Learning Week I: Academic skills and advanced topics in CAD

The first Learning Week will take place in Barcelona from September 6 to 10, 2021. If the pandemic permits, it will be a physical event. Otherwise, we will adopt a hybrid (physical and online) or strictly online format.

The Event will be co-organised with the Barcelona Graduate School of Mathematics (BGSMath) and the University of Strathclyde. It aims to help ESRs develop complementary and transferable skills in Academia. Topics to be covered include communication/presentation to diverse audiences, Fund-raising and Proposal writing, and Knowledge Transfer Basics. These sessions will often include hands-on activities. The event will include a 2-day scientific workshop with courses on advanced topics of CAD.

Doctoral school I & Midterm meeting

Due to the covid19 pandemic, the first Doctoral School and the Midterm meeting will be held online during the first week of February 2021. Despite its name, the Midterm meeting with the REA Project Officer is held on February 4, 2021 as an one day event. Both events will be held on Zoom, links are emailed to the participants. Please join the meeting using your full name!

Schedule of the Doctoral School I

The First Doctoral School focuses on machine learning for shapes. There will be introductory short courses and presentations by GRAPES members and other invited high-profile speakers. Confirmed speakers include P. Alliez (Inria & GF), Y. Avrithis (Inria & Athena RC), M. Bronstein (USI and ICL), M. Salamó (UB), and A. Leutgeb from industrial partner RISC-Software. A pdf version of the schedule is also available.

Monday, February 1st, 2021 (Chair: I. Emiris)
11:00 Tutorial [Part A]: Pierre Alliez (Inria & GF): Clustering algorithms and introduction to persistent homology
Abstract: This tutorial will first offer an introduction to clustering, both discrete and continuous, and persistent homology: K-means, Lloyd iteration, hierarchical clustering, single linkage algorithm, dendograms, mode seeking clustering, persistent homology. I will also provide a basic introduction to machine learning, neural networks, and related data structures.
12:30 Lunch break
14:00 Tutorial [Part B]: Pierre Alliez (Inria & GF): Machine Learning 101 and Neural networks
15:30 Coffee break
17:00 Invited talk:Thierry Chevalier (Airbus): Industrial interest in learning, processing & optimising shapes
18:00 End of the day

Tuesday, February 2nd, 2021 (Chair: M. Salamó)
11:00 Tutorial [Part A]: Yannis Avrithis (Inria & Athena RC): Deep learning and computer vision
Abstract: This tutorial will comprise of the following parts: (a) Visual representation: Data-driven representation learning. Neuroscience and receptive fields. Visual descriptors. Hierarchical representations. (b) Machine learning: Linear classification, binary and multi-class. Multiple layers, neural networks. (c) Convolution: Definition, convolutional networks. Pooling. Network architectures. (d) Optimization: Gradient computation. Optimizers, initialization, normalization. Deeper architectures. (e) Retrieval: Spatial pooling. Metric learning and image retrieval. Unsupervised and semi-supervised learning. Graph-based methods.
12:30 Lunch break
14:00 Tutorial [Part B]: Yannis Avrithis (Inria & Athena RC): Deep learning and computer vision
15:30 Coffee break
16:00 Supervisory Board meeting (restricted)
17:00 End of the day

Wednesday, February 3rd, 2021 (Chair: A. Mantzaflaris)
11:00 Tutorial [Part A]: Michael Bronstein (USI & Imperial College London)
12:30 Coffee break
13:00 Tutorial [Part B]: Michael Bronstein (USI & Imperial College London)
14:30 Lunch break
16:00 “Social” activities: Virtual tours of the Acropolis: #1, #2, and VR 360ᵒ video tour of the Acropolis Museum.

Thursday, February 4th, 2021
Meeting with the REA Project Officer: schedule and its pdf version.

Friday, February 5th, 2021 (Chair: G. Muntingh)
11:00 Tutorial [Part A]: Maria Salamó (UB): Point-cloud analysis and classical Machine Learning techniques
Abstract: The analysis of point cloud has been done in different ways in the field of machine learning. This tutorial is devoted to introducing the main machine learning algorithms that can be used for point-cloud analysis, among other applications. It has been divided in two parts. First part is focused on the theoretical aspects of classical machine learning algorithms, while the second part is devoted to deep learning algorithms. In both parts, the theoretical foundations of every type of algorithm will be detailed. We will see practical examples of 3D shapes analysis on every part.
12:30 Lunch break
14:00 Tutorial [Part B]: Simone Balocco (UB): Deep learning approaches
15:30 Coffee break
16:00 Educational Committee meeting (restricted)
16:30 End of the day

Monday, February 8th, 2021
11:00 Tutorial [Part A]: Alexander Leutgeb (RISC-Software): Dynamic Cutting Force Prediction (During Simulation of Machining Processes) (Chair: A. Fabri)
Abstract: The problem domain is to predict the cutting forces during simulation of metal cutting processes. There already exist several force computation models. These models have in common, that for different material combinations (cutting tool and workpiece) the determination of their coefficients is a time consuming task by performing different metal cutting patterns with the real machine and measuring the resulting cutting forces over the time. The novel approach of our research project should learn this coefficients from regular machining processes. That means we need on the one hand the data from the simulation (machining parameters and geometric representation of cutter workpiece engagement) and on the other hand the measured forces of the sensors from the real machine. Because usually the real machines do not come with sensors providing force measurements we will use an Internet-of-Things sensor from Pro Micron, which measures the forces directly on the tool side. So from a Machine Learning standpoint we have to first correlate the time series data from the simulation with that of the sensor. Later on we perform model fitting/regression (linear & non linear) to learn the coefficients for the force computation model.
After the model is trained, the simulation of the machining process can predict the cutting forces over the time. The application of these forces is relevant for machine vibration analysis, feed rate optimization, increase of energy efficiency, geometric errors in finished workpieces caused by tool cutter deflections, and so on.
12:00 Lunch break
14:00 Tutorial [Part B]: Christoph Hofer (RISC-Software): Dynamic Cutting Force Prediction (During Simulation of Machining Processes) (Chair: A. Fabri)
15:00 Coffee break
17:00 Seminar: Managing and sharing research outputs: all you need to knowSLIDES & VIDEO
Presenters: Elli Papadopoulou, Athena RC/ OpenAIRE, Iryna Kuchma, Electronic Information for Libraries – eifl / OpenAIRE
Abstract: This is an introductory session to the Open Science model. It aims to ensure that all ESRs have a comprehensive understanding of the basics of Open Science and are able to apply them in their everyday work using available resources. Presentations will highlight good practices in scientific publishing and data management activities that increase researchers recognition and at the same time achieve compliance with European requirements (e.g. grants received under H2020, HorizonEurope and ERC). A “first-aid toolkit” will be provided so that researchers can practice Open Science skills at their own time and pace.
18:15 End of the Doctoral School


Schedule of the Midterm Meeting (February 4th, 2021)

The purpose of the Midterm meeting between the REA Project Officer (Filippo Galiardi) and the Consortium is as to discuss the implementation of the project, make sure that all ESRs have been recruited and review the rules of the Marie Curie programme to see if there are any issues that need to be addressed before the beginning of the scientific activities. All beneficiaries and ESRs should participate the meeting. Our Partner Organisations are strongly encouraged to participate.

You can find a pdf version of the Midterm meeting program here. All times are Greek local time (EET=UTC+2=GMT+2).

10:00 Introduction by the Project Coordinator and the REA Project Officer
10:05 Tour de table: All scientists-in-charge briefly present their research team and describe their role within the network. Introduction of the Partner Organisations
10:45 REA Project officer presentation
11:05 Coordinator’s report: Presentation of the Network and the Progress report
11:35 Lunch break
13:00 Fellows’ individual presentations
14:00 Coffee break
14:15 Fellows’ individual presentations
15:00 Restricted Meeting between the fellows and the Project Officer
16:00 Coffee break
16:15 Restricted session: Meeting between site-leaders and Project Officer
16:30 Feedback and open discussion
17:00 End of the meeting

1st Doctoral School and Midterm meeting

The First Doctoral School is just around the corner starting Monday February 1st, 2021. The School focuses on machine learning for shapes. There will be introductory short courses and presentations by GRAPES members and other invited high-profile speaker: P. Alliez (Inria & GF), Y. Avrithis (Inria & Athena RC), M. Bronstein (USI and ICL), M. Salamó (UB), A. Leutgeb from industrial partner RISC-Software, and the Advisory Committee member Thierry Chevalier (Airbus). More details can be found at the School’s webpage. A pdf version of the schedule is also available.

The Midterm review meeting with the REA Project Officer is scheduled for Thursday, February 4th, 2021. A pdf version of its program here.

All times are Greek local time (EET=UTC+2=GMT+2).

Kickoff & Recruitment Event, Rome (Virtual Event)

GRAPES Kickoff Event

Due to the coronavirus pandemic, our Kickoff Workshop will be held online on November 5-6, 2020. It will not be a “recruitment” event as it was initially planned because most of the positions are now closed. However, the application process for the remaining open positions is ongoing and we encourage interested candidates to upload their files (see this page) since the hard deadline to recruit PhD fellows remains end of November 2020.

Schedule

The agenda of the meeting includes introductory presentations by the coordinator, the research coordinator, the head of the Educational Committee and the technical coordinator. Next, each beneficiary will give a short presentation of their team and their PhD projects (15′ for teams hosting one PhD, 25′ for teams hosting two PhDs). The PhD projects will be presented by the ESRs, if they are recruited by the time of the Kickoff, else by the project advisor. We encourage the participation of short listed or selected candidates that will not have completed their recruitment procedures by the start of the Kickoff event. The Project’s Partner Organizations will give a brief overview of their research activities and their expectations from GRAPES. Finally, there will be meetings of the Educational Committee and the Supervisory Board.

You can download a pdf version of the program here.
All times are Rome local time (UTC+1).

Thursday November 5th, 2020 Friday November 6th, 2020
11:00 C. Manni – welcome 11:00 USI Lugano , ESR11, ESR12
11:05 I. Emiris – GRAPES Coordinator 11:25 Univ. Rome Tor Vergata, ESR13
11:20 L. Busé – Research Coordinator 11:40 Vilnius Univ. , ESR14
11:35 C. D’Andrea – Head of Educational Committee 11:55 GeometryFactory , ESR15
11:50 C. Konaxis – Technical Coordinator 12:10 Lunch break
12:00 Lunch break 14:00 3D Industries
13:45 Athena RC , Y. Avrithis , ESR1, ESR2 14:15 International TechneGroup Ltd
14:10 Univ. Barcelona, ESR3, ESR4 14:30 ModuleWorks GmbH
14:35 Inria , ESR5 , ESR6 14:45 RISC-Software GmbH
15:00 Coffee break 15:00 Coffee break
15:15 JKU Linz, ESR7 15:15 Supervisory Board meeting
15:30 RWTH Aachen, ESR8
15:45 SINTEF, ESR9
16:00 Univ. Strathclyde – ESR10
16:15 Coffee break
16:30 Educational Committee meeting