Winter School
on Machine Learning
in Robotics
December 7 - 10, 2020, ONLINE
APPLICATION IS CLOSED

A unique opportunity to explore the fundamentals and practical applications of Machine Learning methods in Robotics
application deadline
25 /Nov
acceptance notification
30 /Nov
start
7 /Dec
COVID-19 | UPDATE
COVID-19 | UPDATE

WINTER SCHOOL on Machine learning in Robotics 2020 will take place ONLINE

As COVID-19 continues to affect life around the globe in unprecedented ways, the safety of our participants, instructors, and staff remains our highest priority.

That is why we have made the decision to offer the Winter School ONLINE. See the application submission deadline updated below.

We extended the registration deadline until the 25th November 2020 . This Winter School will be free of charge.

If you have already applied for the Winter School on ML in Robotics 2020 programme, please check your email inbox for further information.

Stay safe, stay informed!
Innopolis University team
Winter School Scope & Goals
The International Winter School on Machine learning is a four - day intensive course about the powerful combination of Robotics and Machine learning which is opening the door to entirely new automation possibilities.

The keynote sessions of the school program aim to give a clear overview of ML methods in Robotics with a particular emphasis on
  • Reinforcement Learning
  • Deep Learning

One of the main goals of the Winter School on ML in Robotics is bringing together the Robotics and Machine learning communities from all over the world.

We invite students, researchers and professionals to exchange ideas and to be a part of fascinating conversations on ML in Robotics.

Go ahead and press Submit!
Winter School Scope & Goals
The International Winter School on Machine learning is a four - day intensive course about the powerful combination of Robotics and Machine learning which is opening the door to entirely new automation possibilities.

The keynote sessions of the school program aim to give a clear overview of ML methods in Robotics with a particular emphasis on
  • Reinforcement Learning
  • Deep Learning

One of the main goals of the Winter School on ML in Robotics is bringing together the Robotics and Machine learning communities from all over the world.

We invite students, researchers and professionals to exchange ideas and to be a part of fascinating conversations on ML in Robotics.

Go ahead and press Submit!
Program
Moscow time (GMT+3)
Monday,
7 December
Tuesday,
8 December
Wednesday,
9 December
Thursday,
10 December
11:00 - 11:15
11:00 - 11:15
Opening ceremony
Opening speech by Alexander Klimchik - the head of the Center for technologies in robotics and mechatronics components, and Professor Stefano Nolfi - coorganizer, the head of the Laboratory of Autonomous Robotics and Artificial Life, Institute of Cognitive Science and Technology, National Research Council (CNR), Italy
11:15 – 12:45
11:15 – 12:45
Jan Peters, TU Darmstadt
13:00 – 14:30
13:00 – 14:30
Jan Peters, TU Darmstadt
11:00 – 13:00
11:00 – 13:00
Angelo Cangelosi, the University of Manchester (UK)
13:30 – 15:30
13:30 – 15:30
Angelo Cangelosi, the University of Manchester (UK)
Syllabus:
- A robot in all our homes
- Language learning in babies and robots
- Developmental robotics definition and principles
- Embodied Language learning
- Learning abstract words
- Trust and Theory of Mind
- Spiking and neuromorphic models
- Deep learning for robotics
11:00 – 13:00
11:00 – 13:00
Stefano Nolfi, Italian National Research Council (CNR)
13:30 – 15:30
13:30 – 15:30
Stefano Nolfi, Italian National Research Council (CNR)
Syllabus
- Evolving robots
- Embodiment
- Situatedness
- Behavior and cognition as complex dynamical systems
- Swarm Robotics
- Long-term adaptation and open-ended evolution
11:00 – 12:45
11:00 – 12:45
Muhammad Fahim, Innopolis University
Machine learning-based computer vision is becoming an integral part of robotics due to its highly accurate results. It provides the vision to understand the surroundings and classify the objects that enable driverless cars on the road and unmanned aerial vehicles (i.e., drones) to bring enormous opportunities. In this lecture, the objective is to gain in-depth knowledge of convolutional neural networks for the classification and semantic segmentation task. It will cover from basics to modern deep learning models which are based on convolutional neural networks. At the end of the lecture, a home learning task will be provided that enabled the participant to use such models for solving problems related to classification and semantic segmentation task.
13:00 – 15:00
13:00 – 15:00
Adil Khan, Innopolis University
The lecture will begin with an introduction to Generative and Discriminative Models. Next, we will learn about an Autoencoder, followed by a detailed discussion on two of the state-of-the-art generative models: Variational Autoencoder (VAE) and Generative Adversarial Networks. Finally, we will discuss an application of VAE to the problem of Zero-shot Anomaly Detection.
Important dates
November 25
November 25
Submission deadline
November 30
November 30
Acceptance notification
December 7–10
December 7–10
Technical lectures and seminars
Key Speaker and Co-organizer
Stefano Nolfi

  • Research Director of the Italian National Research Council (CNR)
  • Director of the Laboratory of Autonomous Robotics and Artificial Life of the Institute of Cognitive Sciences and Technologies.
  • Professor, Doctor, h-index 57

stefano.nolfi@istc.cnr.it
Speakers
Jan Peters
  • Professor at Technische Universität Darmstadt and Researcher at MPI for Intelligent Systems
  • h - index - 63

jan.peters@tu-darmstadt.de
Angelo Cangelosi
  • Professor of Machine Learning and Robotics at the University of Manchester (UK)
  • h -index - 41

angelo.cangelosi@manchester.ac.uk
Adil Khan
PhD, Kyung Hee University, South Korea
Head Lab of Machine Learning and Knowledge Representation at Innopolis University
h-index 22

a.khan@innopolis.ru
Muhammad Fahim
Ph.D, Assistant Professor at the Institute of Information security and cyberphysical systems, Lab of Cyberphysical Systems, Innopolis University
h-index 13

m.fahim@innopolis.ru
Audience
  • Undergraduate students (3rd year and above)
  • Graduate and postgraduate students
  • Researchers and industry professionals working in Robotics, Machine learning or related areas, willing to expand their knowledge and skills

Admission Requirements
  • Strong mathematical background
  • Programming skills in at least one of the following languages: C ++ / Java/ Python / MatLab
  • Upper-intermediate knowledge of English
Application
The application deadline is the 25th of
November 2020
For application, you will need the items listed below:
CV
max 2 pages including education, work experience and other relevant info
Motivation letter
Committees
Organizing Committee:
General Chair

  • Alexandr Klimchik, Head of the Center for technologies in Robotics and Mechatronics components, PhD, Associate Professor, Innopolis University
Сo-Chair
  • Alexander Maloletov, prof., Dr. Sc. (Phys.-Math.), Innopolis University
Organizing Committee:

  • Igor Gaponov, Associate professor, Candidate of physical and mathematical sciences, Innopolis University
  • Ramil Khusainov, Researcher, Laboratory of Mechatronics, Control and Prototyping, Innopolis University, Ph.D.
  • Alfiia Khabibulina, Innopolis University, Russia
  • Daria Shiyan, Innopolis University


Program committee
General Chair

  • Alexander Tormasov, Rector of Innopolis University
Сo-Chair
  • Iskander Bariev, Vice-Rector for Project, Science and Research Affairs, Innopolis University
Program committee

  • Jan Peters, Professor at Technische Universität Darmstadt and Researcher at MPI for Intelligent Systems
  • Adil Mehmood Khan, PhD, prof. Innopolis University
  • Sergey Savin, Senior Researcher, Laboratory of Mechatronics, Control and Prototyping,Innopolis University, Ph.D.
  • Giancarlo Succi, PhD, prof., Dean of the Faculty of Computer Science and Engineering, Innopolis University
  • Alberto Sillitti, PhD, prof. Innopolis University
  • Stefano Nolfi, Professor, Doctor, Research Director of the Italian National Research Council (CNR), Director of the Laboratory of Autonomous Robotics and Artificial Life of the Institute of Cognitive Sciences and Technologies
  • Angelo Cangelosi, Professor of Machine Learning and Robotics at the University of Manchester (UK)




      School coordinator
      Alexandr Klimchik
      Head of the Robotics Institute, Innopolis University, Ph.D.,
      Associate professor, h-index 14

      a.klimchik@innopolis.ru
      Alumni Testimonials
      Eltun Ibrahimov
      Participant of «The International Project School on Self-driven vehicles, held in April 2019
      As a participant in International Project School on Self-driven vehicles organized by Innopolis University, I would simply state that event was beyond what I was hoping for. International environment, organized sessions and competitions were expected to improve our competency on this trendy area and all participants were highly encouraged to make use of these chances. By taking this opportunity to give feedback on such a valuable event, I would express my deepest gratitude to supervisors, organization team and all heroes behind the scenes. All in all, I am strongly convinced that this event is just a worthwhile example to anticipate the subsequent ones from Innopolis University.
      Marcus Ebner von Eschenbach
      Participant of «The International Project School on Self-driven vehicles, held in April 2019
      Taking part in the project school was a great experience. The project tasks were interesting and ambitious as they required to solve up-to-date challenges in autonomous driving. It was exciting to work with team members of various professional and cultural backgrounds in a friendly but fierce competition.
      Parth Chholak
      Participant of The International double summer school «Robot's cognition, perception and control», held in June 2019
      The summer school was well organised and packed with knowledge and opportunities. The classes were intense, and we were constantly supported by the faculties. The university was well equipped in terms of technology and transport and internet was up to the mark. Last but not the least, there were plenty of informal events and excursions that allowed us to meet other participants and faculties in a relaxed environment and experience the Tatar hospitality!



      Innopolis University, 1, Universitetskaya Str., Innopolis, Russia, 420500


      If you have any questions, please contact our school organizer Alfiia Khabibulina, a.khabibulina@innopolis.ru

      You can visit the page of the last International double summer school «Robot's cognition, perception and control», which was held in June 2019