I’m incredibly fortunate to lead the Analytics and Informatics department at ShapeTX, engaged in novel computational biology and generative machine learning research to help define the future of programmable RNA technologies and therapeutics.

• Led BMS's CTPS group to develop analytical and statistical methods for analyzing and integrating large-scale next-generation sequencing, patient, manufacturing process, product phenotyping, and translational data to help Juno/Celgene/BMS create new, more effective, and safer cellular immunotherapies for cancer• Managed and worked together with exceptional PhD- and MS-level data scientists, statistical geneticists, and bioinformaticians to develop novel methods and integrative analysis strategies for high content, high-throughput cell and molecular profiling data sets (e.g. bulk and single cell RNA-seq, ATAC-seq, immune sequencing, vector integration mapping) and machine learning analyses in the cellular immunotherapy space• Directly involved in the BLA submission processes for the Breyanzi and Abecma CAR-T products by leading or engaging in respective correlative analyses teams and defining critical quality attributes and quality target product profiles• Enabled and drove cross-functional analyses with Research & Early Development, Cell Therapy Development Operations, and Global Biometrics Sciences colleagues, clinicians, and academic collaborators to generate predictive insights that advance CAR-T target discovery and process development• Represented Informatics & Predictive Sciences on cross-functional project and clinical teams to establish corporate strategies, objectives, and key decisions as a subject matter expert in statistical analyses, data integration, genomics, and functional characterization methodologies• Hybrid manager and individual contributor who can link the technical aspects of the day-to-day informatics tasks with the larger-scale goals of a biotech aiming to revolutionize the way cancer is treated

I led Celgene's CTPS group to develop analytical and statistical methods for analyzing and integrating large-scale next-generation sequencing, patient, manufacturing process, and product phenotyping data to help Juno/Celgene create new, more effective, and safer cellular immunotherapies for cancer.

I led Juno's Computational Genomics and Data Science team in Quantitative Sciences to develop methods for analyzing single cell immune repertoire sequencing data to enable Juno to identify novel binders for cellular immunotherapies as well as apply machine learning and computational biology approaches for patient and product biomarker discovery.

I worked with Jay Shendure in the University of Washington Department of Genome Sciences on developing new experimental and analytical methodologies to better understand, interpret, and predict the effects of genetic variants of uncertain significance on complex human phenotypes, such as cancer. Developed a classifier for calling and examining microsatellite instability in cancer and designed an algorithm for predicting mutational effects on protein structure and function, among other things.

Edit scientific publications from foreign, non-native English-speaking researchers to improve acceptance into American scientific journals and publications

• Acquire information regarding Japanese pharmaceuticals for hypertension, diabetes, and rheumatoid arthritis• Initiate and establish working relationships with Japanese physicians to gain critical data regarding the Japanese pharmacetical market• Provide leading pharmaceutical companies detailed reports aggregating gathered intelligence and evaluating opportunities in the market from both commercial and clinical perspectives

Genetics, Genomics and Systems BiologyLaboratory of Dr. Richard B. Jones, University of Chicago, Institute for Genomics and Systems Biology, Ben May Department for Cancer ResearchMy research involved utilizing a combination of genomics, systems-biochemical, and statistical approaches to (1) investigate the roles genetic variation play in regulating global mRNA and protein levels and chemotherapeutic drug responses in the HapMap Yoruba population and protein levels human cerebellum; (2) determine and predict protein recruitment profiles for receptor tyrosine kinases, nuclear receptors, and adapter proteins; and (3) characterize the kinetics of hormone- and growth factor-mediated protein signaling networks in cancers.

• Protein Post-Translational Modifications• Summer Link - Genomics and Systems Biology• Cancer Genomics and Systems Biology

Pharmacogenomics, Spring 2010:Served as teaching assistant for undergraduate students, graduate students, and clinical fellows; held weekly office hours; graded problem sets; helped design course schedule and took care of course logistics; recorded lecturesIntroduction to Probability and Statistics for Geneticists, Fall 2009:Served as teaching assistant for graduate students and post-doctoral fellows; solved weekly problem sets and wrote solutions in LaTeX; led weekly review sessions; held weekly office hours; graded problem sets and examsGenetics, Winter 2008:Served as teaching assistant for 117 undergraduate students; led weekly review sessions; held weekly office hours; gave a lecture on genome structure, genomic technologies, and gene regulatory networksHuman Genetics, Fall 2008:Mentored graduate students in writing faux NIH R01 grants throughout the term; assisted students with leading biweekly discussion sections and presenting on primary literature and their grants; graded grant proposals and problem sets

Plant Development/Molecular Genetics Research, Dr. Jocelyn Malamy, University of Chicago Department of Molecular Genetics and Cell Biology:Worked on elucidating the role of YUCCA-mediated auxin biosynthesis in root development in Arabidopsis thaliana using pYUC:GUS lines, yucca mutants, and the pOp/LhGR glucocorticoid inducible system to spatiotemporally modulate auxin levelsHigh-Throughput Plant Phenomics Technology Development, Dr. Justin Borevitz, University of Chicago Department of Ecology and Evolution:Designed infrastructure and image analysis scripts for high-throughput plant phenotyping of A. thaliana grown in growth chambers set to simulate the spring conditions of Spain and Sweden to identify gene by environment interaction quantitative trait loci that may be responsible for regional adaptation

Dr. Susan Singer, Carleton College Biology DepartmentGenome walked to sequence and identify promoter region of PIM in Pisum sativum; identified transcription factor binding motifs and evaluated evolutionary conservation

Individually tutored students in beginning and intermediate Japanese

Carleton College Biology DepartmentSet up laboratory materials; cell culture preparation; solution preparation; clarified concepts and helped with protocol in and out of the laboratory.