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Curriculum Vitae

Contact Information

LinkedIn: https://www.linkedin.com/in/micheleenharris

Summary

With over 15 years of computer science and data science experience (mostly in industry) as well as over 10 years of biochemistry experience, I have a unique skillset to bring to any role in healthcare or biotech. My skills include:

  • ML and deep learning - NLP, time-series, computer vision, PyTorch, ONNX, Scikit-Learn, XGBoost, Gen AI, and other areas/frameworks.

  • Biochemistry and bioinformatics - over 10 years of experience in biochemistry, proteomics, cancer research, drug discovery, infectious disease, NGS, and protein folding.

  • Software engineering and cloud technologies - Python, R, and Azure cloud services.

  • Speaker and community organizer - founding member of Seattle Artificial Intelligence Workshops and organizer for Seattle Women in Machine Learning and Data Science.

Education

Master of Science in Bioinformatics Tandon School of Engineering, New York University, NYC, NY, August 2025

Bachelor of Science in Biochemistry, Concentration in Computer Science Department of Chemistry and Biochemistry, The School of Natural Sciences, The University of Texas at Austin, Austin, TX, August 2002

Professional Experience

Senior Data Scientist Microsoft, Redmond, WA, May 2015 - Present

Drove ML customer engagements and AI product innovation using cloud and edge technologies from the research phase to production systems working across different industries and ML/DS domains, leveraging skills in software engineering, data engineering, visualization, machine learning, and deep learning.

  • Lead customer engagements in computer vision, time-series and NLP, leveraging classical and deep learning frameworks for data processing and ML modeling.

  • Lead product design research and implementations for timeseries analysis and demand forecasting with classical tree-based and deep learning approaches.

  • Prototyped with highly scalable data processing systems.

  • Delivered presentations, courses and tech talks on data and ML topics internally and externally (computer vision, NLP, Azure ML platform, online learning, responsible AI and more).

R Programmer Revolution Analytics, Seattle, WA, December 2014 - April 2015

Provided consulting on the R language for statistical applications.

  • Enhanced agricultural crop-yield prediction models and developed advanced visualizations and reports using the R language.
  • Microsoft acquired in 2015.

Software Engineer Institute for Systems Biology , Seattle, WA, September 2009 - October 2014

Developed software for bioinformatics in genomics and proteomics, as well as, tools for the visualization of complex biological datasets.

  • Used computational proteomics, search algorithms and data mining to find biomarkers in human tissue for the PeptideAtlas project.

  • Developed visualizations that aided in the transcriptomic analysis of diatoms to better understand the impact of ocean acidification.

Staff Research Associate University of California at San Francisco, San Francisco, CA, June 2008 - July 2009

Assisted in large-scale in vivo FDA-approved drug screening using the zebrafish model and confocal microscopy experiments to find small molecules that could lead to the regeneration of pancreatic beta cells.

Graduate Research Assistant and PhD Candidate Department of Chemistry and Biochemistry, The School of Natural Sciences, The University of Texas at Austin, Austin, TX, August 2002 -January 2006

  • Gene sequence analysis with HMMs for pathogenicity regions in Salmonella typhimurium.

  • Computational protein engineering and lab validation with active site mutagenesis to understand the mechanism of tRNA Synthetases binding and function.

Software Engineer Intern Institute for Systems Biology, Seattle, WA, May 2001 - August 2001

Developed web-based tools in Java and C++ to aid scientists in the field of proteomics (for computational LC/MS peptide identification).

Publications

Microsoft Azure: Planning, Deploying, and Managing the Cloud 2nd ed. Edition. 2020 July;Chapter 16. Link.

Ashworth J, Turkarslan S, Harris M, Orellana MV, Baliga NS. Pan-transcriptomic analysis identifies coordinated and orthologous functional modules in the diatoms Thalassiosira pseudonana and Phaeodactylum tricornutum. Marine Genomics. 2016 Apr;26:21-8.

Farrah T, Deutsch EW, Omenn GS, Sun Z, Watts JD, Yamamoto T, Shteynberg D, Harris MM, Moritz RL. State of the human proteome in 2013 as viewed through PeptideAtlas: comparing the kidney, urine, and plasma proteomes for the biology- and disease-driven Human Proteome Project. Journal of Proteome Research. 2014 Jan 3;13(1):60-75.

Azios NG, Krishnamoorthy L, Harris M, Cubano LA, Cammer M, Dharmawardhane SF. Estrogen and resveratrol regulate Rac and Cdc42 signaling to the actin cytoskeleton of metastatic breast cancer cells. Neoplasia. 2007 Feb;9(2):147-58.

Antikainen NM, Hergenrother PJ, Harris MM, Corbett W, Martin SF. Altering substrate specificity of phosphatidylcholine-preferring phospholipase C of Bacillus cereus by random mutagenesis of the headgroup binding site. Biochemistry. 2003 Feb 18;42(6):1603-10.

Community

Founder Seattle AI Workshops, Redmond, WA https://www.meetup.com/Seattle-Artificial-Intelligence-Workshops

Co-authored and facilitated evening and full-day technical workshops in Python and machine learning, with a focus in NLP. 1100+ members.

  • Preparing for the Data Science Interview Workshop (2021)
  • Introduction to NLP with PyTorch Workshop (2019)

Organizer Seattle Women in Machine Learning and Data Science, Seattle, WA https://www.meetup.com/seattle-women-in-machine-learning-and-data-science/

Honors and Awards

Microsoft Making a Difference Award Microsoft, Redmond, WA

Faraday Fellowship for Teaching Excellence Department of Chemistry and Biochemistry, The University of Texas at Austin, Austin, TX

Welch Teaching Excellence Award Department of Chemistry and Biochemistry, The University of Texas at Austin, Austin, TX

Additional Qualifications

Additional Computational Skills

  • Docker conterization
  • Software testing and lifecycle (DevOps)
  • Data transformation pipelines
  • Cloud-based ML and Data tools (Azure)
  • High performance computing (Slurm systems)
  • Next Generation Sequencing data processing and analysis

Programming Language and Framework Expertise

  • Highly knowledgable in Python, PyTorch, XGBoost, statsmodels
  • Experienced in R and the tidyverse