Francesco Lässig

Francesco Lässig

Data Scientist

Unit8

I am interested in AI, brains, consciousness and other things.

Experience

 
 
 
 
 
Data Scientist
March 2024 – Present Zürich
Working on LLM and other data science / engineering projects in various industries like tech, finance, energy.
 
 
 
 
 
PhD Candidate in Computational Neuroscience
University of Amsterdam
March 2023 – August 2022 Amsterdam
  • Worked as part of the ARC-INTREPID project: an adversarial collaboration between three neuroscientific theories of consciousness.
 
 
 
 
 
Research Assistant
Institute of Neuroinformatics, ETH/UZH
November 2022 – February 2022 Zürich
  • Wrote an original research article based on my master thesis.
  • Currently awaiting feedback from the reviewers at the Biological Cybernetics journal.
 
 
 
 
 
Data Scientist
April 2020 – February 2022 Zürich
  • 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.
 
 
 
 
 
Machine Learning Engineer
September 2019 – December 2019 Zürich
Devised and built machine learning solutions for small and medium-sized Swiss banks.

Contents

All types of publicly available contents that I produced other than academic publications, including blog posts, presentations and other projects.

.js-id-darts

Education

 
 
 
 
 
MSc Neural Systems and Computation
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.
  • Took courses on both neuroscience and machine learning topics.
  • 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.
  • Completed degree with a GPA of 5.36 out of 6.