Biography
I am a Machine Learning Professor operating 50-50 in the UK and Finland. In Finland I lead the Finnish Center for Artificial Intelligence FCAI, and in the UK the Manchester Centre for AI Fundamentals AI-FUN. Part of my research group is at Aalto University and part in the University of Manchester.
Current events maybe of interest:
- CoGenAI: ELLIS Summer School on Collaborative and Generative AI, July 1-5, 2024, Helsinki
- ELLIS Robust ML Workshop in Helsinki: 27-28 June 2024
- ELLIS Robust LLMs Workshop in Oxford: 29-30 July 2024
- ELLIS Summer School on Machine Learning for Healthcare and Biology: 11-13 June 2024, Manchester
- CAIHU: AAAI Bridge Program: Collaborative AI and Modeling of Humans, Feb 2024
Research interests
- Probabilistic modelling and Bayesian inference
- Collaborative AI for decision making and design
- Collaboration with many fields including health, medicine, biology, user interaction, cognitive science, neuroscience; especially when formulated as virtual simulation-based laboratories
- Timely in ML: distribution shifts, multiple tasks and sources, generative models, experimental design, simulation-based inference, humans in the loop and theory of mind, privacy-preserving learning
Current activities:
- ELLIS Unit Helsinki and Manchester; ELLIS Fellow
- ELLIS Robust ML Program
- ELISE European Network of AI Excellence Centres
- Christabel Pankhurst Institute for Health Technology
- UKRI Turing AI World-Leading Researcher Fellow
- UKRI AI CDT in Decision Making for Complex Systems
- AI-DOC 100 AI PhDs in Finland
- Action editor: JMLR, IEEE TPAMI
- Regularly Area Chair (or equiv) of ML conferences including NeurIPS, ICML, AAAI
- I am very proud of the 36 PhD students and many postdocs I have mentored. Of my lab alumni, 21 have got faculty positions in Universities and the rest are entrepreneurs or in company positions (~50%) or staff members or postdocs at research institutes
Representative Recent Publications
All papers in Google Scholar and my group’s pages. Or old-school list.
(2024).
Learning Robust Statistics for Simulation-based Inference under Model Misspecification.
In NeurIPS 2023.
(2023).
Characterizing personalized effects of family information on disease risk using graph representation learning.
In MLHC 2023.
(2023).
Online Simulator-Based Experimental Design for Cognitive Model Selection.
Computational Brain & Behavior.
(2023).
Compositional Sculpting of Iterative Generative Processes.
In NeurIPS 2023.
(2023).
Noise-Aware Statistical Inference with Differentially Private Synthetic Data.
In AISTATS 2023.
(2023).
Differentiable user models.
In UAI 2023.
(2023).
Zero-shot assistance in sequential decision problems.
In AAAI 2023.
(2023).
Toward AI assistants that let designers design.
AI Magazine.
(2022).
Human-in-the-loop assisted de novo molecular design.
Journal of Cheminformatics.
(2022).
Likelihood-Free Inference by Ratio Estimation.
Bayesian Analysis, 17.
(2022).
Parallel MCMC Without Embarrassing Failures.
In ICML 2022.
(2022).
Tackling covariate shift with node-based Bayesian neural networks.
In ICML 2022.