Varuni Sarwal

I am a third year CS PhD student Zarlab, UCLA. Prior to this, I spent 4 wonderful years at the Indian Institute of Technology, Delhi (IIT Delhi) studying Biochemical Engineering and Biotechnology and Computer Science. During my undergrad, I was fortunate to have worked with Professor Frank Doyle (Harvard SEAS), Professor Eleazar Eskin (UCLA), and Professor Serghei Mangul (USC). I'm really excited about the making black box ML algos interpretable in the healthcare and genomics space! Seeing algos I've worked on help identify high risk patients, is something that really motivates me.

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• Jan 2023: Our work on TAMPA, a metagenomics tool for visualzing profiling outputs has been accepted at GigaScience
• December 2022: Thrilled to return to the Rocky Bioinformatics Conference to present new SVPred results
• October 2022: Excited to attent ASHG and present our new consensus SV caller, SVPred
• June-September, 2022
I will be working at Belvedere Trading as a Machine Learning Quant Research Intern. Excited to apply grad school ML models to the options market space
• March 2022: Our paper on benchmarking SV callers is (finally) published in Briefings in Bioinformatics!
• December 2021: Excited to present our work on benchmarking SV callers, and hitting the slopes at the Rocky Bioiformatics conference, Aspen CO
• October 2021: Our work on a network representation of COVID sequences has been accepted at the International Symposium on Bioinformatics Research and Applications!
• March 2021: Our paper on Unlocking capacities of viral genomics for the COVID-19 pandemic response is now on arXiv!
• October 2020: Excited to be giving a talk on benchmarking SV callers at at ABACBS2020!
• October 2020: Our work on eMST, a scalable and interpretable method for Phylogenetic analysis of hundreds and thousands of SARS-CoV-2 genomes, has been accepted for a talk at ABACBS2020!
• October 2020: Our work on the interpretable analysis and visualization of metagenomics-based taxon abundance profiles has been accepted for a talk at ABACBS2020!
• June 2020: Excited to be giving a talk on benchmarking SV callers at BOSC2020!
• April 2020: Our paper on benchmarking of SV callers is now on biorxiv!
• November 2019: Our abstract on insulin estimates in the APS system got accepted at ATTD!
• September 2019: Our paper on computational prediction of DNA replication is now on arXiv!
• June 2019: Our paper on the installability of omnics tools got published in PLOS Biology!
• May 2019: I will be visiting The Doyle Group, Harvard SEAS as an undergraduate summer researcher
• September 2018: I will be visiting INSA Toulouse, France as an international semester exchange student supported by the Charpak Scholarship
• August 2018: My poster on benchmarking structural variant callers wins best poster at BIG Summer, UCLA!
• July 2018: Thrilled to be a recipient of the Charpak Scholarship!
• May 2018: I will be visiting Zarlab, UCLA as an undergraduate summer researcher

I'm interested in the interdisciplinary areas of Computer Science, Biology and Statistics. I have worked on projects based on Computational Biology, Robotics, Machine Learning, Control Sytstems and Systems Biology in the past.

Identified optimal insulin measurement intervals for insulin sensor design by implementing a feedback-based threshold suspend safety-layer to supplement a zone model predictive control algorithm

Compared the performance of structural variant detection tools against a PCR verified set of deletions to determine tools with the best balance of sensitivity and precision

Estimated the archival stability of computational biology software tools by performing an empirical analysis of the internet presence for 36,702 omics software resources published from 2005 to 2017