Building sovereign AI infrastructure for Swiss companies: open-source models, on-premise & Swiss cloud.
AI Learning Coach for Entlastungsdienst Bern: multi-agent system (5 specialised agents) for scenario-based competency assessment, personalised learning paths, interactive training, and a confidential reflection space for care workers. Delivered in 14 weeks (Nov 2025 – Feb 2026).
Sovereign AI Platform: co-developed and rolled out an on-premise / Swiss-cloud platform based on open-source LLMs, deployed across multiple client industries.
Built LLM applications for clients in tech, finance, and energy.
Text-to-Data Chatbot (major US tech company): multi-agent conversational analytics system for querying business and sales data in natural language — identified the correct database, executed queries, generated grounded answers and dynamic charts.
Data Quality Monitoring (Swiss energy company): end-to-end anomaly detection pipeline for operational data; led stakeholder requirements workshops and a comparative evaluation of candidate solutions.
LLM Due Diligence Assistant (Swiss asset manager): semantic document retrieval system for due diligence workflows with full source traceability — every answer linked to its origin document.
PhD Candidate in Computational Neuroscience
University of Amsterdam
August 2022 –
March 2023
Amsterdam
Worked as part of the ARC-INTREPID project: an adversarial collaboration between three neuroscientific theories of consciousness.
Developed a significant part of Darts, an open source library for time series forecasting, including statistical and deep learning-based forecasting tools. Presented Darts at the EuroPython 2021 conference and the PyData Global 2021 conference. During the time I worked on Darts, its GitHub page went from 0 to over 3.3k stars.
Built a ML-based predictive maintenance tool for a Swiss hydro power plant, all the way from exploratory data analysis and model development to backtesting and deployment.
Developed a demand forecasting solution for a Swiss manufacturer of laboratory and industry equipment which improved their existing forecasts by 10% - 50% (depending on the metric).
Co-hosted multiple technical public webinars revolving around topics in data science and machine learning.
Institute of Neuroinformatics, ETH Zürich & University of Zürich
September 2020 –
October 2022
Zürich
Developed a novel, bio-inspired continual learning algorithm called sparse-recurrent DFC as part of my master thesis, which received the maximum grade.
Showcased poster about my master thesis at the AI+X Summit 2022. Presented my work at an IROS 2022 workshop on continual learning.
Founded Qualiaheads, a student club and reading group on consciousness science. Conducted interviews with researchers such as Anil Seth and Pedro Mediano.
Finished degree with a weighted GPA of 5.8 out of 6.
Computer Science Program
University of Pennsylvania
August 2018 –
December 2018
Philadelphia
Took courses at the computer science department and the Wharton business school.
Received honorable mention for Facebook-sponsored award in a project-based coding competition as part of the NETS 212 course (among top 4 of 54 teams).
Finished the semester with a GPA of 3.75 out of 4.
BSc Computer Science
ETH Zürich
September 2016 –
April 2020
Zürich
Worked as a student assistant teaching calculus.
Received a scholarship for a selective exchange program to the University of Pennsylvania.