If you are interested in joining us, please check our open positions page.
Principal Investigator
luigi.acerbi [at] helsinki.fi | Google Scholar | Twitter | Personal page
Assistant Professor, University of Helsinki, Finland
Department of Computer Science | Finnish Center for Artificial Intelligence (FCAI)
Luigi Acerbi leads the Machine and Human Intelligence group at the University of Helsinki. Before that, he was a postdoctoral researcher in computational neuroscience and machine learning at New York University (NY, USA) with Wei Ji Ma and at the University of Geneva (Switzerland) with Alexandre Pouget, where he collaborated with the International Brain Laboratory. He obtained his PhD from the University of Edinburgh (UK) as part of the Doctoral Training Center in Neuroinformatics and Computational Neuroscience, working with Sethu Vijayakumar and Daniel Wolpert. He spent several months of his PhD at the Computational and Biological Learning Lab in Cambridge (UK). Before that, he studied theoretical physics and computer science at the University of Milan-Bicocca (Italy). He obtained the title of Docent of Computer Science from the University of Helsinki and is a member of ELLIS (European Laboratory for Learning and Intelligent Systems). He enjoys boardgames and speculative fiction.
Postdoctoral/Doctoral Researcher
name.surname [at] helsinki.fi
Researcher in probabilistic machine learning
We have openings for co-supervised postdoc and doctoral student positions as part of a Finnish Center for Artificial Intelligence (FCAI) - ICT Helsinki joint postdoc call. See this page for more information.
Postdoctoral Researcher
gregoire.clarte [at] helsinki.fi | Personal page
Finnish Center for Artificial Intelligence FCAI
Grégoire is a FCAI postdoc based in our lab and co-supervised with Aki Vehtari (Aalto University). Grégoire joined our lab in 2021, after obtaining his PhD from University Paris Dauphine, under the supervision of Christian P. Robert and Robin J. Ryder. He is interested in applied Bayesian statistics, in particular to phylolinguistics, and numerical methods for likelihood free models and problematic posteriors. These two last points led him to active learning methods and surrogate model based methods. When not doing maths, he enjoys a nice book, an opera or some board games.
Postdoctoral Researcher
ulpu.remes [at] helsinki.fi | Google scholar
Finnish Center for Artificial Intelligence FCAI
Ulpu is an FCAI postdoc co-supervised with Jukka Corander (University of Helsinki and University of Oslo) since September 2022. She has a DSc (Tech) degree in speech and language technology from Aalto University and has previously worked as a researcher at the University of Helsinki and the University of Oslo. Ulpu is interested in probabilistic machine learning methods and likelihood-free inference. In her spare time, she likes to read books and comics.
Doctoral Student
chengkun.li [at] helsinki.fi | Personal page
Researcher in Sample-Efficient Probabilistic Machine Learning
Chengkun joined the lab in August 2021 as a doctoral student. Previously, he completed the Bachelor program at Shanghai Jiao Tong University (SJTU) and a double Master program at SJTU and Ecole Centrale Paris. After working on computer vision and robotics problems, he now focuses on the foundations of machine learning and novel probabilistic learning methods, with a special interest in sample efficiency. In his spare time, Chengkun enjoys reading, playing the guitar and taking photographs.
Doctoral Student
daolang.huang [at] aalto.fi | Personal page
Researcher in Amortized Probabilistic Machine Learning
Daolang is a doctoral student co-supervised with Samuel Kaski (Aalto University) since July 2022. Previously, Daolang has worked as a research assistant in the Probabilistic Machine Learning Group at Aalto University. He received his master’s degree at Aalto University, with a major in Machine Learning, Data Science and Artificial Intelligence (Macadamia). In his spare time, he is also an electronic music producer, mainly producing house music. Daolang's work in the lab focuses on amortized inference with applications to decision making and multi-agent modeling.
Research Assistant
robert.huggins [at] helsinki.fi
Machine Learning Engineer
Bobby is an M.Sc. student in Mathematics and Statistics, and joined the lab in 2022 to continue work on porting the Variational Bayesian Monte Carlo toolbox to Python. He is animated by research that lies at the intersection of applied mathematics, statistics, and computational science, with a particular interest in statistical approaches to inverse problems. Prior to studying at HY, Bobby completed his B.A. in Mathematics at the University of Chicago, and spent several years working backstage in the live theatre industry before returning to math. In his spare time, Bobby is most likely to be found exploring Dungeons and fighting Dragons around a table (real or virtual) of friends.
Research Assistant
victor.yeomsong [at] helsinki.fi
Machine Learning Researcher
Victor is an M.Sc. student in Data Science, and joined the lab in 2023 to work on probabilistic machine learning methods such as PyBADS and PyVBMC applied to model fitting of complex cognitive science models. His B.Sc. is in Electrical Engineering from the University of Costa Rica, and his research interests lie in Robotics, Signal Processing and Probabilistic Machine Learning. In his free time, he enjoys playing videogames, hiking and learning about mundane, everyday things.
Research Assistant
yinong.li [at] helsinki.fi
Machine Learning Researcher
Yinong is an M.Sc. student in Data Science, and joined the lab in summer 2023 to work on amortized inference, targeting models with challenging-to-evaluate likelihood functions. He completed his bachelor’s degree in Software Engineering at Jiangxi Normal University, and he is interested in Bayesian inference and probabilistic circuits. In his spare time, he enjoys collecting vintage clothing, swimming and traveling.
BSc Thesis Student
julia.perathoner [at] helsinki.fi
Julia is a B.Sc. student in Mathematics at the University of Trento and is currently doing an exchange year at the University of Helsinki. She has a keen interest in computational statistics and is currently working on efficiently implementing the statistical method Inverse Binomial Sampling in Python. In her spare time, Julia enjoys snowboarding and reading books.