Sebastijan Dumancic

I’m attending Aachen Symposium on Representation Learning to Act and Plan.

Tan Zhi-Xuan is visiting us today. We are excited to learn more about her work on probabilistic programming and model-based planning.

I’m participating in the IAS Amsterdam workshop on Logic and AI

I’m giving a lecture on machine learning with provable guarantees at the SIKS course on Neuro-symbolic AI

I’m attending the European AI for Fundamental Physics Conference 2024

Mara joins us as an MSc student. Mara will be working on automatically constructing better proposals in probabilistic programming with constraint solvers.

Lorenzo joins us as a PhD student. Lorenzo will be working with Fernando Kuipers and me on program synthesis for programmable networks, as a part of the Future Network Services project

Stef joins us again as a research assistant helping us to get Herb in a good shape

Han joins us as an MSc student. Han will be working with Frans Oliehoek and me on probabilistic programming and MDPs.

Jord Molhoek defended his master thesis Reasoning about MDPs Abstractly – Bayesian Policy Search with Uncertain Prior Knowledge, exploring how uncertain prior knowledge can be leveraged in MDPs with probabilistic programming

I’m visiting Nathanaël Fijalkow’s group at CNRS in Bordeaux

I’m giving a talk on the need for a neuro-symbolic languages at the Probabilistic Learning and Reasoning mini-symposium, co-located with Emile Van Krieken’s PhD defence. I am also one of Emile’s examiners.

Avi joins us as an MSc student. Avi will be working on improving reasoning in large langauge models with probabilistic programming and theorem provers.

Liang joins my group as a postdoc. He will be working on probabilistic programming for coupled physics simulators.

I am acting as a co-chair for the Special Track on Reasoning, Learning, and Decision-Making at KR 2024 together with Jean Christoph Jung and Iran Mansouri

Lola joins us as an MSc student. Lola will be working on incremental inference in probabilistic programs.

Luka joins us as an MSc student. Luka will be working with Jesper Cockx and me on program synthesis for programs with dependent types.

Bart joins us as an MSc student. Bart will be developing a specialised constraint solver for program synthesis.

Hector Geffner is visiting us today. We are excited to learn more about his work on generalised planning.

Reuben joins us as a PhD student. Reuben will be working on program synthesis and probabilistic programming for scientific discovery.

Alexander Freeman defended his master thesis Exploiting modularity during program synthesis, exploring how modularity can help us explore program spaces better

Gautham Venkataraman defended his master thesis Reduce, Reuse, Recycle – On exploration of solution reuse in VRPTW, exploring how exploit structure in vehicle routing problems thorugh probabilistic programming

Timo Jugariu defended a master thesis Program Synthesis for Programmable Data Planes, exploring the potential of progrma synthesis to automatically configure programmable networks

Reuben Gardos Reid defends his thesis Inferring Robust Plans with a Rail Network Simulator on using probabilistic programming to deal with uncertainty in railway planning problems

Pepijn Klop defended a master thesis Augmenting Program Synthesis with Large Language Models, exploring how large language models can help us generate more expamples for program synthesis

Jaap de Jong defended his master thesis Speeding up program synthesis with specification discovery, showing how we can automatically discover program equivalences and specifications in program synthesis from data

Andrew, Celine and I are giving a tutorial on inductive logic programming at AAAI’23.

Our RAIL lab has been funded through the ROBUST programme

I’m hiring a postdoc to work on probabilistic programming and simulators in geophysics! Check out the details here

I’m visiting Josh Tenenbaum and Tom Silver at MIT.

Dirk van Bokkem, a Master student I co-supervised with Neil, has won the second prize 2nd prize of the Young Talent KNVI/KIVI thesis prizes for Computer Science and Information Science.

Tilman Hinnerichs joined my group.

Issa Hanou has started a PhD with me and Mathijs de Weerdt. Issa will be working on making rail network planning more robust through insights from program synthesis and probabilistic programming.

A paper on automated decision-making for greenhouse climate management, with Neil and a Master student Dirk van Bokkem, is accepted at IAAI 23.

Our paper on provably safe machine learning, with Kshitij and Hendrik is accepted to ECML PKDD 22.

I’m visiting Andrew Cropper at Oxford.

I have joined the Algorithmics group at the Delft University of Technology as an Assistant Professor!

Join Behrouz, Parisa, Alex and me on our Combining Learning and Reasoning - Programming Languages, Formalisms, and Representations workshop at AAAI 22

I gave a talk on what abstraction can do for program induction at the Automated Verification group, Oxford University. slides

I gave a talk on what abstraction can do for program induction at CoCoSci lab, MIT. slides

Our work on knowledge refactoring for program induction is accepted to AAAI 21.

Our work with Teal Partners on using automated reasoning for payroll management is accepted to IAAI 21.

I will be giving a tutorial on neuro-symbolic AI at AAAI 21 with Luc, Giuseppe and Robin. Stay tuned!

A paper on tackling noise in semi-supervised clustering accepted to ECML 2020 in Ghent, Belgium.

Three papers accepted at IJCAI 2020 in Kyoto, Japan.

I’m speaking at the Decision Analytics Closing Symposium about constraint solving with Z3

I’m speaking at the Aritificial Intelligence Applied in Industry symposium about our work with Skyline Communications

I’m honoured that my PhD thesis has been awarded a honourable mention for the EurAI Distinguished Dissertation Award 2018!

I’m honoured to be among the Distinguished Program Committee at IJCAI 2019!

Two papers accepted at IJCAI 2019 - Learning Relational Representations with Auto-encoding Logic Programs and A Comparative Study of Distributional and Symbolic Paradigms for Relational Learning!