Personal Websites
Alexander Shapeev
Laboratory of Artificial Intelligence for Materials Design
Center for Artificial Intelligence Technology
I have graduated from Novosibirsk State University in 2001 with Bachelor degree and in 2003 with Master degree. I got my PhD from National University of Singapore in 2009 on this topic of computational fluid mechanics.
Through my two postdocs, in EPFL (Lausanne, Swizerland) and the University of Minnesota (USA) I was working on mathematical analysis of coupling of atomistic and continuum description of solids, my work has been award the 2013 SIAM Outstanding Paper Prize. After assuming an Assistant Professor position at Skoltech, my main interest is in development and practical applications of models of interatomic interaction (aka interatomic potentials) with a multidisciplinary approach that combines ideas from computational mathematics, machine learning and physics and has applications in materials science, physics, and chemistry.
You can find more info on my website, including publications.
Read about my research on my website
See my publications on my website
2013 SIAM Outstanding Paper Prize
PhD students, Materials Science: Konstantin Gubaev, Tatiana Kostyuchenko, and Edgar Makarov, Sotskov Vadim
PhD students, Data Science: Evgenii Tsymbalov
MSc students, Materials Science: Ilya Beniya, Vladimir Ladygin
MSc students, Data Science: Mozhdeh Sriranirad, Evgeni Okhmatovski
Numerical Modeling
Number of ECTS credits: 6
Course Classification: Science, Technology, and Engineering
Course description:
Many scientific models are formulated in terms of differential or integral equations and describe continuous quantities, such as the distribution of velocity of a fluid in a space outside an aircraft wing, distribution of stress in a solid body, price of a stock as a function of time, etc. In order to use these models in a computer simulation, the models must be discretized. The course covers a representative selection of methods of discretization of differential and integral equations. The emphasis of the course is on practical aspects of using discretization methods: intuitive understanding and formal derivation of accuracy of different methods, modelling, testing and optimizing real mechanical systems, and solving applications-informed practical problems
Prerequisites:
Numerical linear algebra, knowledge and understanding of Bachelor-level numerical methods for PDEs.
Advanced Materials Modeling
Number of ECTS credits: 6
Course Classification: Science, Technology, and Engineering
Course Description:
The course builds on introductory Computational Chemistry and Materials Modeling course to provide in-depth understanding and advanced-level use of commonly employed modeling methods, as well as teach state of the art methods tailored for modeling of specific classes of materials relevant to multiple major industries in the future, including nanotechnology and energy. The emphasis is on practical use of techniques, algorithms and programs to bridge theory and applications, from the discovery of materials to their use in real-world technologies. Personalized advisory of multiple experts in different areas of computational materials science will allow students to accomplish challenging projects related to their MSc/PhD theses or other research in materials science.
Prerequisites:
Computational Chemistry and Materials Modeling course
ФИО: Шапеев Александр Васильевич
Занимаемая должность (должности): Старший Преподаватель
Преподаваемые дисциплины: Быстрые методы решения дифференциальных и интегральных уравнений
Ученая степень: Ph.D., вычислительная математика, 2009, Национальный Университет Сингапура
Ученое звание (при наличии): нет
Наименование направления подготовки и/или специальности: Вычислительная математика
Данные о повышении квалификации и/или профессиональной переподготовке (при наличии): нет
Общий стаж работы: 13 лет
Стаж работы по специальности: 13 лет