Key dates

Registration deadlines extended!
Early registration:
  • before May 20, 2012
Late registration:
  • before June 20, 2012
AACIMP-2012:
  • August 3 to 16
Want to promote Summer School AACIMP in your University? Nice Idea! Then the following files are for you:
Poster of the Summer School
Information leaflet
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Operational Research Stream

Operations Research is a rapidly developing mathematical science that applies advanced analytical methods to help make better decisions. It is successfully used by business, military and government structures since its foundation in the middle of 20th century. OR provide decision-makers with more complete data, it helps to focus on optimal solutions, measure risk and use modeling to forecast results of different decisions.

This year we would like to focus our participants’ attention at such important subject of OR as data mining.

Data mining provides techniques to find useful information in large sets of data to improve decision making. It is an answer to the modern world and modern methods of doing researches and discoveries, where the amount of information available increases with exponential speed. Today the main problem of analysts in many fields is not to get more information, but to learn how to work and understand the existing and turn it into usable knowledge. With methods of data mining you may achieve better understanding of complex systems, what is crucible for effective decision making. Successful implementation of data mining tools every day brings large benefits to super-market networks, logistics business and internet companies.

Besides courses on data mining, some courses and lectures on other important field of operational research such as financial mathematics and combinatorial optimization will be proposed to our participants' attention.

Program

  1. Data mining (approximately 25 h)
    1. Introduction to Data Mining
    2. Special Applications of Data Mining Techniques
  2. Optimization. Combinatorial Optimization (approximately 15 h)
  3. Financial Mathematics (approximately  8 h)

 

Tutor
Course

Prof. Sergiy Butenko
Department of Industrial and Systems Engineering, Texas A&M University, USA

is expected to participate
Complex Network Analysis

Detailed information about the course will be available later.

Prof. Boris Goldengorin
Higher School of Economics Branch in Nizhny Novgorod, Russia
Combinatorial Optimisation

Detailed information about the course will be available later.

Dr. Erik Kropat
Universität der Bundeswehr München, Germany
Special Applications of Data Mining Techniques

Within this course, participants will further improve their understanding of the Data Mining by studying its various up-to-date applications, such as: Social Network Analysis, Crime Data Analysis, Bioinformatics, Data Farming and Open Source Intelligence.

Detailed information about the course will be available later.

Prof. Alexander Makarenko
Institute for Applied System Analysis of NTUU KPI, Ukraine
Concepts and Mathematical Models of Consciousness

Consciousness research is one of the main directions of modern science. This rapidly developing field may cause the next scientific revolution. In the proposed lecture we will review the existing models and concepts of Consciousness as well as some prospective ideas including new concept of Anticipating Neural Networks and their relations to understanding of Consciousness.

Also we will discuss some other subjects of Operational Research that are practically connected: Neuroscience and Modelling of Socio-economical systems which include the using of Consciousness.

Detailed information

Prof. Panos Pardalos
Industrial and Systems Engineering, University of Florida, USA
Combinatorial Optimisation

Detailed information about the course will be available later.

Prof. Oleg Prokopyev
Department of Industrial Engineering, University of Pittsburgh, USA
Combinatorial Optimization, Integer Programming

Detailed information about the course will be available later.

Konstantin Tretyakov
Department of Computer Science, Tartu University, Estonia
Introduction to Data Mining

Data mining (which is often referred to as the machine learning, pattern analysis and frequently defined bymany other names) is one of central disciplines of modern-day computational science. Data mining deals with the problem of extracting (or "learning") "knowledge", "models", "algorithms" or other types of useful information from raw data.

The course aims to give an overview of basic data mining and machine learning techniques. We shall discuss both theoretical basis and practical implementation as well as application issues of data mining.

Detailed information

Dr. Gerhard-Wilhelm Weber
Department of Financial Mathematics and Department of Scientific Computing, Institute of Applied Mathematics, Middle East Technical University, Ankara, Turkey
Financial Mathematics

Financial mathematics is another discipline with plenty of applications. It uses mathematical (and in particular stochastic) methods and models for conducting financial estimations, forecasting of financial markets and analysis of financial risks. Modern work banks, stock markets, investment funds and others financial companies can’t be imagined without regular use of tools that financial mathematics provides. It can give you better understanding of economic processes and advise you how to manage your financial instruments more profitable.