Leading a computational biology team in the Informatics and Predictive Sciences department working with the IO and Cell Therapy Thematic Research Center; team members and I perform exploratory analyses for discovery, pre-clinical, and translational activities. We use datasets such as bulk and single cell RNA-seq on solid tumor and sorted immune cells, flow cytometry on blood and bone marrow cells, multiplex IHC of solid and heme tumors, CAR-T expansion, disease genetics, and blood cytokines. Participate in cross-functional teams related to cellular therapy strategy, biotherapeutics and small molecule discovery, and translational programs. Perform gene expression analysis using TCGA and single cell datasets to predict responsive patients across cancer indications for internal and partner immuno-oncology clinical programs. Use learnings from analysis of T cell exhaustion datasets to enable identification of new targets, inform in vitro target validation assays, and interpret CAR-T expansion and response in the clinic. [Originally hired at Celgene, now at BMS through acquisition][Consultant, 2015; Principal Scientist, 2015-2018; Senior Principal Scientist, Nov 2018; Director, March 2020-]

Develop and maintain a gene expression atlas web application for use by biologists. Application allows users to search for differentially expressed genes, generate gene expression plots, discover and test potential biomarkers, perform sample clustering analysis. It also provides the data and plots with a user-friendly API so that other tools can incorporate the data. License the software to several biotech companies.

• Statistical analysis and reporting of clinical data for FDA filing of a new diagnostic gene expression test for sepsis, SeptiCyte(c) Lab, later approved in 2017.• Process and analyze many public gene expression datasets with the goal of finding new signatures for sepsis or other infections in various settings. (published June 2017, Scientific Reports, see below for link)

• Lead well respected bioinformatics team whose focus included many aspects of the autoimmune drug discovery process such as target discovery, biomarker identification, mechanism of action, and patient clinical response. The team used a wide combination of RNA expression (RNA-seq and microarray), genetic (GWAS and whole genome), FACS and pathway data as our primary sources for this work.• Identified need and took the initiative to develop a web-based tool to integrate and share all of the relevant public and internal RNA-seq profiling data with the various biology groups across company global sites. This web database enabled team members and biologists to introduce multiple new targets into the drug discovery pipeline.• Participated in several cross functional strategy teams including: the rheumatoid arthritis target discovery program, big data, software evaluation, human genetics, in-licensing and the lupus (SLE) disease focus group.• Utilized data analysis techniques such as principal component analysis (PCA), clustering approaches (hierarchical clustering, k-means), differential expression tests, linear models, machine learning, gene modules, cell type deconvolution, and pathway analysis.[Senior Scientist, 2009-2014; Principal Scientist, 2014]

• Integral member of Computational Biology group, involved with many different research and discovery projects in areas of immunology and oncology. The group was the major source of novel drug candidates and value for the entire company. • Example activities: computational assisted discovery of novel protein therapeutics (data management and integration, web interface design, sequence alignments, HMM algorithms), working with biologists on specific projects and interdepartmental discovery strategy teams, global EST and microarray gene expression statistical analysis, proteomics tool development, 3D protein modeling, public data downloading services and various other support activities.• Played a significant role in the discovery of drug candidate interferon-lambda (IL29), which had positive results in recent clinical trials for Hepatitis C and was the primary asset in the multi hundred million dollar acquisition of ZymoGenetics by BMS.[Associate Computational Biologist, 2000-2001; Computational Biologist 2001-2005; Senior Computational Biologist, 2005-2009]

• Worked to understand the active conformation of blood coagulation Factor XIII in the lab of advisor David Teller, Ph.D. Used X-ray crystallography to determine the structure of this enzyme under several different conditions.• Assisted in the highly delicate process of crystal handling, synchrotron data collection, and the initial steps for the eventual structure determination of the rhodopsin protein - the first crystal structure of a GPCR. This publication has been cited several thousand times due to the enormous importance of this class of proteins in biomedicine.• In the lab of David Baker, Ph.D., worked on computational research projects associated with protein fold prediction. Developed secondary structure packing descriptive statistics used in the early and groundbreaking versions of the Rosetta software, which was the best performing protein fold prediction programs.• Projects involved genetic algorithms, monte carlo methods, 3D model feature extraction, phylogenetic analyses, 3D model visualization, FFTs, least squares minimization and other statistical and numeric methods.

• Visualized a dataset of wind streak patterns derived from Mars Viking orbital photos overlaid on surface topographical maps (Peter Gierasch, Ph.D.).• Examine images and redshifts of nearby galaxies to calculate the relative motion of the Milky Way (Martha P Haynes, Ph.D.)• Applied statistical methods to determine the likelihood of a relationship between the visual imagery and high energy observations of gas embedded hot stars (Katy Garmany, Ph.D. @ Boulder).