Panagiotis Misiakos

e-mail:
Office: CAB H 81.2
Universitätstrasse 6
Zürich, Switzerland

I am a PhD student of Markus Püschel. My research interests include applications of mathematics in Signal Processing and Machine Learning. Currently, I am working on DAG learning methods from a causal Fourier analysis perspective.

Publications

2025

SpinSVAR: Estimating Structural Vector Autoregression Assuming Sparse Input
Panagiotis Misiakos and Markus Püschel
In The 41st Conference on Uncertainty in Artificial Intelligence (UAI) 2025.
[pdf] [poster]

Learning Time-Varying Graphs from Data with Few Causes
Panagiotis Misiakos and Markus Püschel
In Proc. International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2025.
[pdf] [poster] [slides]

The CausalBench challenge: A machine learning contest for gene network inference from single-cell perturbation data
Mathieu Chevalley, Jacob Sackett-Sanders, Yusuf H Roohani, Pascal Notin, Artemy Bakulin, Dariusz Brzezinski, Kaiwen Deng, Yuanfang Guan, Justin Hong, Michael Ibrahim, Wojciech Kotlowski, Marcin Kowiel, Panagiotis Misiakos, Achille Nazaret, Markus Püschel, Chris Wendler, Arash Mehrjou, Patrick Schwab
Conference on Causal Learning and Reasoning (CLeaR), Proc. Machine Learning Research 275, pp. 1–19, 2025.
[arXiv]

2024

Learning signals and graphs from time-series graph data with few causes
Panagiotis Misiakos, Vedran Mihal, Markus Püschel
Oral presentation in Proc. International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2024.
[pdf] [presentation]

2023

Learning DAGs from Data with Few Root Causes
Panagiotis Misiakos, Chris Wendler, Markus Püschel
Advances in Neural Information Processing Systems 2023.
[pdf] [poster] [short slides]

Learning Gene Regulatory Networks under Few Root Causes assumption
Panagiotis Misiakos, Chris Wendler, Markus Püschel
3rd prize award in GSK.ai CausalBench Challenge 2023, hosted in MLDD workshop ICLR 2023.
[OpenReview] [arXiv] [slides]

2022

Neural Network Approximation based on Hausdorff distance of Tropical Zonotopes
Panagiotis Misiakos, Georgios Smyrnis, Georgios Retsinas, Petros Maragos
In International Conference on Learning Representations (ICLR) 2022.
[pdf] [poster] [slides]

2020

Diagonalizable Shift and Filters for Directed Graphs Based on the Jordan-Chevalley Decomposition
Panagiotis Misiakos, Chris Wendler, Markus Püschel
Proc. International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2020.
[pdf] [poster]

Talks

2025

SpinSVAR: Estimating Structural Vector Autoregressions Assuming Sparse Input
Seminar for statistics group, ETH Zurich. May 2025

Learning Graphs from Structural Vector Autoregressions with Sparse Input
GSP workshop, Mila-Quebec AI institute. May 2025

2024

Learning Directed Acyclic Graphs from Data with Few Root Causes
Antonio Ortega's group, University of Southern California. Dec 2024

Teaching

Spring 2025, Head TA in Information Retrieval
Fall 2024, Head TA in Information Systems for Engineers
Spring 2024, Head TA in Information Retrieval
Fall 2023, teaching assistant in Information Systems for Engineers
Spring 2023, teaching assistant in Information Retrieval
Fall 2022, teaching assistant in Algorithms and Data Structures
Spring 2022, teaching assistant in Introduction to Machine Learning

Education

Master (M.Eng.) in Engineering.
School of Electrical and Computer Engineering, National Technical University of Athens, Greece.
Thesis (in Greek) supervised by Prof. Petros Maragos.

November 2021