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Anastasios Kratsios focuses on the geometric foundations of artificial intelligence, particularly in applications related to finance, control, and partial differential equations (PDE). His research delves into analytic statistical foundations of deep learning, emphasizing the understanding of behavior models and their rigorous modification. He explores efficient encoding structures that arise in finance, stochastic processes, and game theory. Kratsios has contributed to several significant publications in the field, including works on metric embeddings, optimal transport, and universal approximation theorems. He is actively involved in mentoring students and hosting seminars that discuss the latest developments in AI theory. Through these initiatives, he fosters a collaborative environment that encourages research in deep learning and its applications across various domains.
University of Toronto • Toronto, ON, Canada
Conducting research and teaching in areas related to AI, game theory, and finance.
Department of Sociology