artificial intelligence tasks such as in chemosensory systems and healthcare
Ian Caldas (Clark/Messer) Interested in applying computational methods, statistics and machine learning to questions about the evolutionary history of populations and species.
Tinyi Chu (Danko) Developing Bioinformatics tools and addressing biological questions using state of-art machine learning and statistical learning algorithms.
Shagun Gupta 1st Year - Rotating
Adam He (tbd)  

Melissa Hubisz
(Williams/
Siepel)

Using ancestral recombination graphs for inference in population genetics, especially demographic reconstruction of human populations.
Olivia Lang (Brito)  
Charles Liang
(Yu)
Discovering trends and patterns in biological datasets, such as protein network disruption datasets and drug-drug interaction datasets, with statistical methods and machine learning tools.
Madhav Mantri 1st Year - Rotating
Manisha Munasinghe (Clark)

Interested in constructing models to examine the underlying population genetics of genetic conflict, particularly as it applies to mitochondrial-nuclear interactions, sexual antagonism, and the evolution of sex chromosomes. 

Paul Munn
(Danko)

Interested in both developing machine learning techniques to aid in the identification of transcription unit boundaries, and in improving our understanding of chromatin structure and how it affects gene regulation.
Nathan Oakes (Messer)

Characterizing the dynamics of rapid evolution in complex demographics.

Ying Qiao (Williams) Developing statistical and computational methods to understand the relationship of DNA replication timing and mutational landscape of the genome.

Afrah Shafquat (Mezey)

Developing statistical and computational methods to identify biomarkers associated with complex phenotypes.
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. 

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.

Li Yao 1st Year - Rotating
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. 

TRI-I COMPUTATIONAL BIOLOGY & MEDICINE RESEARCH FOCUS
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.

Nathaniel Tippens (Yu/Lis)

Developing an experimental technique to map all protein-DNA interactions in accessible regions of the genome. I am interested in applying this and other genomic techniques to study the transcriptional mechanisms that specify cellular identity.

Yiping Wang (Gu) Developing a new constraint-based computational method called FALCON, to predict metabolic flux distributions using gene expression.