Patrik Reizinger is a Ph.D. student in machine learning at the University of Tübingen and part of the ELLIS and IMPRS-IS doctoral programs. He holds a B.Sc. and M.Sc. in electrical engineering from the Budapest University of Technology, where he specialized in control engineering and intelligent systems. His main research interests include designing AI that can understand cause-effect relationships. In his free time, he tries to decrypt sustainable strategies for earning a Ph.D., which he summarizes in his newsletter, The Path to PhD.   For show notes and transcript visit: https://kk.org/cooltools/patrik-reizinger-doctoral-researcher-in-machine-learning/   If you're enjoying the Cool Tools podcast, check out our paperback book Four Favorite Tools: Fantastic tools by 150 notable creators, available in both Color or B&W on Amazon: https://geni.us/fourfavoritetools

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