Together with Maryam Tavakol & Vincent Francois-Lavet, we are organizing the 2024 edition of the Belgian-Netherlands Reinforcement Learning Workshop (BeNeRL) in Amsterdam! It will take place on June 10th, and will be a free event thanks to generous support by the Ellis Unit Amsterdam and the NWO. Registration is required, though.
More info & sign-up at the event website.
Masoud started as assistant professor at TU Delft
After his postdoc, Masoud has recently started as assistant professor in the Multimedia Computing Group of TU Delft. Congratulations, Masoud!
Jin’s paper was accepted to SIGIR
“Going Beyond Popularity and Positivity Bias: Correcting for Multifactorial Bias in Recommender Systems” by Jin Huang, Harrie Oosterhuis, Masoud Mansoury, Maarten de Rijke, and me, was accepted for presentation in SIGIR!
David & Guillermo’s paper was accepted to ICAPS
David & Guillermo’s paper “Planning with a Learned Policy Basis to Optimally Solve Complex Tasks” was accepted for presentation at ICAPS. This paper investigates how pre-trained sub-policies can be used to complete complex tasks described by reward machines, without losing optimality. Congrats!
AAMAS paper accepted!
Our paper on Uncoupled Learning of Differential Stackelberg Equilibria with Commitments has been accepted for publication at AAMAS. Congratulations, Robert and Mert!
Preprint is accessible here.
PhD positions on machine learning for fintech
At Amlab, we have two open PhD positions on machine learning in the fintech domain (in collaboration with Adyen). One student will work with Sara Magliacane on causal machine learning, and the second student will work with me on reinforcement learning. Deadline for applications is March 11th. For all details and how to apply, please see the official vacancy.
PhD position on reinforcement learning for controlling critical infrastructure
We are looking for a PhD candidate to work on several fundamental questions necessary for allowing AI methods to support human operators in critical infrastructure. For example, can machine learning tools be combined with conventional optimisers to improve safety and data efficiency? Can complex, structured decisions be made jointly by a human operator and an artificial agent? Can such algorithms deal with hierarchies in decision making, and how can decisions or models be explained and verified? Full details and instructions to apply can be found on this page.
New project on using AI to support human operators to control critical infrastructure
As part of consortium of 8 European countries, I will be involved in AI4REALNET (AI for real-world network operations). In this project, we will investigate how AI can be used to support decision making by human operators to improve safety and efficiency in the energy and transport sectors. AI4REALNET receives funding from the European Union’s Horizon Europe Research and Innovation programme.
2-day graduate course on “adaptive hybrid intelligence”
We are organizing a course for PhD students in the Netherlands around training RL agents to assist or collaborate with people. I’m very happy with our line-up. Read more!
Postdoc positions on AI for sustainable molecules and materials
The university of Amsterdam is looking for 4 postdocs on the topic of AI for meta-materials. One of the positions will be co-advised by me, on the topic of “Machine Learning-based models of plant protein mixtures for sustainable food design”. Two other positions are co-advised by AMLab colleagues. Deadline for applications is 16 May. Apply is only possible through the form here.
(Note that another postdoc position at the VU on learning and reasoning for medical decision making is also still open, see below).