School in AI: Deep Learning, Vision and Language for Industry

The “School in AI: Deep Learning, Vision and Language for Industry” is a new, intensive two-week training course (in English) at UNIMORE. It consists of a first week of “foundational” and a second week of “strengthening” AI training, followed by a practical experience, developing a project with the support of the course tutors and possibly in collaboration with companies.

The course is free for 30 graduated students and entirely funded by the Emilia Romagna Region through the “Advanced Schools in Artificial Intelligence in Emilia-Romagna” project.

AI School is in partnership with AIAcademy and AImagelab

our program

First week

14 - 18 February 2022

Module 1: Fundamentals of Deep Learning – 45 hours

  1. Introduction to machine learning (with PyTorch)
  2. Basic linear classifiers
  3. Artificial neural networks
  4. Recurrent neural networks
  5. Autoencoders and self supervised learning

Module 2: Fundamentals of Computer Vision – 45 hours

  • Foundations of computer vision
  • Basic image processing: operations and descriptors
  • Convolutional neural networks
  • Motion analysis
  • Advanced deep architectures for visual cognitive systems

first week

Schedule

monday
tuesday
Wednesday
Thursday
friday
Introduction to machine learning (with PyTorch)
Basic linear classifiers
Artificial neural networks
Recurrent neural networks
Autoencoders and self supervised learning
Foundations of computer vision
Basic image processing: operations and descriptors
Convolutional neural networks
Motion analysis
Advanced deep architectures for visual cognitive systems
Lab. of Introduction to machine learning (with PyTorch)
Lab. of Basic linear classifiers
Lab. of Artificial neural networks
Lab. of Recurrent neural networks
Lab. of Autoencoders and self supervised learning
Lab. of Foundations of computer vision
Lab. of Basic image processing: operations and descriptors
Lab. of Convolutional neural networks
Lab. of Motion analysis
Lab. of Advanced deep architectures for visual cognitive systems

first week

Schedule

MONDAY
9 - 11 Introduction to machine learning (with PyTorch)
11 - 13 Foundations of computer vision
14 - 16 Lab. of Introduction to machine learning (with PyTorch)
16 - 18 Lab. of Foundations of computer vision
TUESDAY
9 - 11 Basic linear classifiers
11 - 13 Basic image processing: operations and descriptors
14 - 16 Lab. of Basic linear classifiers
16 - 18 Lab. of Basic image processing: operations and descriptors
WEDNESDAY
9 - 11 Artificial neural networks
11 - 13 Convolutional neural networks
14 - 16 Lab. of Artificial neural networks
16 - 18 Lab. of Convolutional neural networks
THURSDAY
9 - 11 Recurrent neural networks
11 - 13 Motion analysis
14 - 16 Lab. of Recurrent neural networks
16 - 18 Lab. of Motion analysis
FRIDAY
9 - 11 Autoencoders and self supervised learning
11 - 13 Advanced deep architectures for visual cognitive systems
14 - 16 Lab. of Autoencoders and self supervised learning
16 - 18 Lab. of Advanced deep architectures for visual cognitive systems

our program

Second week

21 - 25 February 2022

Advanced Topics

  1. Anomaly detection and process monitoring in industry
  2. Automotive applications of artificial intelligence
  3. Continual Learning
  4. European Union Artificial Intelligence Act
  5. Explainability in artificial intelligence
  6. Geometric deep learning
  7. High performance computing and large-scale models
  8. Medical imaging
  9. Robot and 3D vision
  10. Vision and language (attention and Transformer Neural
    Network)

second week

Schedule

monday
tuesday
Wednesday
Thursday
friday
Vision and language (attention and Transformer Neural Network)
Automotive applications of artificial intelligence
European Union Artificial Intelligence Act
High performance computing and large-scale models
Company meetings
Medical Imaging
Continual Learning
Geometric deep learning
Anomaly detection and process monitoring in industry
Robot and 3D vision
Assisted project
Explainability in artificial intelligence
Assisted project
Assisted project

second week

Schedule

MONDAY
9 - 11 Vision and language (attention and Transformer Neural Network)
11 - 13 Medical Imaging
14 - 16 Anomaly detection and process monitoring in industry
16 - 18 Assisted project
TUESDAY
9 - 11 Automotive applications of artificial intelligence
11 - 13 Continual Learning
14 - 16 Robot and 3D vision
16 - 18 Assisted project
WEDNESDAY
9 - 11 European Union Artificial Intelligence Act
11 - 13 ValoGeometric deep learningre2
14 - 16 Assisted project
16 - 18
THURSDAY
9 - 11 High performance computing and large-scale models
11 - 13
14 - 16 Explainability in artificial intelligence
16 - 18
FRIDAY
9 - 11 Company meetings
11 - 13
14 - 16
16 - 18

LECTURERS

Rita Cucchiara holds a Degree in Electronic Engineering (1989) and a PhD in Computer Engineering (1993), both received at the University of Bologna. has been, since 2005, Full Professor of Information Processing Systems at the University of Modena and Reggio Emilia, where she is responsible for the AimageLab Laboratory and the AI Academy; she deals mainly with Artificial Vision and Deep Learning, with more than 350 publications on the subject. She is also Director of the interdepartmental Artificial Intelligence Research and Innovation Center AIRI, member of the Board of IIT (Italian Institute of Technology) and has been from 2018 to 2021 Director of CINI (National Interuniversity Consortium for Informatics) National Laboratory AIIS – Artificial Intelligence for Intelligent Systems.

Simone Calderara holds a Master’s degree in Computer Engineering (2005) and a PhD in Computer Engineering (2009), both received at the University of Modena and Reggio Emilia, where he is currently Associate Professor within the AimageLab group. His current research interests include machine vision and machine learning applied to human behaviour analysis, and visual monitoring in crowded environments. During his research career he has collaborated with national and international public and private institutions such as: Hebrew University of Jerusalem Interdisciplinary Center for Neural Computation, Center for Research in Computer University of Central Florida, and others. He has published more than 90 articles in international journals or conferences, he is also co-author of 3 chapters of books.

 

Costantino Grana graduated from the University of Modena and Reggio Emilia in 2000 and received his PhD in Computer Science and Engineering in 2004. He is currently Full Professor at the Department of Engineering Enzo Ferrari’ of the University of Modena and Reggio Emilia. His research interests mainly concern artificial vision and multimedia data processing: medical imaging, image processing, digital image analysis of historical manuscripts and other cultural heritage resources, Media images and recovery of videos and color-based applications. Costantino Grana has published 5 chapters of books, 38 articles in peer-reviewed international journals and more than 100 articles on international conferences.

Roberto Vezzani graduated in Computer Engineering in 2002 and received his PhD in Information Engineering in 2007 at the University of Modena and Reggio Emilia. Since 2016 he has been Associate Professor at the Department of Engineering ‘Enzo Ferrari’, he is part of the AimageLab group and has been director of the AIRI research center until 2021. His research interests mainly concern video surveillance systems, with particular attention to motion detection, detection and identification of people. He is author of about 80 articles published in international journals and conference proceedings. He is member of ACM, IEEE and CVPL.

Lorenzo Baraldi received his PhD (cum laude) in Information and Communication technologies from the University of Modena and Reggio Emilia, Italy, in 2018. He has been an intern researcher at Facebook AI Research (FAIR) in 2017. He is currently Assistant Professor at the Department of Engineering “Enzo Ferrari”, University of Modena and Reggio Emilia. He is author or co-author of over 40 publications in scientific journals and international conferences. His filed of research include image processing, video comprehension, deep learning, and multimedia.

Silvia Cascianelli holds a Master’s Degree in Information and Automation Engineering in 2015 and a PhD with honours in Information and Industrial Engineering at the University of Perugia in 2019. She is currently Assistant Professor (RTD-A) at the Department of Engineering Enzo Ferrari’ of the University of Modena and Reggio Emilia. She was Visitor Researcher at the Queen Mary University of London between 2017 and 2018. He is Associate Editor of IEEE Robotics and Automation Letters. She is author or co-author of more than 30 publications in scientific journals and international conference proceedings.

Angelo Porrello obtained a Master’s Degree in Computer Engineering in 2017 from the University of Modena and Reggio Emilia.  He pursued a Ph.D. programme in Information and Communication Technology during the three-year period 2019-2021; at the moment, he works as Research Fellow within the AImageLab Group at the Department of Engineering “Enzo Ferrari”. His research interests focus on Deep Learning techniques: more precisely on the fields of Continual Learning, Re-Identification, and Anomaly Detection. He is the author or co-author of more than 10 publications in scientific journals and international conference proceedings.

Giuseppe Fiameni is a Data Scientist at NVIDIA where he oversees the NVIDIA AI Technology Centre in Italy, a collaboration among NVIDIA, CINI and CINECA to accelerate academic research in the field of AI. He has been working as HPC specialist at CINECA, the largest HPC facility in Italy, for more than 14 years providing support for large-scale data analytics workloads. Research interests include large scale deep learning models, system architectures, massive data engineering, video action detection.

info

Course Details

Participation fee: None. The course is completely free.

Credits granted: The Postgraduate Course provides for the disbursement of 15 ECTS (expendable in Master’s Degree Courses that recognize them), if after the lesson period an independent project is completed with a positive evaluation, delivered by the deadline of 05/31/2022.

Location: “Enzo Ferrari” Engineering Department, via P. Vivarelli 10, Modena.

Duration of face-to-face lessons: Two weeks, from 14 February 2022 to 25 February 2022.

Application deadline: 14 January 2022 at 13:00.

Selection: Based on qualifications only (bachelor’s or master’s degree grade and curriculum vitae).

Availabilities: The course includes 30 free places, including free accomodation, assigned on the basis of the degree grade and the CV evaluation.

AI ACADEMY

Creating innovative solutions of Artificial Intelligence is a complex task, requiring specialized expertise to understand which solutions are ideal for your company. The demand for professionals with those skills is soaring, and the acquisition of these skills is the goal of the School in AI: Deep Learning, Vision and Language for Industry.


The course is organized in partnership with AI Academy, and AimageLab excellence clusters at national and European level, connected with numerous leading companies in multiple fields.

THE TRAINING COURSE

The School is free and entirely financed by Regione Emilia Romagna, through the project “Advanced Schools in Artificial Intelligence in Emilia-Romagna”. The area has become an outstanding international environment for AI over the latest years and strongly incentives the adoption of new AI-based technologies, as fundamental elements of innovation to shape the future of companies and society in the area.
The course is aimed at recent graduates in STEM subjects, or subjects where computer technology is now crucial (medicine, economics, up to digital humanities), who do not yet have a specific training on Artificial Intelligence, and to all those who are already employed but want to keep up with the developments in the professional world.
This intensive two-weeks training course, in English, will consist of two sections of one week each:
The first part aims to fill the most relevant gaps by providing the basic knowledge and skills related to the tools of Machine Learning, Deep Learning and their applications to Computer Vision.
The second section is for improving and broadening the competence achieved in the first one: the most recent computer techniques will be explored in detail and the AI skills necessary in industry will be sharpened, thanks to the interventions of professors engaged at the highest levels in this field of research.
During the entire duration of the course, the synergy with the territory will provide interventions and company visits to integrate the school training with practical examples of application and workshops, to make what was introduced in the lessons concrete. Furthermore, seminars and detailed supplementary material will integrate the lessons.

14 - 18 february 2022

enroll

Apply

Official information on the UNIMORE page: Link

How to Apply:
Login on www.esse3.unimore.it -> Top Right menu “Area Studente” -> “Ammissione”
Select: “Iscrizione Concorsi”
Select: “Corso di perfezionamento”
Select: “Corso di Perfezionamento a crediti​”
Select: “Ammissione al Corso di Perfezionamento School in AI: Deep Learning, Vision and Language for Industry”
Follow the guided procedure uploading all required attachments.

Progetto triennale di alta formazione in ambito culturale, economico e tecnologico ai sensi dell’art. 2 della legge regionale n. 25/2018 approvato con deliberazione di Giunta regionale n.1251/2019.

Applications deadline: 14 January 2022 at 13:00