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Joined the MINDS research group at RUG as part of the European post-digital training network. The post-digital network's goal is to facilitate the interdisciplinary education and research needed for the design and development of unconventional computing systems. At MINDS, we try to understand how intelligent information processing can arise from dynamics in nonlinear material substrates. We are working toward a fundamental theory of computing in brainlike materials, grounded both in physics and mathematics.
Studied computer science with a focus on artificial intelligence and deep neural networks. Won Dean's best thesis award for thesis on "Automated Architecture Design for Deep Neural Networks" (see publications).
Spent one semester at Carnegie Mellon, taking graduate-level courses in artificial intelligence and deep learning and working in the DELPHI research group (see below).
Studied physics and mathematics for one year before transferring to Jacobs University Bremen.
- Introduction to Computer Science, Fall '17
- Algorithms and Data Structures, Spring '18
- Machine Learning, Spring '19 (as head TA)
Spent three summer internships at Bloomberg LP. Worked in the software engineering department on different machine learning projects with financial derivatives.
Worked in London 2018, in New York 2019, in London 2020.
Worked in the DELPHI research group at CMU on epidemiological forecasting using machine learning methods. Worked with two PhD students on expanding the existing nowcasting system for influenza to dengue and norovirus.
Worked part-time during the semester and full-time during the summer break as a software developer on cross-platform mobile applications.