# Jacob Pichelmann

> Jacob Pichelmann is Head of AI Development at RetInSight (Topcon Healthcare) in Vienna, where he leads the team developing AI for retinal OCT imaging.

At RetInSight, a Medical University of Vienna spin-off and part of Topcon Healthcare since 2025, I lead the AI engineering team that takes models for retinal imaging from data and clinical annotation to validated, certified, deployed product.

I came to medical AI through econometrics. I trained at the Toulouse School of Economics, graduating top of my track, and did empirical research at the OECD and the University of Zurich. That grounding in measuring things rigorously still shapes how I build and evaluate models.

## Timeline
- Aug 2026 – present: Up! More time with friends, Side project
- Jun 2026 – present: Head of AI Development, RetInSight
- Feb 2025 – Jun 2026: AI Development Lead, RetInSight (First author at ARVO 2025 & 2026; Acquired by Topcon, May 2025)
- Feb 2022 – Feb 2025: Deep Learning Engineer, RetInSight (Promoted after 10 months; First author at ARVO 2024)
- Oct 2021: Sustainability Data Science Challenge, Co-hosted by Capgemini and Microsoft (1st for model performance; 2nd overall)
- Nov 2020 – Aug 2021: Research Assistant, University of Zurich
- May 2020 – Jul 2020: Data Science Intern, Erste Group
- Sep 2019 – Sep 2021: MSc Econometrics & Empirical Economics, Toulouse School of Economics (Valedictorian, Econometrics track; Highest honours; TSE scholarship 2020)
- Mar 2019 – Mar 2020: Intern, then Consultant, OECD (Co-author, OECD Working Paper No. 1626)
- Oct 2015 – Nov 2018: BSc Economics, WU Vienna (Highest honours; Ranked 30th, top 1%; Dean’s List; Merit scholarships 2016–2018)
- Oct 2015 – In progress: Law (Mag. iur.), University of Vienna
- Mar 2015 – Jun 2018: Co-founder, Findus
- Oct 2013 – Jun 2014: Civilian service, Verein Ute Bock (Record €45,000 in donations)
- 2011: Editorial intern, DIE ZEIT

## Selected work
- [AI screening for retinal disease: from algorithm to clinical evidence](https://j-3-1415.github.io/projects/retinal-screening/): I led development of a deep learning algorithm that screens OCT scans for retinal biomarkers, then ran a reader study to test whether it helps clinicians decide better. It does: detection performance improved by 42%.
- [Should I stay or should I go? Housing and residential mobility across OECD countries](https://j-3-1415.github.io/projects/oecd-paper/): A cross-country study of what makes people move home, and how housing policy helps or hinders it. I co-authored the paper and did the entire statistical analysis and methodology.
- [Moving beyond efficiency: a novel framework to measure trade-flow resilience](https://j-3-1415.github.io/projects/thesis/): COVID stress-tested global trade in real time. I set up a collaboration with the University of Zurich and developed a way to measure trade-flow resilience where none existed before.
- [Sustainability Data Science Challenge](https://j-3-1415.github.io/projects/sustainability-challenge/): Together with a colleague from university, I built a satellite-imagery segmentation pipeline that estimates CO₂ emissions, biodiversity and solar potential. It placed 1st for model performance and 2nd overall.
- [Up! More time with friends](https://j-3-1415.github.io/projects/up/): A small social app I built with agentic coding and shipped to the App Store and Google Play. One tap says “I’m free”, and your friends see who’s up today.

## Profiles
- [LinkedIn](https://www.linkedin.com/in/jacob-pichelmann)
- [GitHub](https://github.com/j-3-1415)