Jeremias Berg receives the 2020 Doctoral Research Award of the Association for Constraint Programming.
Jeremias Berg of the Constraint Reasoning and Optimization Group has been awarded the 2020 Doctoral Research Award of the Association for Constraint Programming (ACP) for his PhD thesis Solving Optimization Problems via Maximum Satisfiability: Encodings and Re-Encodings.
-I am very happy and honoured for the recognition. I would like to thank my PhD supervisor Matti Järvisalo whose great supervision was instrumental in enabling my PhD research. I am also very grateful toward the Doctoral Programme in Computer Science and Petri Myllymäki for the role he played in providing me the financial security of completing the thesis. I would also like to thank all of my collaborators; working with all of you has been very rewarding, says Berg.
The ACP Doctoral Research Award is awarded annually to a promising young researcher working in the area of constraint programming and who defended his/her thesis within the previous two years.
Currently Berg continues his research as a postdoc in the Constraint Reasoning and Optimization group at University of Helsinki and Helsinki Institute for Information Technology HIIT.
Berg gives an invited award talk at CP 2020, the main international conference on constraint programming, on September 11. 2020.
With his thesis, Berg contributes to this progress by advancing the theory and practice of preprocessing in the context of MaxSAT, and presents novel MaxSAT-based approaches for the exact solution of two relevant computational problems stemming from the field of machine learning and data analysis. The contributions presented in the thesis have already been published at top peer-reviewed international venues, including Artificial Intelligence Journal and the IJCAI, AISTATS, ECAI, and CP conferences.
Constraint programming in itself is a major research area in computer science and artificial intelligence, studying and developing generic problem solving techniques through declarative means. Indeed, from e.g. formal verification of safety-critical hardware and software systems to optimizing the use of natural, human and financial resources in various real-world settings, constraint solving is a critical core technology that enables automatically and efficiently solving hard search and optimization problems underlying real-world and industrial settings at large.