Lorenz Wolf

Lorenz Wolf

PhD Student Foundational AI

University College London

About me

Hi, thanks for checking out my website! I’m a PhD student on the Foundational AI CDT at the Centre for Artificial Intelligence at UCL. My first supervisor is Mirco Musolesi who leads the Machine Intelligence Lab at UCL.

My research interests span from Statistical Machine Learning and especially Generative Modelling to Reinforcement Learning and Multi Agent systems.

Before starting the PhD I worked on Deep Generative models for music (AI assistant to composers) and did a ML research placement at Apple. In 2021 I graduated from the MSc Statistics at Imperial College London. I wrote my dissertation on Variational Autoencoders on Hilbert Spaces to generate functional data, supervised by Dr Andrew Duncan at Imperial College London and the Alan Turing Institute. I was happy to be awarded the Department of Mathematics Prize for my MSc results and fortunate to be supported by the Basil Furneaux Memorial Scholarship throughout the MSc. Prior to the MSc, I completed my BSc in Mathematics with Statistics also at Imperial College London.

Always looking for fun projects in the field of RL, ML, statistics, so feel free to get in touch if you want to chat or collaborate:)

  • Statistical Machine Learning
  • Multi-Agent RL
  • Generative Models
  • Unsupervised Learning
  • CDT Foundational AI, 2026


  • MSc Statistics, 2021

    Imperial College London

  • BSc Mathematics with Statistics, 2020

    Imperial College London


PhD, Foundational AI CDT
Sep 2022 – Present London
Working on RL, Multi-Agent RL, and Deep Generative Models
Machine Learning Research Placement
May 2023 – Sep 2023 London
Machine Learning Research Placement
Jun 2022 – Sep 2022 London
Machine Learning Research Intern
May 2022 – Jun 2022 London
Machine Learning for Music Synthesis
Teaching Assistant
Imperial College
Aug 2020 – Sep 2020 London
Developed teaching materials for the 3rd year module Stochastic Simulation.
Undergraduate Researcher
Imperial College London
Aug 2019 – Sep 2019 London
Modelling the spread of HIV

Recent Publications

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(2022). F-EBM: Energy Based Learning of Functional Data (AISTATS 2023).