Postdocs Liang Wang Liang is working on simulation-based inference with probabilistic programming. In particular, Liang focuses on exploring how can probabilistic programming help us to do better inference with coupled simulators. PhD students Lorenzo Theunissen Lorenzo is working on new program synthesis techniques for automatically configuring the functionality of programmable network devices -- new generation network devices have switched to progammable data planes. Reuben Gardos Reid Reuben is working on scientific discovery through program synthesis and probabilistic programs as a representation of scientific models -- they allow us to focus on causal links and capture all stochasticity and uncertainty. Tilman Hinnerichs Tilman is working on neuro-symbolic approaches to knowledge representation and program synthesis, developing formal languages that combine symbols and distributed representations as well as techniques to learn such models. Issa Hanou Issa is exploring the interations between learning, the ideas from program synthesis, with special attention to robust planning. Aldo Pareja Probabilistic programming and simulators (with MIT-IBM Watson Lab) Jonas Witt Jonas is exploring how analogical reasoning, tied wtih problem decomposition, can help program synthesis techniques to solve more complex tasks (at Siemens and University of Bamberg) Research engineers Pamela Wöchner Pamela is helping us make [Herb.jl](https://herb-ai.github.io) as good as possible! Master students Avi Halevy Improving reasoning in Large Language Models with probabilistic logic programming and proof assistants (with Tina Nane) Han Heijmans Probabilistic programming and MDP solving (with Frans Oliehoek) Mara Coman Better proposals in probabilistic programming through constraint solving Luka Janjić Program synthesis for dependently typed programs (with Jesper Cockx) Lola Dekhuijsen Incremental inference in probabilistic programming Research assistants Stef Rasing Honours students (Bsc) Piotr Cichoń Evolving search procedures in program synthesis Nicolae Filat Evolving search procedures in program synthesis Ivan Bozhanin Learning distances for distance-guided program synthesis Tudor Magirescu Learning distances for distance-guided program synthesis Alumni PhD students Kshitij Goyal Machine learning under constraints (at KU Leuven, with Hendrik Blockeel) Master students Timo Jugariu Program synthesis for programmable data planes Jord Molhoek Incorporating prior knowledge in MDPs with probabilistic programming Reuben Gardos Reid Reasoning with a Rail Network Simulator Jaap de Jong Unifying example- and specification-based program synthesis Pepijn Klop Using Large Language Models to generate examples for program synthesis Gautham Venkataraman Using Probabilistic Programming to guide Combinatorial Optimization in Dynamic Environments Koen du Buf System on Chip early power estimation using Machine Learning Alexander Freeman Exploiting modularity in program synthesis Marc Droogh AI for chip topographical optimisation Dirk van Bokkem Economical greenhouse decision support model Research assistants Stef Rasing
