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layout: about title: About permalink: / subtitle: Assistant Professor, Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School.
profile: align: right image: prof_pic.jpg image_circular: true # crops the image to make it circular more_info: > <p>368 Plantation Street, AS4-1063</p> <p>Worcester, MA 01605-2324, USA</p>
news: true # includes a list of news items selected_papers: false # includes a list of papers marked as “selected={true}” social: true # includes social icons at the bottom of the page —
Causes, genes, and networks
My research focuses on causal gene regulatory networks (cGRNs), particularly the computational methods and statistical models to infer and analyze them. Some of my studies ask what is causation to develop new models and inference methods. My other studies apply new and traditional methods to infer causal gene regulatory networks from high-throughput sequencing data, particularly single-cell multiomics. I like to first think gene regulatory network inference as a generic causal inference question and then apply domain-specific techniques and optimizations to the particular context and data type.
You can find our current and past research in the Projects tab.
I am looking for research assistants, graduate (Ph.D.) students, postdocs, and visiting researchers that are motivated and interested in cGRNs. Please send me an email to introduce yourself and attach your CV.
555 your office number
123 your address street
Your City, State 12345
layout: about title: About permalink: / subtitle: Assistant Professor, Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School.
profile: align: right image: prof_pic.jpg image_circular: true # crops the image to make it circular more_info: > <p>368 Plantation Street, AS4-1063</p> <p>Worcester, MA 01605-2324, USA</p>
news: true # includes a list of news items selected_papers: false # includes a list of papers marked as “selected={true}” social: true # includes social icons at the bottom of the page —
Causes, genes, and networks
My research focuses on causal gene regulatory networks (cGRNs), particularly the computational methods and statistical models to infer and analyze them. Some of my studies ask what is causation to develop new models and inference methods. My other studies apply new and traditional methods to infer causal gene regulatory networks from high-throughput sequencing data, particularly single-cell multiomics. I like to first think gene regulatory network inference as a generic causal inference question and then apply domain-specific techniques and optimizations to the particular context and data type.
You can find our current and past research in the Projects tab.
I am looking for research assistants, graduate (Ph.D.) students, postdocs, and visiting researchers that are motivated and interested in cGRNs. Please send me an email to introduce yourself and attach your CV.