Teddy Lazebnik
Prof' Teddy Lazebnik is a applied mathematics and computer science researcher with extensive experience leading RnD teams in both the life sciences and financial domains. Over the past decade and a half, Teddy has honed his software development skills, including nine years of experience managing development teams of up to fourteen professionals. Teddy has a proven track record in system architecture, developing production-ready algorithms, and collaborating with clients. His expertise includes bio-physical simulations, big data analysis, and data analysis for information systems. His research is focused on applying advanced mathematics and computer science to the life sciences and socio-economic domains, covering areas such as AI-driven personalized treatment protocols, drug discovery, eXplainable AI, socio-economic systems modeling and simulation, and optimal policy detection from financial data.
Session
Unmanned vassals, from ships to mini-submarines, shaping the new age of marine warfare. However, this transformation, occurring in traditional and high-risk environment, should be both better and transformative from our current state to the future. To this end, we developed admiral-driven machine learning framework for marine operations and resource allocation. This frameworks allows to produce admiral approved solution while still using state-of-the-art machine learning methods to obtain mathematical optimum for different needs. In this talk, we discuss the process we followed to developed this framework with real-world examples, sampled data from secret operation, and the code that could make it all happen.