Nino Scherrer Portrait

Nino Scherrer


I am a researcher working on automated language model evaluations and synthetic training data construction.

Previously, ...

Fields of Interest

Causality NLP AI Safety / AI Ethics Interpretability Robustness Fairness


> Language Model Evaluations

> Mechanistic Interpretability

  • Uncovering Mesa-Optimization Algorithms in Transformers
    Johannes von Oswald*, Eyvind Niklasson*, Maximilian Schlegel*, Seijin Kobayashi, Nicolas Zuccet, Nino Scherrer, Nolan Miller, Mark Sandler, Blaise Agüera y Arcas, Razvan Pascanu and João Sacramento
    Arxiv Preprint, 2023

    Mechanistic Interpretability

> Causality / Machine Learning

> Medical Image Analysis

> Biology / Tissue Engineering

Tutorial "Causality and Deep Learning"

I contributed to the ICML 2022 Tutorial on "Causality and Deep Learning: Synergies, Challenges and the Future". The corresponding work (systematic survey) "Deep Learning for Causality: A Unifying Perspective on Neural Causal Structure Learning" will be released soon.
Tutorial Slides


  • ...
  • September 2023: "Evaluating the Moral Beliefs Encoded in LLMs", ChatGPT Zurich Group (AI Meetup), Zurich
  • February 2023: "Deep Learning for Causality: Neural Causal Structure Learning", AI for Actionable Impact (AI4AI) Lab , Imperial College London
  • January 2023: "On the Synergies of Causality and DeepLearning", Neuroscience in ML Seminar, ETH Zurich
  • April 2022: "Learning Neural Causal Models with Active Interventions", XAI seminar series, Imperial College London
  • October 2021: "Learning Neural Causal Models with Active Interventions", Causality Reading Group, TU Darmstadt

Nino's Log

Heavily inspired by Liliam Weng's Log, I am starting to "log" my learning notes / thoughts in the field of AI using blog posts.

Last Updated: August 18th, 2023