On this page you can find the slides of most of the talks I have given, including both technical conference presentations as well as more general presentations directed toward a wider audience.
I was very happy to receive the 2020 ACP doctoral award from the association of constraint programming (the ACP). I gave a talk regarding my thesis research at the CP conference in 2020. The slides can be found here and the prerecorded video of the talk here.
Lectio Praecursoria a 20 minute presentation given at the start of my thesis defence. The presentation is intended for people without a background in the field.
During my research visit to Melbourne in the autumn of 2018 I gave two, slightly more technical, overviews of my thesis work. One focusing on the MaxSAT encodings, in the CIS seminar at the University of Melbourne and one on the MaxSAT preprocessing in the DATA61 seminar at Monash university.
During my research visit to Toronto I gave another talk regarding my thesis, specifically about the MaxSAT encodings in it.
Invited Talks & Tutorials
These are longer scientific talks that are not bound to a single publication.
- Advances in Maximum Satisfiability, a tutorial at ECAI 2020 given together with Ruben Martins and Matti Järvisalo. The tutorial webpage can be found here.
- Maximum Satisfiability Solving, a revised and updated version of the ECAI tutorial given at the Beyond Satisfiability workshop of the Simons Institute. A recording of the talk can be found here.
These are presentations of my papers. The title of each presentation is equal to the title of the paper. These are all fairly technical and assume familiarity with the research field.
- Abstract Cores in Implicit Hitting Set MaxSat solving and its 5-minute long pitch talk, presented at SAT 2020. As the conference was online, there is actually a video of me presenting it available as well.
- Preprocessing in Incomplete MaxSAT solving presented at ECAI 2020. As the conference was online, there is a video of me presenting it as well.
- Bounded Treewidth Bayesian Network Structure Learning with Maximum Satisfiability, presented at the Logic Seminar at the Department of Mathematics and Statistics of the University of Helsinki.
- Minimum-Width Confidence Bands via Constraint Optimization presented at CP 2017
- Weight-Aware Core Extraction in SAT-Based MaxSAT Solving, presented at CP 2017
- Impact of SAT-Based Preprocessing on Core-Guided MaxSAT Solving, presented at CP 2016
- Subsumed Label Elimination for Maximum Satisfiability, presented at ECAI 2016
- Re-Using Auxiliary Variables for MaxSAT Preprocessing, presented at ICTAI 2015
- Improving the Effectiveness of SAT-Based Preprocessing for MaxSAT, presented at IJCAI 2015
- SAT-Based Approaches to Treewidth Computation: An Evaluation presented at ICTAI 2014
- (Cost-) Optimal Correlation Clustering via Max-SAT presented at ICDMW 201
In addition to the ones listed above, I have also presented papers at the following venues.
- I gave a talk at the academy club of the Young Academy of Finland titled (NP-kovaa) Optimointia Deklaratiivisesti
- Oral Presentation: MaxPre: An Extended MaxSAT Preprocessor, at SAT 2016
- Poster Presentation: Learning Optimal Bounded Treewidth Bayesian Networks via Maximum Satisfiability. at the Machine Learning Summer School (MLSS), 2015
- Poster Presentation: Learning Optimal Bounded Treewidth Bayesian Networks via Maximum Satisfiability at AISTATS 2014
Non technical presentations
- Hur svårt kan det vara (in Swedish), an informal introduction to reductions and NP-completeness using SAT and Sudoku aimed at an audience with practically no background.
- Intuition in mathematics (in Swedish), a collection of examples designed to challenge the idea and intuition of mathematics that many high school students have. The example that worked really well was the mothy hall paradox. (in Swedish)
- NaNu (in Swedish), an informal introduction to neural networks, explanations and adversarial examples, aimed at high school students and undergraduate students in all sciences.
- Voivatko tietokoneet ajatella ihmimäisesti? (in Finnish), an introduction to artificial intelligence and machine learning aimed at 9 to 12 year old kids. I presented this as a part of the meet a researcher initiative of the Young Academy of Finland.