Jeremy Leipzig, PhD

Jeremy Leipzig, PhD

Bioinformatics engineer & Technical PM. Reproducible research, genomics, pipelines, and metadata. Architect and product leader for early stage therapeutic, diagnostic, and SaaS startups.

Teaching & Presentations

Teaching Experience

Adjunct Instructor

Drexel University College of Computing and Informatics
Spring Quarter 2018

  • Taught INFO103 Introduction to Data Science

Instructor & Teaching Assistant

Programming for Biology
Cold Spring Harbor Laboratory, 2007-2010

  • Multi-year instruction role at prestigious biological research institution
  • Focused on computational biology education for researchers

Conference Presentations and Posters

Recent Presentations

  • Drexel-CODATA FAIR-RRDM Workshop 2019 (Philadelphia)
  • CYTO2018 (Prague)
  • 2016 MidAtlantic Bioinformatics Conference (Philadelphia)

Academic Conference Presentations

  • Regional Translational Research in Mitochondria, Aging, and Disease Symposium - October 2013 (Philadelphia)
  • IEEE BIBM 2012 (Philadelphia)
  • ASHG 2012 (San Francisco)
  • RECOMB 2004 (San Diego)
  • Rocky Mountain Regional Bioinformatics Meeting 2003 (Aspen)

Professional Development & Outreach

Community Leadership

PhillyR Founder & Organizer

  • Founded and organized PhillyR, a user group aimed at sharing knowledge and experience among users of the R statistical programming environment
  • Built a community of data scientists and statisticians in the Philadelphia region

Online Presence & Knowledge Sharing

biostars.org - Bioinformatics Q&A Site

  • Top-20 ranking contributor
  • Active participant in the bioinformatics community’s premier Q&A platform

jermdemo.blogspot.com

  • Over 70,000 pageviews
  • Technical blog covering bioinformatics, data science, and reproducible research topics

Educational Philosophy

My teaching approach focuses on bridging the gap between computational methods and biological research. Through my experience at Cold Spring Harbor Laboratory and Drexel University, I emphasize practical, hands-on learning that enables researchers to apply computational tools effectively in their work.

I believe in making complex bioinformatics concepts accessible through:

  • Real-world examples and case studies
  • Interactive programming exercises
  • Community engagement and knowledge sharing
  • Open science and reproducible research practices

This philosophy extends to my community work with PhillyR and my contributions to online forums, where I’ve helped thousands of researchers solve computational challenges in their work.