Piotr Kamil Kotlarz

Position at the ZHAW

Research Assistant

Educational background

Master of Science, Quantitative Finance, 2018, Vienna University of Economics and Business
Bachelor of Science, Business, Economics and Social Sciences, 2016, Vienna University of Economics and Business

• Strengthening Swiss Financial SMEs through Applicable Reinforcement Learning / Team member / Project ongoing
• COST Action Fintech and Artificial Intelligence in Finance - Grant Holder / Team member / Project ongoing
• Towards Explainable Artificial Intelligence and Machine Learning in Credit Risk Management / Team member / Project ongoing
• Decentralized financing of Fairtrade producers using a blockchain-based solution / Team member / Project ongoing
• Currency hedging for SMEs and pension funds / Team member / Project ongoing
• Digitalisation non-bankable assets (specifically: art) / Team member / Project completed
• Deep Learning & Neuronal Networks: Selbstständige KI-Agenten zur Entwicklung von neuartigen Handelsstrategien im Asset Management auf Basis von Self-Play / Team member / Project completed
• 4th Conference Finance and Industry 2019 / Team member / Project completed
• European Workshops in Finance / Team member / Project completed
• FIN-TECH – Financial Supervision and Technology Compliance Training Programme / Team member / Project completed
• Big Data Analytics Research / Team member / Project completed
• Mathematics and Fintech: The next revolution in the digital transformation of the finance industry / Team member / Project completed

• Posth, Jan-Alexander; Kotlarz, Piotr Kamil; Hadji Misheva, Branka; Osterrieder, Jörg; Schwendner, Peter,

  2021.

  The applicability of self-play algorithms to trading and forecasting financial markets.

  Frontiers in Artificial Intelligence.

  4(668465).

  Available from: https://doi.org/10.3389/frai.2021.668465

• Posth, Jan-Alexander; Hadji Misheva, Branka; Kotlarz, Piotr Kamil; Osterrieder, Jörg; Schwendner, Peter,

  2020.

  The applicability of self-play algorithms to trading and forecasting financial markets : a feasibility study.

  SSRN.

  Available from: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3737714

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