Cutting Edge Education for the Digital Future: Convergence of HPC, Big Data, ML and IoT
The Goal
The impressive progress of supercomputer technologies actively contribute to the emergence of many prospective directions for the development of modern science, technology, business and industry. The seminar is oriented on the discussion of the best practices and problems of training highly qualified personnel who can successfully use the high potential of convergence of Superсomputer Technologies, Mathematical Modeling, Big Data, Machine Learning and Cognitive Technologies, Internet of Things in the era of active digital transformation of our life.
Topics of Interest
- Educational programs for training, retraining and advanced training;
- Training courses and laboratory works;
- Master's degree programs;
- Successful experience in training and research projects;
- The potential of e-learning and examples of on-line educational resources;
- Forms and methods of cooperation of scientists, teachers and specialists in the development of new educational materials;
- Best practices of interaction with the IT industry;
- Topics of the workshop and school education
and other related topics.
Within the framework of the seminar, the training programs for the presentation of educational programs, training courses, and laboratory training in the field of supercomputer education may be organized.
Language: Russian, English (without simultaneous translation).
Rules of Paper Submission
Important Dates
April 15April 25 , 2023 - paper submissionMay 15May 25 - author notificationMay 30June 10 - camera ready submission
Program Committee
- Barkalov K.A., UNN (co-chair, academic secretary)
- Sokolinskiy L.B., SUSU (co-chair)
- Boldyrev Yu.Ya., StPPU (co-chair)
- Antonov A.S., MSU
- Bukhanovskiy A.V., ITMO
- Voevodin Vl.V., MSU
- Gazizov R.K., UGATU
- Mashechkin I.V., MSU
- Meyerov I.B., UNN
- Modorskiy V.YA., PSTU
- Popova N.N., MSU
- Yufryakova O.A., NArFU
Contacts
All questions about participating in the workshop should be directed to Konstantin Barkalov, konstantin.barkalov@itmm.unn.ru.