athanasiospolimeridis



Personal Websites

Athanasios Polimeridis

Athanasios (Thanos) Polimeridis is an Assistant Professor at Skolkovo Institute of Science and Technology (Skoltech), and the principal investigator of the Computational Prototyping Group.  He received the Diploma and the Ph.D. degrees in electrical engineering and computer science from the Aristotle University of Thessaloniki, Greece, in 2003 and 2008, respectively. Prior to joining Skoltech, he held research positions in Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland and Massachusetts Institute of Technology (MIT), Cambridge, MA, USA.

His research interests revolve around computational methods for problems in physics and engineering (classical electromagnetics, quantum and thermal electromagnetic interactions, and magnetic resonance imaging), with an emphasis on the development and implementation of integral-equation-based algorithms.

  • Simulation and modeling for magnetic resonance imaging
  • Simulation and modeling for quantum/thermal fluctuating phenomena (Casimir forces, radiative heat transfer, fluorescence)
  • Computational electromagnetics
  • Integral equations
  • Optimization and inverse problems
  • Fast algorithms

Swiss National Science Foundation Fellowship for Advanced Researchers in 2012

mikhaillitsarev
Mikhail Litsarev
Research Scientist

Introduction to Numerical Simulation
Number of ECTS credits: 6
Course Classification: Science, Technology, and Engineering

Course description:
This course is an introduction to computational techniques for modeling and simulation of a large variety (e.g. aerospace, mechanical, electrical, energy and biomedical) of engineering and physical complex systems
Topics include techniques for automatic assembly of mathematical problems from physics’ principles; sparse, direct and iterative solution techniques for steady state analysis of linear complex systems; Newton methods for nonlinear systems; Time domain and periodic steady state simulation; techniques for model order reduction of complex dynamical systems.
The focus is on a learn-by-doing philosophy.

Prerequisites:
Solid background in differential equations and linear algebra.
Some very basic programming experience in Matlab (we will provide tutorials and support for Matlab) or alternatively a high level of fluency and independence in any other programming language of choice (we will not provide any support for other languages)

 

Great Computational Methods
Number of ECTS credits: 6
Course Classification: Science, Technology, and Engineering

Course Description
This course is an introduction to computational techniques for modeling and simulation of a large variety (e.g. aerospace, mechanical, electrical, energy and biomedical) of engineering and physical complex systems
Topics include techniques for automatic assembly of mathematical problems from physics’ principles; sparse, direct and iterative solution techniques for steady state analysis of linear complex systems; Newton methods for nonlinear systems; Time domain and periodic steady state simulation; techniques for model order reduction of complex dynamical systems.
The focus is on a learn-by-doing philosophy.

Intended Learning Outcomes
Upon completion of this course, the student will be able to:
Recognize and formulate mathematical structures (e.g. conservation laws and constitutive equations) common to a lot of complex engineering and physical systems, intended as networks of interconnect dynamical components (e.g. mechanical and structural frames, oil/blood/heat transport networks, integrated circuits and nation-wide electrical energy transport networks, bio-chemical reaction networks and many others)
Select, implement and if needed modify the appropriate type of formulation (e.g. nodal analysis, node-branch) for the description of complex systems.
Select (and modify) or implement an appropriate steady state solver (e.g. sparse LU vs. iterative methods) for a given linear or linearized complex system description
Select, implement and modify an appropriate strategy (e.g. damping, source/load stepping, homotopy, etc.) to facilitate initialization and convergence of a Newton solver for a given nonlinear complex system
Select and implement an appropriate integrator (e.g. implicit vs. explicit, lower order vs. high order, stable vs. A-stable) for the time domain simulation of a given complex system

ФИО: Полимеридис Атанасиос

Занимаемая должность (должности): Старший Преподаватель

Преподаваемые дисциплины: Вычислительные методы

Ученая степень: Ph.D. Электротехника и информатика, 2008, Аристотелевский институт Салоники, Греция

Ученое звание (при наличии): нет

Наименование направления подготовки и/или специальности: Электротехника и информатика

Данные о повышении квалификации и/или профессиональной переподготовке (при наличии): нет

Общий стаж работы: 12 лет

Стаж работы по специальности: 12 лет