I'm a PhD candidate studying how the brain processes visual information. My work sits at the intersection of neuroscience, machine learning, and building practical tools - I'm as interested in the science as I am in making research more efficient.

Before diving into academia, I spent several years as a data scientist in industry, building recommendation systems, image processing pipelines, and ML infrastructure. That experience shaped how I approach research: I care about things that work, scale, and can actually be used.

I'm wrapping up my PhD and open to opportunities starting September 2026 - particularly roles where I can apply ML to interesting problems, whether in research, industry, or somewhere 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 (Working student)

Webdata Solutions (now Vistex)

Built product image retrieval pipeline from scratch - crawled and cleaned massive datasets, trained models for image representations, segmentation, and text classification.

2018

Data Analyst (Working student)

Mercateo (now Unite)

Cloud data warehousing (AWS, Apache NiFi), ETL processes, integration testing infrastructure.

2017 - 2021

M.Sc. Computer Science

Leipzig University

Grade 1.2 (Distinction). Focus on ML, data analysis, medical image processing. Thesis on using GANs to synthesize images that maximally activate specific brain regions. Also worked as academic tutor for course on distributed systems.

2014 - 2017

B.Sc. Business Information Systems

Leipzig University

Grade 1.5. CS + economics + business. Included SAP development internship at GISA.

Skills

ML & AI

PyTorch, TensorFlow, Transformers (CLIP, ViT), GANs, contrastive learning, LLMs

Engineering

Python, Docker, SQL, Git, CI/CD, Flask, Redis, Linux, SLURM (HPC)

Methods

Model interpretability, Bayesian uncertainty, A/B testing, fMRI analysis

Beyond Work

When I'm not at a computer, I'm usually bouldering. I also play guitar and have a long-standing interest in meditation.

Get in Touch

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