Applied AI for sustainable development

Overview

Abstract

Skoltech Applied AI center’s mission is to create AI models and frameworks for solving the problems of sustainable development of industry and economy. The frameworks include a multi-modal data fusion framework, a science-informed machine learning framework, and a green AI framework (acceleration and optimization of big DL models). The frameworks use algorithms resulting from fundamental research on generative modeling, manifold learning, topological data analysis, Bayesian modeling and optimization, and other modern directions of machine learning considered in the center. The main applied problems include forecasting the economic consequences of the onset of physical risks, improving AI computing performance, self-learning reservoir model for oilfield service technologies, monitoring, and forecasting air pollution, forecasting the ice situation in the Arctic region, and remote sensing monitoring for assessing natural disasters, change detection, etc. In my presentation, I will overview the current center's activities, applied and fundamental problem statements, and corresponding recent results.

Brief Biography

Evgeny Burnaev is a Full Professor, Director of the Research Center in artificial intelligence in the direction of optimization of management decisions to reduce the carbon footprint at Skolkovo Institute of Science and Technology (Skoltech), Russia.  Since 2016 Evgeny Burnaev is an Associate Professor in Skoltech CDISE and a head of Advanced Data Analytics in Science and Engineering group. Evgeny’s current research focuses on the development of new algorithms in machine learning and artificial intelligence such as deep networks for an approximation of physical models, generative modeling, and manifold learning, with applications to computer vision and 3D reconstruction, neurovisualization. The results are published in top computer science conferences (ICML, ICLR, NeurIPS, CVPR, ICCV, and ECCV) and journals.