I'm finishing a PhD in computational cognitive neuroscience, working on a question I find genuinely interesting: how do you choose the right images to show someone in a brain scanner? Most vision experiments use a few hundred hand-picked stimuli. I'm building frameworks that can select from millions — so we learn more from fewer, shorter experiments.

Before academia, I spent several years as a data scientist — building recommendation systems, image processing pipelines, and ML infrastructure in production. That background shapes how I do research: I write code that's tested, documented, and meant to be reused, not just run once for a paper.

I'm open to opportunities starting September 2026, particularly roles where I can apply ML to hard problems — whether that's in industry, research, or something in between.

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The Path

2022 - Present

PhD in Computational Cognitive Neuroscience

Max Planck Institute for Human Cognition and Brain Sciences & University of Gießen

Working with Martin Hebart on making vision science experiments more efficient. Built pipelines to process massive fMRI datasets, developed active learning frameworks for optimal stimulus selection, and contributed to open-source tools and datasets used by the research community.

2021 - 2022

Research Assistant - ML in Medicine

ScaDS.AI Dresden/Leipzig

Built deep learning models for medical imaging - automatic brain region segmentation and uncertainty-aware prostate cancer mortality prediction.

2020 - 2021

Full-Stack Developer

Kimetric UG (Freelance)

Built hebartlab.com and things-initiative.org . Django backend, JS frontend, Linux hosting with NGINX.

2019 - 2021

Data Scientist (Working student)

CHECK24

Led development of an image processing microservice - deduplication, retrieval, classification, quality assessment. Optimized recommender systems with Bayesian hyperparameter tuning, trained ranking models. Also worked on backend (PHP, Go).

2018 - 2019

Data Scientist & Analyst (Working student)

Webdata Solutions (now Vistex) · Mercateo (now Unite)

Image retrieval pipelines, product classification models, cloud data warehousing (AWS). First exposure to building ML systems from scratch.

2014 - 2021

B.Sc. Business Information Systems & M.Sc. Computer Science

Leipzig University

M.Sc. grade 1.2 (Distinction). Focused on ML, data analysis, and medical image processing. Thesis on using GANs to synthesize images that maximally activate specific brain regions.

What I'm Good At

ML for perception

Training and interpreting vision models (CLIP, ViT, GANs), designing experiments that connect model representations to brain data.

Research infrastructure

Building pipelines that process terabytes of imaging data on HPC clusters. Packaging research code so others can actually use it.

Production ML

Recommendation systems, image retrieval, ranking models — I've shipped ML in industry before and know what it takes to keep it running.

Get in Touch

Happy to chat about research, potential collaborations, or opportunities. Email is best. Also on LinkedIn, GitHub, Hugging Face, and Google Scholar.