Teaching, mentoring and service

How I teach, whom I have mentored, and how I contribute to the communities I work in.

Teaching

I teach from three habits that also shape my research. Start from the biological question and state the assumptions before fitting a model. Confront real data where those assumptions break, such as batch structure, donor effects confounded with condition, or changes confined to a few cell states. State how certain a result is, and which measurement would change it. Four questions carry these habits into every topic: what biological question does this formalism address, what are its assumptions, how do we interpret the results, and what are the computational trade-offs?

In class, students present their solutions and evaluate one another's, a regular, low-stakes occasion to share an idea. AI tools change how students learn each term, so my practices for them are current and provisional: some work is done without AI, such as deriving a model, predicting a result or explaining it in one's own words; an AI configured to push back challenges the student's reasoning before it helps; students audit AI-generated analyses with planted flaws; and grading rewards the reasoning, through open questions and brief oral defenses. Neither banning these tools nor surrendering to them serves students.

Experience

University of Washington, MCB 536 Introduction to Computational Biology (Winter 2025). Two lectures on single-cell RNA-seq analysis for first-year graduate students in the Molecular & Cellular Biology program.
Seattle Area Single Cell User Group (2025). Led an introductory workshop on single-cell analysis in Python.
Freie Universität Berlin, teaching assistant in mathematics (2013 to 2015). Led two weekly tutorial sections of about 20 students each and graded homework and examinations, in Computer-Oriented Mathematics I and II (numerical methods, error analysis, interpolation, ODE integration) and Logic and Discrete Mathematics.
Fraunhofer Institute for Cell Therapy and Immunology IZI, Leipzig (2021). Mentored undergraduates in the principles of RNA-seq data analysis and statistical methods for medical research.

Mentoring

Brennan Dury, undergraduate in computer science, University of Washington. Helped implement Mellon and 2for1separator, and is a co-author of the Mellon paper in Nature Methods.
Siddharth Baasri, undergraduate in computer science, University of Washington. Contributed to AnnZarro, an openly released single-cell data viewer whose preprint Baasri co-authored (bioRxiv, 2026).
Across laboratories, I guide trainees on computational questions in their projects, including Claire Mills on field cancerization in head and neck cancer, Connor Finkbeiner on chromatin and transcription during retinal differentiation, Jacob Greene on cell-cycle dynamics of histone methylation, and Elana Thieme.

From running teams of AI agents I carry three practices into mentoring: specify the task, have the result checked independently, and record each decision together with who made it. I completed CIMER-based Inclusive Research Mentor Training (2024) and was selected for the CCEH Leadership and Management Skills Course for Postdocs (2024).

Service

Seminar series: Co-chair of the MET-X (Center for Metastasis Research eXcellence) Seminar Series at Fred Hutch, 2025 to 2026: bi-weekly seminars, for which I invited external speakers across career stages and chaired trainee talks.
Journal review: Nature Computational Science, Bioinformatics, BMC Genomic Data, Theory in Biosciences, Genome Medicine, BMC Bioinformatics and Discover Oncology; with senior researchers for Genome Research, Cell Systems and ICML.
Conference review: MLCB and ACM-BCB (papers); ISSCR 2026 Annual Meeting (abstracts).
Fred Hutch: Reviewer for the SPAC Mentoring Awards (2025); poster judge at the TDS IRC Retreat and the Basic Sciences Division Retreat (2026).
Community: Organizer of bi-monthly Seattle networking events (Stammtisch) for the German Academic International Network (GAIN), a joint initiative of the Humboldt Foundation, DAAD and DFG, since 2023; co-host and moderator of the GAIN26 Science Slam, San Francisco, 2026.
Open science: Maintainer of the tools listed under Software, with documentation, continuous integration and user support; participant in the Open Problems in Single-Cell Analysis Jamboree (2021), which led to a benchmark paper in Nature Biotechnology (2025).