Music 
About
Daolang is a doctoral student co-supervised by Samuel Kaski (Aalto University) and Luigi Acerbi (University of Helsinki), affiliated with the Probabilistic Machine Learning group at Aalto University, the Machine and Human Intelligence group at the University of Helsinki, and ELLIS Institute Finland. He is fully funded by Finnish Center for Artificial Intelligence (FCAI). He received his master’s degree at Aalto University, with a major in Machine learning, data science and artificial intelligence (Macadamia). Daolang’s work focuses on amortized inference with applications to various Bayesian inference tasks. In his spare time, he is also an electronic music producer, mainly producing house music.
Click here to see my latest CV (last update: January 2026).
Research interests: amortized inference, Bayesian experimental design, simulation-based inference, Bayesian optimization, prior-data fitted networks (PFNs), neural processes.
News
2026.05: Our paper “Constrained Bayesian Experimental Design via Online Planning” has been accepted by ICML 2026, and I haven been selected as Gold Reviewer!
2026.02: Started a 3-month research visit at the RainML group at the University of Oxford, supervised by Prof. Tom Rainforth.
2026.01: Three papers have been accepted by ICLR 2026!
2025.11: Had an amazing week attending the Dagstuhl Seminar: Bayesian Optimisation.
2025.10: Gave an invited talk and short visit in RainML group at the University of Oxford.
2025.09: Our paper “ALINE: Joint Amortization for Bayesian Inference and Active Data Acquisition” has been accepted by NeruIPS 2025 as Spotlight (Top 3.2%)!
2025.09: Gave an invited talk at the Seminar on Compuational Engineering in LUT Lappeenranta.
2025.06: Gave an invited talk at the Accelerating statistical inference and experimental design with machine learning workshop at the Isaac Newton Institute in Cambridge. You can check the video of the talk here.
2025.05: I was awarded the Encouragement Grant by The Finnish Foundation for Technology Promotion.
2025.01: Our paper “PABBO: Preferential Amortized Black-Box Optimization” has been accepted by ICLR 2025 as Spotlight (Top 5.1%)!
2025.01: Two of our papers have been accepted by AISTATS 2025!
2024.10: I have been selected as one of the top 3 nominees for the AI Researcher of the Year by AI Finland!
2024.10: Participated in the poster session and served as the photographer at Finland AI Day x Nordic AI Meet 2024.
2024.09: Our paper “Amortized Bayesian experimental design for decision-making” has been accepted by NeurIPS 2024!
2023.11: Gave a talk about conditional neural processes at the Mathematical perspective on machine learning seminar at the University of Helsinki. [Slides]
2023.11: Gave a talk about our RCNP paper at Finland AI day 2023.
2023.09: Attended the Ellis RobustML Workshop.
2023.09: Two of our papers have been accepted by NeurIPS 2023!
2023.08: Had a fantastic week attending the Ellis Doctoral Symposium (EDS) 2023. I presented our work “Learning robust statistics for simulation-based inference under model misspecification” and also gave an introduction about the FCAI amortized inference team.
2023.07: Our paper “Augmenting Bayesian Optimization with Preference based Expert Feedback” has been accepted by ICML 2023 workshop The Many Facets of Preference-based Learning.