Experience [n] = publication number on page 2
Axiom Bio Founding Member of the Technical Staff
San Francisco, CA2023–2026
- Invented two image-based bioactivity-detection methods ~10× more sensitive than conventional assays.
- Led labeling, QC and PyTorch U-Net segmentation of 100,000+ compound images; in production 1+ year.
- Oversaw assay development for two of the largest Cell Painting datasets, built as AI-ready training data.
Nat Commun 2026 [4] Cell Syst 2026 [3]
Insitro Associate Scientist III, Arrayed Screening
South SF, CA2022–2023
- Onboarded tuberous sclerosis and ALS screens, from assay development to automated 384-well imaging.
- Trained two screen operators; automated analysis of hundreds of plates in Python and R.
- Developed a label-free phase-contrast timecourse imaging method to track live neuron growth.
MIT Technical Associate II, Synthetic Neurobiology Group
Cambridge, MA2021–2022
- Imaged 30+ proteins at nanoscale by optimizing expansion revealing (mExR) over 7+ staining rounds.
- Ran and optimized the lab's shared ImageJ/Fiji and MATLAB pipelines for the published method.
Nat Commun 2024 [6]
AbbVie Associate Scientist II, Foundational Neuroscience Center
Cambridge, MA2018–2021
- Established tau-aggregation screens in primary and iPSC neurons, from assay development to R lead ranking.
- Designed microfluidic neuron cultures that model tau spread between cells, for testing propagation inhibitors.
Mol Neurodegener Adv 2026 [1] iScience 2026 [2] J Biol Chem 2025 [5] iScience 2022 [7]
Massachusetts General Hospital Research Technician I
Boston, MA2017–2018
- Recorded voltage-clamp currents from GABA-A receptors in Xenopus oocytes to study how anesthetics act.
Eur J Med Chem 2019 [8]
Independent work questions explored with AI agents
Datum Line Designing my ideal AI × bio startup: controls alone name the lab, 99.9% 2026
Overdose Watch Public overdose tracker a weekly Claude Code agent keeps current 2026
Vanitas / Veritas AI slop as vanitas: 4K open-source diffusion loop, interactive piece 2026
Education
Colgate University B.A. Cellular Neuroscience, minor Mathematical Systems Biology
2013–2017
Harvard Extension School Graduate coursework in Python and computer vision
2019–2020
Skills
ML & data: PyTorch, U-Net segmentation, feature engineering, Python, R, agentic coding (Claude Code)
Lab & imaging: confocal, high-content and expansion microscopy, voltage clamp, iPSC neurons, HT screening
Story & design: data visualization, figure and pitch-deck design, generative art (Midjourney, diffusion)