DEVISHI KESAR

● 404-***-**** adgme2@r.postjobfree.com https://www.linkedin.com/in/dkesar/

SKILLS

Programming Languages: Python, R, Bash, C, Java, SQL, MATLAB Software: Cytoscape, Hadoop, Spark, Hive, Docker, Git, Git- SVN, RStudio, GeneData Profiler, PyMol Bioinformatics Tools: Rshiny,Rmarkdown,BWA, GATK,VarScan,Samtools,BayesDel,Picard,E-utils,SPAdes,fastp,PLINK Bioinformatics Databases: TCGA, MSigDB, UCSC Genome browser, gnomAD, dbSNP, ClinVar, dbNSFP, PharmGKB, HGMD WORK EXPERIENCE

Graduate Research Assistant, Jordan Lab, Georgia Institute of Technology Aug’20 - Present

● Generating comprehensive database of Colombian genome sequence variants, and associated clinical annotations

● Cataloging genomic variants from Colombian populations and characterising their predicted functional impact

● Identifying single variant disease associations using best practices from the American College of Medical Genetics

● Creating pharmacogenomic database for the Colombian populations Bioinformatics Summer Intern, EMD Serono Research & Development Institute May’20 - Jul’20

● Developed Rshiny app to share isolated immune cell RNAseq from bulk breast cancer tumors with biological experts

● Discovered novel myeloid drug targets by leveraging differential expression and gene signature analysis

● Drove bioinformatics discovery by frequently presenting results to key stakeholders across multiple departments

● Identified actionable biomarkers supporting therapeutic remediation of immuno-oncology and autoimmune disease Graduate Research Assistant, Jordan Lab, Georgia Institute of Technology Jan’20 - Apr’20

● Evaluated distribution of health-related genetic variants among populations from Colombia in light of their ancestry

● Benchmarked variant calling pipelines by comparison of performance of mappers and variant callers

● Performed SNP annotation for the dataset from the 3 populations using VICTOR pipeline Intern, NETS Lab - IIT Delhi, AIIMS Delhi May’19 - Jul’19

● Generated metrics for evaluation of sutures done by neurosurgeons at AIIMS Delhi

● Estimated suture quality by performing image segmentation and color thresholding followed by machine learning Teaching Assistant, IIIT Delhi Jan’18 - Apr’18

● Teaching assistant for introduction to quantitative biology course assisting 150 students Intern, IIT Madras May’17 - Jun’17

● Used Machine learning to predict drug synergies for different cancer affected cell line samples in DREAM challenge

● Learnt about supervised, semi-supervised, unsupervised machine learning and deep-learning algorithms EDUCATION

Georgia Institute of Technology, Atlanta, GA Aug’19 - Present Master’s in Bioinformatics CGPA: 3.87/4

Indraprastha Institute of Information Technology Delhi Aug’15 - Aug’19 Bachelor’s (Honors) in Computer Science and Engineering CGPA: 8.68/10 with minors in Computational Biology

PROJECTS

Predictive Web Server for E. coli isolates

● Designed an automated platform as part of genome assembly and web server team to analyse E. coli isolates

● Executed QC analysis and benchmarked de-novo assemblers to create a pipeline for genome assembly

● Created web server to execute computational genomics pipeline to predict outbreak cluster and virulence factors Epidemiological modelling of spread of COVID-19 in Germany and South Korea

● Implemented SEIRD and machine learning based models for epidemiological modelling of the spread of COVID-19

● Compared spread of COVID-19 in South Korea and Germany over time

● Provided phase adjusted estimation of spread helping determine effectiveness of public health interventions Exome Variant Analysis of 1000 Genomes Project Individual

● Implemented variant calling pipeline for whole exome sequence of International Genome Sample Resource sample

● Top clinically significant SNP’s obtained using ANNOVAR to visualise the change in the protein structure due to SNP Differential Gene Expression Analysis in lung cancer lines between wildtype and mutant p53 cell lines

● Performed quality control, trimming, sequence alignment and differential gene expression analysis for the cell lines

● Used HISAT2 for alignment, DESeq2 for differential expression and Reactfoam for pathway analysis Multiple Myeloma and Proteogenomics DREAM challenges

● Implemented disease progression based genomic variant predictor identifying high risk Multiple Myeloma patients

● Imputed missing data in breast cancer global proteomics data using random forests algorithm PUBLICATION

● Mason, M.J., Schinke, C., Eng, C.L.P. et al.Multiple Myeloma DREAM Challenge reveals epigenetic regulator PHF19 as marker of aggressive disease. Leukemia (2020). - member of DREAM consortium

● Yang, et al. “Assessment of the Limits of Predictability of Protein and Phosphorylation Levels in Cancer.” SSRN, 30 Mar. 2020, CELL-SYSTEMS, papers.ssrn.com/sol3/papers.cfm?abstract_id=3554086. - member of NCI-CPTAC-DREAM consortium

AWARDS

Graduate Research Assistantship Jul’20

Received GRA award for the term August 2020- November 2020 at the Jordan lab Graduate Research Assistantship Dec’19

Received GRA award for the term January 2020- April 2020 at the Jordan lab Dean Academic Excellence Award, 2017-18 Sep’18

Received Dean Academic Excellence Award for average SGPA more than 9 in AY 2017-18 RECOMB/ISCB Conference Travel Grant Nov’17

Received travel grant of 1500$ to attend 10th annual RECOMB/ISCB Conference CERTIFICATIONS

MIT COVID-19 Challenge Apr’20

Introduction to breast cancer, online course by Yale University Jun’19 Computer science and automation, Summer School IISc Bangalore Jul’18 User Experience Design, Winter School IIIT-Delhi Dec’17 Summer school in Bioinformatics NCBS Jun’17

Introduction to cancer, online course by Johns Hopkins University Jan’17

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