Mikhail Krinitskiy is the head of the Laboratory of Machine Learning in Earth Sciences in Moscow Institute of Physics and Technology. He is a researcher at the Shirshov Institute of Oceanology and a lecturer at the Moscow Institute of Physics and Technology (MIPT), where he teaches courses on machine learning and deep learning for Earth Sciences. His academic background spans physics, applied mathematics, and computer science, and his current research focuses on the development and deployment of AI models for oceanographic and atmospheric analysis, weather forecasting, and climate modeling. He has been actively involved in national and international initiatives aimed at advancing data-driven Earth system modeling, with a particular emphasis on foundation models and hybrid modeling approaches that integrate physics and machine learning.

In the Lab, Mikhail coordinates interdisciplinary projects that bridge the gap between environmental sciences and conm=temporary AI, including the creation of open-source platforms and training datasets for the geoscience community. His work combines theoretical insights with practical deployment on high-performance computing infrastructure, and he is a frequent speaker at conferences dedicated to machine learning in Earth sciences. He also contributes as a reviewer to leading scientific journals in the field and mentors graduate students engaged in cutting-edge AI research for environmental monitoring and prediction.