Matija PaschMathematics Institute, University of Munich Email: pasch@math.lmu.de Tel: +49 (0)89 2180 4609 |
I am a PhD student under the supervision of Prof. Dr. Konstantinos Panagiotou.
Office hours: Appointment upon request by email.
Teaching
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Lineare Algebra und analytische Geometrie II (nicht-vertieft) mit Übungen (Summer term 2023)
Research
I focus on phase transitions in random constraint satisfaction problems, mostly the random binomial, uniform and regular models for fixed arity. Naturally, this research interest extends to spin glasses. Related questions for (graphical) inference problems and channel coding pique my curiosity, too. Recently, also some topics in random matrix theory caught my attention. Moreover, I study the limiting dynamics of probabilistic versions of compartmental models in epidemiology, which allow for more complex interactions and more granular parametrizations.
Publications
Refereed Conference Publications
- Coja-Oghlan, Amin/Hahn-Klimroth, Max/Loick, Philipp/Müller, Noela/Panagiotou, Konstantinos/ Pasch, Matija, 2021, Inference and Mutual Information on Random Factor Graphs, 38th International Symposium on Theoretical Aspects of Computer Science (STACS 2021), doi: 10.4230/LIPIcs.STACS.2021.24.
- Panagiotou, Konstantinos/Pasch, Matija, 2019, Satisfiability Thresholds for Regular Occupation Problems, 46th International Colloquium on Automata, Languages, and Programming (ICALP 2019), doi: 10.4230/LIPIcs.ICALP.2019.90.
Manuscripts Under Preparation
- Heckel, Annika/Kaufmann, Marc/Müller, Noela/Pasch, Matija, 2023, The hitting time of clique factors, https://arxiv.org/abs/2302.08340.
- Panagiotou, Konstantinos/Pasch, Matija, 2023, Satisfiability Thresholds for Regular Occupation Problems, https://arxiv.org/abs/1811.00991v3.
- Panagiotou, Konstantinos/Pasch, Matija, 2022, Mutual Information, Information-Theoretic Thresholds and the Condensation Phenomenon at Positive Temperature, https://arxiv.org/abs/2207.11002.
- Panagiotou, Konstantinos/Pasch, Matija, 2022, The Evolution of an Epidemic in a General Stochastic Compartmental Model.