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Paulius Dilkas

I am a Research Fellow at the School of Computing of the National University of Singapore, hosted by Kuldeep S. Meel. I received my PhD in Robotics and Autonomous Systems jointly from the University of Edinburgh and Heriot-Watt University, supervised by Vaishak Belle. I received my MSci in Computing Science degree from the University of Glasgow.

I am interested in discrete algorithms that count and compute sums of products from a logic-based description of the problem. Specifically, my recent work is on weighted model counting (i.e., a weighted version of #SAT) and first-order model counting. Algorithmic techniques used to solve these problems include dynamic programming, knowledge compilation, and various representations of Boolean and pseudo-Boolean functions. Solving such model counting problems efficiently is crucial for many areas of artificial intelligence (AI) such as explainable AI, neural-symbolic AI, probabilistic programming, and statistical relational AI. Other applications include bioinformatics, data mining, natural language processing, prognostics, and robotics. I am also interested in graph algorithms, constraint satisfaction, and search algorithms. Previously, I have worked on graph algorithms, algorithm portfolios, formal modelling with bigraphs, and inverse reinforcement learning.


Paulius Dilkas, Vaishak Belle. Synthesising Recursive Functions for First-Order Model Counting: Challenges, Progress, and Conjectures. KR 2023
paper video slides code
Paulius Dilkas. Generating Random Instances of Weighted Model Counting: An Empirical Analysis with Varying Primal Treewidth. CPAIOR 2023
paper slides code
Paulius Dilkas, Vaishak Belle. Weighted Model Counting Without Parameter Variables. SAT 2021
paper video slides code
Paulius Dilkas, Vaishak Belle. Weighted Model Counting with Conditional Weights for Bayesian Networks. UAI 2021
paper supplement video slides poster code
Paulius Dilkas, Vaishak Belle. Generating Random Logic Programs Using Constraint Programming. CP 2020
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Theses, Dissertations, and Reports

Generalising Weighted Model Counting (supervised by Vaishak Belle, 2023)
PhD thesis slides
Variational Inference for Inverse Reinforcement Learning with Gaussian Processes (supervised by Bjørn Sand Jensen, 2019)
MSci report slides code
Nondeterministic Bigraphical Reactive Systems for Markov Decision Processes (supervised by Michele Sevegnani, 2018)
internship report slides code
Algorithm Selection for Maximum Common Subgraph (supervised by Ciaran McCreesh and Patrick Prosser, 2018)
BSc dissertation slides code
Clique-Based Encodings for Graph Edit Distance (supervised by Ciaran McCreesh, 2017)
internship report slides code


At the School of Informatics, University of Edinburgh, I worked on the following courses:
At the School of Computing Science, University of Glasgow I worked as a demonstrator for the following courses:
Before that, I worked as a Distance Learning Teacher in Mathematics at the National Student Academy in Lithuania


  • 2023
    • UAI 2023 Top Reviewer
  • 2019
    • 3-Year Scholarship from the EPSRC CDT in Robotics and Autonomous Systems
    • MSci Class Prize
  • 2018
    • EPSRC Vacation Scholarship
    • Level 4 Project with Best Product
  • 2017
    • EPSRC Vacation Scholarship
    • Level 3 Honours Class Prize for Computing Science
  • 2016
  • 2015
    • O'Reilly Academic Prize for Best Overall Performance in Assessed Coursework in Level 1 Computing Science
    • Lorimer Bursary Prize