Current Students

Donghoon Lee - Gerstein lab (2014)
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Donghoon’s research has primarily focused on cancer genomics. He works on developing computational methods that integrate genomic, transcriptomic, and epigenomic signals from various next-generation functional sequencing assays. Using a comprehensive set of functional elements and an accurate regulatory network, he works on interpreting non-coding mutations and gene regulation. In particular, he is interested in studying the roles of epigenetics and chromatin structure on transcriptional and splicing regulation in cancer. Using integrative approach, he plans to decipher the hidden messages buried within the epigenetic landscape.

Xiaotong Li - Gerstein lab & Pusztai lab (2014) | ORCID: 0000-0003-1644-6835
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Xiaotong is interested in next-generation sequencing data analysis, with a major focus on breast cancer. Currently she is working on whole genome sequencing analysis on inflammatory breast cancer, and heterogeneity analysis.

 
Jun Zhao - Kluger lab & Flavell lab (2014)
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Jun’s research focuses on the analysis of high-throughput sequencing data, RNA-seq, CRISPR, CLIP-Seq, etc. The goal is to help understand the genetic mechanisms of immune-related biological processes.

 
Daniel Chawla - Kleinstein lab (2015)
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Dingjue Ji - Zhao lab (2015) | ORCID: 0000-0001-6288-8891

Frank is working on spatio-temporal transcriptomic data of brain. He is interested in developing new methods to identify the expression pattern of specific genes related to brain development. The new approaches are expected to help to understand the mechanisms of brain diseases like ASD.

Kevin Lopez - Brandt lab (2015)
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Kevin Lopez works on multi model learning using deep learning and convolutional neural networks. He is also working on expanding the capabilities of Yale Image Finder by applying deep learning methods to classify images from PubMed publications.

Quan Zhou - Kleinstein lab (2015) | ORCID: 0000-0001-9602-2092
Quan Zhou's picture

Julian works with high-throughput adaptive immune receptor repertoire sequencing (AIRR-seq) data, especially in the context of B cell-mediated autoimmune diseases. He is interested in developing novel methods for inferring B cell lineages that help shed light on their developmental pathways.

David Chang - Brandt lab & Zhao lab (2016)
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David Chang is studying recent advances in deep learning and NLP to enable effective integration of multiple EHR data modalities to improve information extraction

Hussein Mohsen - Gerstein lab (2016) | ORCID: 0000-0002-6263-8865
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Hussein’s main research interests are machine learning and cancer genomics. He is working on projects that leverage genomics big data to explore variation patterns in cancer. In particular, he is interested in developing machine and deep learning methods that study the underlying interaction between somatic and germline genetic variations in pan-cancer tumor types.

Nir Neumark - Kaminski lab & Coifman lab (2016) | ORCID: 0000-0002-5560-6136
Jay Stanley - Krishnaswamy lab (2016)

Jay studies learned representations of biological data, in particular graph representations and their processing.

Jiawei Wang - Zhao lab (2016) | ORCID: 0000-0003-2627-4897

Jiawei’s research interest lies in imaging genetics and mental diseases. He is working on gene expression analysis to help discover the etiology of PTSD and graphical models to study brain functional and structural network. 

Zhaolong Yu - Zhao lab (2016)
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Zhaolong’s current research focus is patient outcomes prediction based on multi-omics data. He is particularly interested in developing machine learning algorithms to better predict cancer patient outcomes.

Evan Cudone - McDougal lab (2017) | ORCID: 0000-0002-1055-1645
Jeffrey Fisk - Townsend Lab (2017) | ORCID: 0000-0002-1940-393X
Jeffrey Fisk's picture

Nick (Jeffrey) Fisk works on constructing phylogenetic trees to answer questions about cancer development, evolution, and the selective pressure treatment induces on the system. He also works on developing and implementing methods to optimize general phylogenetic experimental design.

Jiahao Gao - Gerstein lab (2017) | ORCID: 0000-0002-6311-3526

Jiahao focuses on the analysis of high throughput sequencing data, with special interest in ChIP-seq and other functional genomics technologies. He is currently working on denoising the ChIP-seq binding sites in order to improve the de novo inference of transcription factor binding motifs.

Scott Gigante - Krishnaswamy lab (2017) | ORCID: 0000-0002-4544-2764
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Scott’s research is focused the development of methods in deep learning and graph signal processing to understand the structure of single-cell genomics data, especially single-cell RNA sequencing data. He is particularly interested in how to make the most of many high-resolution noisy measurements, and how manifold learning techniques can facilitate this understanding.

Pranav Kantroo - Wagner lab & Machta lab (2017)
Tianxiao Li - Gerstein lab (2017) | ORCID: 0000-0002-9147-7511

Tianxiao is interested in applying novel machine learning techniques to inference of gene regulatory networks and 3D genomics. He is now working on developing novel methods to associate 3D genomics structures with gene regulatory elements.

Wei Liu - Zhao lab (2017) | ORCID: 0000-0003-2558-1377
Wei Liu's picture

Wei’s research is mainly focused on understanding genetic architecture and mechanisms of complex diseases. She is now working in developing statistical methods investigating disease-associated genes using multi-omics data including genetics, epigenetics and transcriptomics data. Wei is also interested in population genetics and causal inference.

Rihao Qu - Kluger lab & Flavell lab (2017)

Rihao’s research interests include high-throughput sequencing analysis and immunogenomics. He is working on developing computational and statistical methods to process high-dimensional single cell sequencing data and help understand the genetic mechanisms underlying immune pathways.

Yixuan Ye - Zhao lab (2017)
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Yixuan research focuses on the genetic risk prediction for chronic diseases and cancer. She is currently working on exploring the interaction between gene, lifestyle and diseases. She is also interested in developing new methods to improve genetic prediction accuracy and the interpretation of polygenic risk score. 

Geyu Zhou - Zhao lab (2017)

Geyu’s research interest is statistical genomics and genetics. He is experienced in gene expression data analysis. He is currently working on developing statistical methods to compute polygenic risk score.

Edel Aron - Kleinstein lab (2018)
Egbert Castro - Krishnaswamy lab (2018)
Guannan Gong - Krumholz lab (2018)
Alex Grigas - O'Hern lab (2018) | ORCID: 0000-0002-1588-2996
Jeff Mandell - Townsend lab (2018) | ORCID: 0000-0002-3839-2543
Kyra Thrush - Levine lab (2018) | ORCID: 0000-0002-3991-9597
Ana Berthel - (2019)
Jeremy Gygi - (2019)
Diana Leung - (2019)
Wes Lewis - (2019)
Yaroslav Markov - (2019) | ORCID: 0000-0001-8778-4909
Eric Ni - (2019) | ORCID: 0000-0002-4530-0707
Vimig Socrates - (2019) | ORCID: 0000-0001-7955-9875
Andrea Tamminga - (2019)
Aarthi Venkat - (2019) | ORCID: 0000-0003-0298-0172
Mamie Wang - (2019) | ORCID: 0000-0002-3453-7805
Junchen Yang - (2019)
Maryam Zekavat - (2019)
Biqing Zhu - (2019)