报 告 人: Alexander Boukhanovsky
Alexandra Klimova
Associate Professor
ITMO University
Dr. Nikolay O. Nikitin
Associate Professor
ITMO University
主 持 人:张牧涵 助理教授
55世纪官方登录入口
时 间:2024/1/17 10:00 - 12:00
地 址:55世纪官方登录入口资源西楼2201会议室
报告题目:Artificial Intelligence: Industrial Applications, Education, and Open Source
报告摘要:
Title: Generative AI for industrial applications
AI Research center in ITMO University was founded in 2021 as a part of Russian Federal Project “Artificial Intelligence”. The main topic of its activity is the development of AI technologies to reproduce the creative activity of domain specialists (e.g. designer, engineer, operator) for various industrial areas. Basic technologies of the center are generative AI joined with advanced AutoML techniques with allow to compose complex simulation models over the data. The talk is covered several approaches of generative AI to industrial problems, e.g. tunning of industrial LLMs, design of architectural projects, scheduling over strong uncertainty, generation of data-driven digital twins of technical systems and (even) the customers of technologies. Assessment of generative AI using in real industrial projects (such as urban development and oil and gas industry).
Title: Higher Education and Continuing Education Courses in AI: ITMO experience
Education and training in the field of Artificial Intelligence is one of the key priorities of all countries today. I will briefly talk about several key initiatives from the Russian Federation governement and industry, and discuss how they have changed educational landscape there. Then I will precent several initiatives from ITMO which helped us to manage AI education and related activities at our University. I will talk about AI Expert Counsil, AI Competence Framework, and some instruments that might be used for AI educational properties.
Title: Reproducibility of Scientific Research in AI/ML using Open Source: Experience of ITMO Ecosystem
The research reproducibility crisis is particularly arising in AI and ML. One of the ways to solve this problem is to introduce the culture of open source code, data and models into the scientific sphere. I will talk about how I have been helping to turn ITMO University research results into open source libraries and frameworks for several years. We will discuss both the technical aspects of bringing AI solutions into Open Source and the nuances of developing an open source ecosystem community in an academic environment.
报告人简介:
Professor Alexander Boukhanovsky is a head of national-level AI research center and dean of School of Translational IT in ITMO University. Не has Ph.D. (Cand.Sc.) degree in physics and mathematics, and Dr.Sc. degree in computer science. Нe was a fellow in Lisbon Technical University (Portugal) and Institute of Advanced Studies (Netherlands), and has been working in ITMO University since 2006. Experienced in AI, data-driven modeling and complex system simulation. Head of mathematics section of Russian Scientific Foundation (2019-2023). He has 40 successfully graduated Ph.D.
Alexandra Klimova is an Associate Professor from ITMO University and Vice Dean of School of Translational IT. Was a fellow of a Scholarship of the President of the Russian Federation for Students and PhD Students Training Abroad; Glasgow Caledonian University (Great Britain) was a host organization. She has been working in ITMO University since 2011. Experienced in management of educational and scientific international projects organized in the framework of Erasmus Mundus, ENPI CBC, Tempus initiatives, etc. Participated in development of the first double degree educational programme in CS in Russia. In 2014-2017 was an invited scholar at University of Lorraine, giving a cource in Academic writing. Her current area of experteese is AI educational programs. She is an executive secretary of AI Expert Council in ITMO and project leader in AI Education project in ITMO.
Dr. Nikolay O. Nikitin is an Associate Professor and Head of AutoML Lab at the Research Center “Strong AI in Industry”. in ITMO University. Nikolay has completed his thesis devoted to the methods and technologies of local dynamic tuning for metocean models and defended a Ph.D. at the end of 2020. The main areas of interest include automated machine learning, meta-optimization and generative design.