About

I am an Academy Research Fellow at Aalto University, supported by the Research Council of Finland. I lead the Approximate Inference Lab in the Department of Computer Science at Aalto. I am an ELLIS Member and also affiliated with the Finnish Centre for Artificial Intelligence. Previously, I was a postdoctoral researcher working with Prof. Samuel Kaski at Aalto University. I did my PhD from the Department of Electronic Systems, Aalborg University, Denmark on making approximate Bayesian computation methods for estimating parameters of stochastic models in the field of radio propagation (click here for more details).

My primary research area is simulation-based inference (or likelihood-free inference). I am interested in developing approximate inference methods that are (i) robust to model misspecification, and (ii) computationally efficient. For more details on my work, see my Publications page or my Google scholar

News

• September 2025: Our paper on Multilevel neural simulation-based inference is accepted at NeurIPS 2025.
• September 2025: Our paper titled ALINE: Joint Amortization for Bayesian Inference and Active Data Acquisition is accepted at NeurIPS 2025.
• September 2025 I was recently featured in the Humans of FCAI newsletter.
• January 2025: Our paper on Cost-aware Simulation-Based Inference is accepted at AISTATS 2025.
• January 2025: Our paper on Robust Simulation-Based Inference under Missing Data is accepted at ICLR 2025.
• January 2025: Yuga Hikida joined as a PhD student on my Research Council of Finland project.
• June 2024: I have received the Academy Research Fellowship grant from the Research Council of Finland.
• April 2024: Our paper on Bayesian Active Learning in the Presence of Nuisance Parameters was accepted for an oral presentation at UAI 2024.
• April 2024: Our paper on Learning relevant contextual variables within Bayesian Optimization was accepted at UAI 2024.
• Sep 2023: Our paper on Learning Robust Statistics for Simulation-based Inference under Model Misspecification was accepted at NeurIPS 2023.
• April 2023: Our paper on Optimally-weighted Estimators of the MMD for Likelihood-free Inference was accepted at ICML 2023.
• March 2023: Gave a talk at BayesComp 2023 conference on our paper Optimally-weighted Estimators of the MMD for Likelihood-free Inference.
• Nov 2022: Talk at the Department of Statistical Science, UCL.
• Oct 2022: Talk at the AI Centre, UCL. Video
• Oct-Nov 2022: Visiting Dr. F-X Briol at the Dept. of Statistical Science, UCL.
• May 2022: Our paper on Approximate Bayesian Computation with Domain Expert in the Loop was accepted for a short presentation at ICML 2022.
• April 2022: I was featured in the Everyday choices column of the Aalto University Magazine (Spring 2022 edition).
• February 2022: Co-organised the FCAI-Turing Meetup with Dr. F.-X. Briol. The event aimed at bringing together researchers from the Turing and FCAI to foster collaboration and create connections.
• September 2021: Our blog post (co-written by Dr. F.-X. Briol) on Using machine learning to improve the reliability of wireless communication systems is published on the Alan Turing Insitute’s website. The blog is based on our paper in the Transactions on Antennas and Propagation journal, and is joint work with Assoc. Prof. Troels Pedersen.