Experience

  1. PhD in Machine Learning

    ETH Zurich

    Research Focus: Representation Learning, Multimodal Foundation Models.

    • Four first-author conference publications, each accepted on first submission.
    • Leading development of an agentic, multimodal foundation model for clinical decision support.
    • Translated own method into clinical practice, enabling first-ever bowel obstruction localization.
    • Supervised 12 MSc theses across four cohorts.

  2. Research Scientist Intern

    Meta

    Performance Rating: Greatly Exceeds Expectations (Highest Tier).

    • Developed multimodal tokenization learning for scalable generative recommender systems.
    • First generative recommender to surpass sequential recommenders on industry-scale datasets.

  3. Research Scientist Intern

    QuantCo

    Performance Rating: Highest Recommendations (Highest Tier).

    • Generative modeling of MRI images, reducing acquisition time by 50%.

  4. Teaching Assistant in Statistics

    University of Zurich
    Performance Rating: Very Satisfied (Highest Tier).
    Focus: Teaching Statistics and Econometrics to 1,000 students.

  5. Data Science and Central Controlling Intern

    Allianz Suisse
    Performance Rating: Highest Tier in all categories.
    Focus: Implementation of new statistical methods to forecast company KPIs.

Education

  1. PhD in Machine Learning

    ETH Zurich
    Supervisors: Prof. Julia E. Vogt and Prof. Bjoern H. Menze. Thesis: Structural Learning for Interpretability and Multimodal Foundation Models.

  2. Master of Science in Statistics

    ETH Zurich

    GPA: 5.98 / 6 (Class Rank 1)

    During my master’s, I was intrigued by the capabilities of ML methods, which led me to go beyond the standard curriculum, earning over 30 additional credits and publishing two papers. Selected completed courses include Deep Learning, Medical Image Analysis, Natural Language Processing, Probabilistic Artificial Intelligence, and Statistical Learning Theory. My master’s thesis focused on detecting and removing biases in ML models.

  3. Bachelor of Arts in Business and Economics

    University of Zurich

    GPA: 5.84 / 6 (Class Rank 2)

    With a major in Banking & Finance and a minor in Statistics, my bachelor’s has laid the foundation for my interest in quantitatively assessing and understanding the behavior of complex phenomena. My bachelor’s thesis focused on predicting stock returns with high-dimensional generalized additive models.

Skills
Technical
Python
PyTorch
Tensorflow
Hugging Face
Distributed Training
Slurm
Docker
Git
LaTeX
R
Research
Multimodality
Foundation Models
Vision-Language Models
Representation Learning
Structural Learning
Generative Modeling
Diffusion Models
Computer Vision
Interpretability
Achievements
Selected Participant, Citadel EMEA PhD Summit
Citadel ∙ 2026
Four Orals (ICML/ICLR Workshops)
TTU, InterpretableAI, AccMLBio, DG Workshops ∙ 2026
Oral presentation of papers at TTU, InterpretableAI, AccMLBio, and Domain Generalization Workshops.
Spotlight Poster at NeurIPS
NeurIPS ∙ 2023
Willi Studer Prize
ETH Zurich ∙ 2022
Best Master’s Degree in Statistics at ETH Zurich.
Best Paper Award
Swiss Urology Congress ∙ 2022
Scholar
Swiss Study Foundation ∙ 2021
Summa cum Laude distinction
University of Zurich ∙ 2020
For Bachelor’s Degree in Business and Economics.