Students & Research

Michael Klein - Zhao lab/ - Stern lab (entered Fall 2012)
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Michael’s current research focus is to understand the etiology of human cancers. Although much is known about individual oncogenes and how they contribute to cancer, very little is understood about how these individual oncogenes cooperate to cause malignancy. To this end Michael is developing computational approaches to infer the combinations of oncogenic events that are required for malignancy. He has also worked on developing GRAPE, a computational method for detecting abnormal pathway behavior from gene expression profiles. GRAPE is a template-based method and is robust to batch effects.

Cong Liang - Wagner lab (entered Fall 2012)
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Cong is investigating the phylogenetic tree-likeness in cell type evolution with their transcriptomic data. She is also interested in developing a model for cell type comparison with regulatory networks inferred from DNaseI footprints.

Ruijie Song - Acar lab (entered Fall 2012)

Ruijie’s research focuses on computational modeling of gene networks in yeast, generating predictions of network behavior to be experimentally tested by his fellow lab members. He is particularly interested in whether and how network dosage invariance affects other properties of the network.

Vincent Zhao - Zucker lab (entered Fall 2012)
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Vincent is interested in understanding both low-level and high-level nervous system structures and functions. We build statistical models to model data encoding and decoding and the network structures of the nervous system. Currently, our research is focused on studying the connections among high-order statistics, edge and curvature detection in visual system, and the underlying nervous system structure.

Jennifer Gaines - O'Hern lab (entered Fall 2013)
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Jennifer focuses on modeling protein structure using a hard sphere model of atomic interactions. Her current work focuses on understanding the RMSD changes found when the same protein is crystallized multiple times and to see how this compares to the change in structure found due to protein mutations.

Mengting Gu - Gerstein lab (entered Fall 2013)
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Mengting’s research involves processing next-generation sequencing data. She is interested in enhancer predictions and other functional annotations of the genome.

Alexandra Signoriello - O'Hern lab/ - Bosenburg lab (entered Fall 2013)
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Alexandra’s research seeks to understand how signaling and physical interactions between subsets of cancer stem cells regulate the function and spatiotemporal evolution of cancerous tumors. Her focus is on melanoma and other types of skin cancer.

Donghoon Lee - Gerstein lab (entered Fall 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 (entered Fall 2014)
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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.

Ryan Powles - Zhao lab/ - Pusztai lab (entered Fall 2014)
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Ryan applies network-level analysis tools and clonal evolution methods to sequencing data to characterize resistance in breast cancer to subtype-specific targeted therapies.

Jun Zhao - Kluger lab/ - Flavell lab (entered Fall 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.

Dingjue Ji - Zhao lab (entered Fall 2015)

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 - Krauthammer lab/ - Brandt lab (entered Fall 2015)
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Kevin works on image classification 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 (entered Fall 2015)
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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 - Krauthammer lab/ - Brandt Lab (entered Fall 2016)
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David is looking at large drug perturbation and gene expression datasets to explore efficient drug discovery methods that can improve the outcomes of immunotherapy treatments. The idea is to computationally characterize drugs by their capacity to modulate the neoepitope landscape of cancer cell lines, and to predict their effects on patient outcomes when used in conjunction with immunotherapy treatments.

Hussein Mohsen - Gerstein Lab (entered Fall 2016)
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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 (entered Fall 2016)
Jay Stanley - Krishnaswamy Lab (entered Fall 2016)

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

Jiawei Wang - Zhao Lab (entered Fall 2016)

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 (entered Fall 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 (entered Fall 2017)
Jeffrey Fisk (entered Fall 2017)
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Nick (Jeffrey) 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 (entered Fall 2017)

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 (entered Fall 2017)
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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 (entered Fall 2017)
Tianxiao Li (entered Fall 2017)
Wei Liu (entered Fall 2017)
Rihao Qu (entered Fall 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 (entered Fall 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 (entered Fall 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.