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Profile

Piotr Szymański

Assistant Professor

Piotr Szymański
urban data sciencespoken language understandingnatural language processingrepresentation learning

Research groups

Piotr Szymański is an assistant Professor at the Department of Artificial Intelligence at the Wrocław University of Science and Technology and a Machine Learning Engineer at Avaya. Professionally involved in data analysis, statistical reasoning, geospatial data science, natural language processing, machine learning and artificial intelligence techniques.

He is an alumni of the Top 500 Innovators program at Stanford University, worked in several institutions over the years incl. Hasso Plattner Institute in Potsdam, Josef Stefan Institute in Ljubljana, University of Notre Dame and University of Technology Sydney. He is the author of http://scikit.ml - a popular python library for multi-label classification, and https://github.com/niedakh/pqdm/ - a parallel processing wrapper for tqdm.

Apart from multi-label classification, Piotr published papers concerning urban data, traffic analysis and bridging the gap between ASR and NLP in spoken language understanding systems. In his free time he is an urban activist in Wrocław - chairing the [http://tumw.pl](Society of Beautification of the City of Wrocław), and a member of Wrocław city [http://brochow.wroclaw.pl](distric council of Brochów).

Recently he became a member of the international group which models coronavirus spread: http://mocos.pl, which publishes regular reports about the state of the pandemic in Poland and also analysis of related phenomena.

Education

2008

MsC in Computer Science

Wroclaw University of Science and Technology

Publications(39)

Mitigation and herd immunity strategy for COVID-19 is likely to fail

Marek Bawiec, Viktor Bezborodov, Marcin Bodych, Tyll Krüger, Agata Migalska, Barbara Pabjan, Tomasz Ożański, Ewaryst Rafajłowicz, Wojciech Rafajłowicz, Ewa Skubalska-Rafajłowicz, Sara Ryfczyńska, Piotr Szymański, Barbara Adamik, Wolfgang Bock, Jan Pablo Burgard, Thomas Götz, Ewa Szczurek

Raporty Katedry Automatyki, Mechatroniki i Systemów Sterowania. 2023, Ser. PRE, nr 3, 25 s.

2023

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