Tutorial Lectures       


Tutorial Speakers:

  • Fuad Aleskerov, National Research University 'Higher School of Economics' and the Institute of Control Sciences of Russian Academy of Sciences, Moscow, Russia

  • Yong Shi, International Academy of Information Technology and Quantitative Management (IAITQM)

  • Francisco Antonio Doria, the Federal University at Rio de Janeiro, Brazil

  • Walter Böddener, Rio 2016™, Brazil

Models for analysis of consumers¡¯ behavior for a large retail network

Fuad Aleskerov
Head, Department of Mathematics for Economics, National Research University Higher School of Economics;
Head, International Laboratory of Decision Analysis and Choice, National Research University Higher School of Economics;
Head, Laboratory of Choice Theory and Decision Analysis, Russian Academy of Sciences Institute of Control Sciences


How can a company or a bank increase the loyalty of customers? How can we attract customers to switch from competing companies? How can we get more profit from our customers?
These questions are continuously studied by all companies, specially retail networks.
In my paper I propose a system of new models to solve the following problems
©¤ an analysis of consumers¡¯ baskets and segmentation of the customers of a large retail firm on the basis of similarity of their consumption;
©¤ an analysis of the sets of goods purchased by the customers of a large retail network, and segmentation of these sets;
©¤ an analysis of the dynamic behavior of customers, and segmentation of customers in terms of their life cycle period, i.e. weather the customer is a leaving, growing or stable one;
©¤ one analysis of how can a retail network return a leaving customer.
These models allow us to solve the above stated problems, and they were used to analyze a real retail network with more than 500,000 customers and more than 1 mln. goods.
We analyzed the data for this network for more than 1 year of functioning on the basis of the customers¡¯ purchases.
We analyzed real Big Data of this network and construct the corresponding very fast algorithms.

Author’s  short biographical note:

1969--1974, Student, Mathematics Faculty, Moscow State University
1981, Ph.D. in Control in Socio--Economic Systems (thesis title ¡°Interval Choice¡±)
1993, Doctor of Science (thesis title ¡°Local Aggregation Models¡±)
- First prize: Vavilov's Scientific Society, 1986.
- Second price: All--Union Exhibition on Advanced Studies, 1989.
- First prize: Popov's Scientific Society, 1989.
- Award ¡°Golden Vyshka¡± by the State University ¡°Higher School of Economics¡± for the scientific achievements, 2004
- Honorary Worker of Science and Technology of Russian Federation, 2011
- Medal of the Order "For Merit II" (Decree of the President of Russia on 21.12.2013)
10 books, more than 200 articles, more than 100 in peer-reviewed journals and volumes
Member of
The Society for Social Choice and Welfare (member of the Council, 2008-2013);
International Economic Association (member of the Executive Council, 2011-2017)
American Mathematical Society;
New Economic Association, Russia
Invited Expert:
1. United Nations environmental summit, Rio de Janeiro, 1991;
2. Administaration of the President of Russia Federation, 1993;
3. Yapi Kredi Bank (Turkey), 1996 ¨C 2001
4. AEG ¡°Metro¡± (Germany), 2007-2008
Many other companies and governmental organizations
Member of Editorial Board for the journals:
- Mathematical Social Sciences,
- Automation and Remote Control,
- Information Technologies and Decision Making,
- Political Studies (TBF),
- Control Problems (in Russian),
- Politeia (in Russian),
- Economic Journal HSE (in Russian),
- Business-informatics (in Russian),
- Journal of New Economic Association (in Russian), vice-editor-in-chief
Invited Speaker: more than 70 conferences and workshops

Big Data and Data Science in ITQM

Yong Shi
International Academy of Information Technology and Quantitative Management (IAITQM)


Big Data has become a reality that no one can ignore. Big Data is our environment whenever we need to make a decision. Big Data is a buzz word that makes everyone understands how important it is. Big Data shows a big opportunity for academia, industry and government. Big Data then is a big challenge for all parties. This talk will discuss some challenges of Big Data application as well as Data Science, the scientific issues behind Big Data. Then, this talk will provide a number of real-life Big Data Applications. Finally, it will outline two journals of ITQM community: International Journal of Information Technology and Decision Making (IJITDM) and Annals of Data Science (AODS).

Author’s  short biographical note:

Yong Shi, serves as the Executive Deputy Director, Chinese Academy of Sciences Research Center on Fictitious Economy & Data Science and the Director of the Key Lab of Big Data Mining and Knowledge Management, Chinese Academy of Sciences. He has been Union Pacific Chair of Information Science and Technology, University of Nebraska at Omaha, USA. Dr. Shi's research interests include business intelligence, data mining, and multiple criteria decision making. He has published more than 23 books, over 300 papers in various journals and numerous conferences/proceedings papers. He is the Editor-in-Chief of International Journal of Information Technology and Decision Making (SCI), Editor-in-Chief of Annals of Data Science (Springer) and a member of Editorial Board for a number of academic journals. Dr. Shi has received many distinguished awards including the Georg Cantor Award of the International Society on Multiple Criteria Decision Making (MCDM), 2009; Fudan Prize of Distinguished Contribution in Management, Fudan Premium Fund of Management, China, 2009; Outstanding Young Scientist Award, National Natural Science Foundation of China, 2001; and Speaker of Distinguished Visitors Program (DVP) for 1997-2000, IEEE Computer Society. He has consulted or worked on business projects for a number of international companies in data mining and knowledge management.


Francisco Antonio Doria
the Federal University at Rio de Janeiro, Brazil


We present and discuss the O'Donnell 1979 algorithm for the solution of NP-complete problems. If P<NP is proved in a theory with greater "provability strength" than Primitive Recursive Arithmetic, the O'Donnell algorithm turns out to be quasi--polynomial. We elaborate on how close to polynomial it might be. O'Donnell's algorithm isn't based on a specific problem in a given NP class, as most standard algorithms for similar problems. Instead it arises out of some very general, abstract considerations about NP-complete problems. Surprisingly, this leads to a very efficient program. For the usual working range (say, around 2 gigabytes), the algorithm behaves as a low-degree polynomial algorithm (given our hypothesis), and can be applied to the solution of a whole fauna of practical problems in the NP-class, e.g. the traveling salesman problem, allocation problems, the knapsack problem, and so on.

Author’s  short biographical note:

Francisco Antonio Doria was born in Rio de Janeiro in 1945. He holds a bachelor's degree in Chemical Engineering from the Federal University of Rio de Janeiro (1968); a master's degree in Physics from the Brazilian Centre for Physics Research (1973); and a doctorate in Physics from the Brazilian Centre for Physics Research (1977). He has extensive experience in Computer Science and has contributed to the following areas: incompleteness of formalized physical theories, gauge field copies, difficult problems and dynamical systems, hypercomputing, and complexity theory. He is an emeritus professor of the Federal University at Rio de Janeiro. With his colleague Newton da Costa they proved that chaos theory is undecidable and Godel incomplete. Also with Newton da Costa they solved the Arnol'd Problems, which belongs to the AMS 1974 list of problems presented at the Symposium on the Hilbert Problems. An interesting example which da Costa and Doria conceived out of their techniques is the proof that there are infinitely many problems in dynamical systems theory which as hard to settle as Fermat's Last Theorem.



Walter Böddener
Rio 2016™, Brazil


The presentation will consist in showing what types of technology are used nowadays in high level Classes sailing events over the world, as the ISAF World Cup, World Championships and Olympic Games. Sailing is a spectacular sport, in which athletes submit their skills to a sailing boat in the sea, using the force of the wind. To show this spectacle more interesting for the spectators, in the last 20 years, a lot of technology has been developed to show spectators on shore what is going on in the water, to explain the sport and to enhance the interest in sailing. Such technology is for example the on water GPS tracking systems, onboard cameras and live coverage in the water with high quality images. Tracking systems shows the positions of the sailors online for all over the world, they can be seen in computers, tablets and also cell phones miles away from the regatta venue. Results feed has also been a great challenge in these events, and today it is already possible to have immediate final and partial results online directly from the water, with special software and wireless communication system. These results can be distributed to any client that is interested in results of such events. Finally, some electronic equipment will be showed that is used at modern sailing boats, especially big boats, that facilitate and potential the sailing experience of high level sailing competition.

Author’s  short biographical note:

Walter Böddener, Representative of RIO 2016™ - Rio 2016™ Organising Committee (Rio 2016™) is a Brazilian Private Non-Profit Association created solely to plan and organize the Olympic and Paralympic Games Rio 2016; it coordinates all those who work for the Games: volunteers, suppliers, staff.
Walter Böddener was born in 1967 in Niter¨®i, RJ, Brazil. He is a professional Sports Manager specialized in Sailing. He has been sailing since 5 years of age, at the regional, national and international levels. Walter studied Sports at the State University Rio de Janeiro (1985-1988) and made a Specialization at the Sports University from Cologne (Sporthochschule Köln), Germany, from 1991 until 1995, in Sailing and Sport Psychology. He came back to Brazil at the end of 1995 and began his career as sailing teacher and coach, first teaching kids at the Optimist Class, and then changing after this to Youth Classes as Laser, Laser Radial, 420 and Europe. More than 200 sailors were taught and trained by Walter Böddener at this time; this led him to getting many National, Southamerican and World Championships as a coach. In 2001 Walter Böddener began his first Olympic Campaign in the Star Class with Torben Grael and Marcelo Ferreira. They won the Gold Medal at the Athens Olympic Games. In 2005 Walter Böddener assumed again this challenge with the sailors Robert Scheidt and Bruno Prada, and they won the Silver Medal at the 2008 Beijing Olympic Games. Next, Walter Böddener took the Advanced Sport Management Course from the IOC (International Olympic Committee) and became the Technical Coordinator of the the Brazilian Sailing Federation for 5 years. In the London 2012 Olympics Walter Böddener was the General Manager of the Brazilian Team. Since 2013 Walter Böddener has been working as Sailing Sport Manager at the Rio 2016 Organizing Committee.




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