XVI Summer School on Operations Research, Data, and Decision Making, ORA 2024
.jpg)
XVI Summer School on Operations Research, Data, and Decision Making, ORA 2024, May 23-24, 2024.
Higher School of Economics, Nizhny Novgorod, Rodionova street 136
The Summer School on Operational Research, Data and Decision Making will take place on May 2024 in Nizhny Novgorod, Russia. The school is organized by the Laboratory of Algorithms and Technologies for Networks Analysis and Faculty of Informatics, Mathematics and Computer Science of the National Research University Higher School of Economics, Nizhny Novgorod.
THIS YEAR THE SCHOOL WILL BE ORGANIZED MAY 23-24, 2024 in mixed format ONSITE and ZOOM.
Interested participants have to register (see below) and we will send you the link for participation.
The main topics of the school are related to practical algorithms in logistics, transportation and traffic management, scheduling, decision science, and stochastic programming. The school follows the traditions of previous summer schools on operational research and applications 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022(summer school in optimization):
The school is organized for last-year bachelor, master and PhD students. To attend the school as a participant you must register before May 16, 2024. If you have any questions, please do not hesitate to contact us: vkalyagin@hse.ru
Important Dates and Schedule :
Registration - May 16, 2024
Notification acceptance: Ad hoc
Summer School: May 23-24, 2024.
School schedule:
Thursday, May 23: 15:00 - 18:00,
Friday, May 24: 10:00 - 13:00.
Summer school onsite location: HSE building on Rodionova street 136, room 401,
Summer school outside access: Zoom (for registered participants)
Program
Presentations
Mario R. Guarracino, A Short Journey through Graph Embedding Techniques(part 1)
Mario R. Guarracino, A Short Journey through Graph Embedding Techniques(part 2)
Panos M. Pardalos, Twin Support Vector Machines
School lecturers
Roman Belavkin, Middlesex University, London, UK
Lecture 1: Data, Information and its Value: Applications of the Value of Information to Model Selection and Parameter Control.
Lecture 2: New Developments of the Value of Information Theory: Optimal Transport and Dynamic Value of Information
Mario Guarracino, University of Cassino, Italy and lab LATNA HSE University
Lecture 1: A Short Journey through Whole Graph Embedding Techniques (Part I)
Lecture 2: A Short Journey through Whole Graph Embedding Techniques (Part II)
Panos Pardalos, University of Florida, USA and lab LATNA HSE NN.
Lecture: Exploring Twin Support Vector Machines: Advances and Applications
Sergey Slashchinin, lab LATNA HSE NN.
Lecture: Introduction to Graph Neural Networks with Applications to Combinatorial Optimization
Co-Chairs of the school
Panos M. Pardalos, University of Florida, USA and LATNA, NRU HSE
Natalia Aseeva, NRU HSE, Russia
Program Committee
Fedor Fomin, Bergen University, Norway and St Petersburg department of Steklov Mathematical Institute
Yury Kochetov, Russian Academy of Sciences, Novosibirsk
Oleg Prokopyev, University of Pittsburgh, USA
Andrey Raigorodskii, Moscow Institute of Physics and Technology, Moscow State University, Yandex
Nikolay Zolotykh, Lobachevsky State University, Nizhny Novgorod
Organizing Committee
Natalia Aseeva, NRU HSE, Russia
Valery Kalyagin, NRU HSE, Russia
Nikita Kuzmin, NRU HSE, Russia
Timur Medvedev, NRU HSE, Russia
Have you spotted a typo?
Highlight it, click Ctrl+Enter and send us a message. Thank you for your help!
To be used only for spelling or punctuation mistakes.