School in AI: Deep Learning, Vision and Language for Industry - second edition
After the first extremely successful edition in February, we are happy to announce the second edition of the “School in AI: Deep Learning, Vision and Language for Industry”, a new and intensive two-week training course 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 practitioners 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, AIMAGELAB, Artificial Intelligence Research and Innovation Center and hosted at Dipartimento di Ingegneria Enzo Ferrari
5 - 9 September 2022
Module 1: Fundamentals of Deep Learning – 45 hours
- Introduction to machine learning (with PyTorch)
- Basic linear classifiers
- Artificial neural networks
- Recurrent neural networks
- 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
Schedule Lessons from 5 to 9 September 2022
(Building MO25, second floor, first room) Dipartimento di
Ingegneria "Enzo Ferrari"
|9 - 11||Introduction to machine learning (Calderara)
|11 - 13||Introduction Computer Vision (Cucchiara)
|14 - 16||Lab. of Introduction to machine learning (with PyTorch) (Boschini/Bonicelli)|
|16 - 18||Lab. of Foundations of computer vision (Amoroso)|
|9 - 11||Linear classifiers (Calderara)|
|11 - 13||Image processing and descriptors (Grana)|
|14 - 16||Lab. of Basic linear classifiers (Porrello/Boschini)|
|16 - 18||Lab. of Image processing and descriptors (Bolelli)|
|9 - 11||Artificial neural networks (Calderara)|
|11 - 13||3D Computer Vision (Vezzani)|
|14 - 16||Lab. of Artificial neural networks (Porrello/Bonicelli|
|16 - 18||Lab. of 3D Computer Vision (Simoni)|
|9 - 11||Convolutional neural networks (Cucchiara)|
|11 - 13||Recurrent neural networks (Calderara)|
|14 - 16||Lab. of Recurrent neural networks (Boschini/Bonicelli)|
|16 - 18||Lab. of Convolutional neural networks (Amoroso)|
|9 - 11||Autoencoders and self supervised learning (Porrello)|
|11 - 13||Advanced deep architectures for visual cognitive systems (Baraldi)|
|14 - 16||Lab. of Autoencoders and self supervised learning (Porrello/Bonicelli)|
|16 - 18||Lab. of Advanced deep architectures for visual cognitive systems (Baraldi)|
12 - 16 September 2022
- Anomaly detection and process monitoring in industry
- Automotive applications of artificial intelligence
- Continual Learning
- European Union Artificial Intelligence Act
- Explainability in artificial intelligence
- Geometric deep learning
- High performance computing and large-scale models
- Medical imaging
- Robot and 3D vision
- Vision and language (attention and Transformer Neural
Schedule Lessons from 12 to 16 September 2022
(Building MO25, second floor, first room) Dipartimento di
Ingegneria "Enzo Ferrari"
|9 - 11||Medical Imaging (Grana)|
|11 - 13||Geometric deep learning (Rodolà)|
|14 - 16||Deep Learning for Financial Forecasting (Calderara)|
|16 - 18||Robot and 3D vision (Vezzani)|
|9 - 11||Explainability in artificial intelligence (Natalia Diaz Rodriguez)|
|11 - 13||Continual Learning (Lomonaco)|
|14 - 16||Artificial Intelligence for Bioinformatics (Ficarra)|
|16 - 18||Assisted project (Bolelli)|
|9 - 11||European Union Artificial Intelligence Act (Cucchiara)|
|11 - 13||Vision and language (attention and Transformer Neural Network) (Baraldi)|
|14 - 16||Assisted project (Bonicelli)|
|16 - 18||Assisted project (Bonicelli)|
|9 - 11||High performance computing and large-scale models (Fiameni)|
|11 - 13||High performance computing and large-scale models (Fiameni)|
|14 - 16||Automotive applications of artificial intelligence (Baraldi)|
|16 - 18||Explainability in artificial intelligence|
|9 - 11||Company meetings (Grana)|
|11 - 13||Company meetings (Grana)|
|14 - 16||Company meetings (Grana)|
|16 - 18||Company meetings (Grana)|
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.
Roberto Paredes is Full Professor of Computer Science at Universitat Politècnica de València in Spain (UPV). He has been the first Director of the Pattern Recognition and Human Language Technology Research Center and President of the AERFAI (Pattern Recognition and Image Analysis National Association). His research interests include deep learning, machine learning, pattern recognition, biometrics and their application to computer vision and big data analysis. He has participated in several National and European Research Projects and currently he is the Lead Developer of the European Distributed Deep Learning Library under the DeepHealth European Project. Professor Paredes is the coauthor of more than 130 articles in international journals and international conferences. He has received different awards like the Best Face Verification Algorithm in AVBPA 2003.
Participation fee: None. The course is completely free.
Credits granted: The Postgraduate Course provides the certification of 15 ECTS (expendable in Master’s Degree Courses that recognize them). In order to get the credits, 75% of the lessons must be attended and after the lesson period an independent project must be delivered with a positive evaluation, by the deadline of 30 November 2022.
Location: Dipartimento di Ingegneria “Enzo Ferrari”, Via P. Vivarelli 10, 41125 Modena.
Duration of face-to-face lessons: Two weeks, from 5 to 16 September 2022.
Application deadline: 30 June 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 (if requested), assigned on the basis of the degree grade and the CV evaluation.
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 the AI ACADEMY UNIMORE that connects the major technological players with sites in Emilia Romagna and fosters life-long learning initiatives on the AI fields and related subfields.
Companies affiliated with AI ACADEMY:
Official information on the UNIMORE page: Link
Read the call carefully!
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.