1st ECMS International School for Young Researchers
About
We are thrilled to introduce the inaugural “1st ECMS International School for Young Researchers” scheduled to coincide with the ECMS International Conference on Modelling and Simulation. This summer school is tailored specifically for young scholars eager to delve into the expansive realms of modelling and simulation.
Goals of the Summer School:
The primary aim is to equip young researchers with advanced knowledge and practical skills that are essential for pushing the boundaries of modelling and simulation. The summer school seeks to inspire participants to pioneer new research directions and to apply sophisticated modelling and simulation techniques in their own research projects.
Who should attend:
This program is ideal for graduate students, post-doctoral researchers, and young academics who are currently engaged in or are starting their research in fields related to modelling and simulation. It offers a unique opportunity to interact with leading experts and peers from around the globe.
Date and venue:
The Summer School will be held from 3rd to 4th of June 2024 at the same venue as the ECMS conference. Details regarding the schedule and registration process will be announced shortly.
Terms and conditions:
Please read the terms and conditions before registering – download.
Registration:
The registration form is available until 10 May 2024, 11:59 PM. Priority is given to ECMS conference participants on a first-come, first-served basis.
Join us for this exceptional educational experience, where you will gain not only knowledge but also practical skills and inspiration to advance your research in modelling and simulation. Stay tuned for more details!
Programme
- “Quantum computing with Qiskit” – Tomasz Stopa, IBM Software Lab
- “Federated learning in Flower” – Maciej Malawski, Sano Science
- “Brain connectivity. How to predict neurodegeneration and brain causality with machine learning, and how those compare with traditional simulations” – Alessandro Crimi, Sano Science
- “Analytical Representative Volume Element (aRVE) and its applications” – Vladimir Mityushev, Cracow University of Technology
- “Multiformalism modelling” – Mauro Iacono, Università degli studi della Campania Luigi Vanvitelli
- “Resampling Methods Theory and Practice” – Elżbieta Gajecka-Mirek, Cracow University of Technology
- “Image processing and analysis”, Anna Wójcicka, AGH University of Science and Technology, Center of Excellence in Artificial Intelligence
- “Virtual platform for medical data and modern diagnostics MDB-MEDICAL DATA BANK”, Sławomir Wiak, Lodz University of Technology
- “Algorithms of Selection and Aggregation Coefficients in Methods of Categorizing Skin Lesions”, Łukasz Wąs, Lodz University of Technology
Schedule
June 3, 2024
- 08:00 – 08:15 AM: Welcome
- 08:15 – 09:00 AM: “Multiformalism Modelling” – Mauro Iacono
- 09:00 – 10:30 AM: “Image Processing and Analysis – Part 1” – Anna Wójcicka
- 10:30 – 10:45 AM: Coffee Break
- 10:45 – 12:15 PM: “Overview of 5G/6G networks & technology” – Sławomir Wiak, location: A3 room, 2nd floor, building of Faculty of Electrical and Computer Engineering
- 12:15 – 01:00 PM: “Virtual Platform for Medical Data and Modern Diagnostics MDB-MEDICAL DATA BANK” – Sławomir Wiak
- 01:00 – 02:00 PM: Lunch Break
- 02:00 – 03:30 PM: “Analytical Representative Volume Element (aRVE) and Its Applications” – Vladimir Mityushev
- 03:30 – 03:45 PM: Coffee Break
- 03:45 – 05:15 PM: “Algorithms of Selection and Aggregation Coefficients in Methods of Categorizing Skin Lesions” – Łukasz Wąs
June 4, 2024
- 08:00 – 09:30 AM: “Federated Learning in Flower” – Maciej Malawski
- 09:30 – 11:00 AM: “Brain Connectivity. How to Predict Neurodegeneration and Brain Causality with Machine Learning, and How Those Compare with Traditional Simulations” – Alessandro Crimi
- 11:00 – 11:15 AM: Coffee Break
- 11:15 – 12:45 PM: “Quantum Computing with Qiskit” – Tomasz Stopa
- 12:45 – 01:45 PM: Lunch Break
- 01:45 – 03:15 PM: “Image Processing and Analysis – Part 2” – Anna Wójcicka
- 03:15 – 03:30 PM: Coffee Break
- 03:30 – 05:00 PM: “Resampling Methods Theory and Practice” – Elżbieta Gajecka-Mirek
- 05:00 – 07:00 PM: ECMS2024 Welcome Reception
All classes will take place in Room 114 in the Gil Gallery, except for the 5G-6G lecture (A3 room, 2nd floor, building of Faculty of Electrical and Computer Engineering).
Venue
The ECMS School will take place in the GIL gallery building, on the 1st floor, in room 114. For more information about the campus of the Cracow University of Technology, please visit: Location.
GIL gallery
Room no 114
Meet Our Workshop Leaders
Maciej Malawski
Director of Sano – Centre for Computational Medicine, Research Team Leader of Extreme-scale Data and Computing, Associate Professor at AGH
Holds a PhD in computer science and an MSc in computer science and in physics. In 2011-2012 he was a postdoc at the University of Notre Dame, USA. Currently an associate professor at the Faculty of Computer Science AGH and a senior researcher at ACC Cyfronet AGH. His scientific interests at Sano include parallel and distributed computing, data science, large-scale data analysis, cloud and serverless technologies, federated learning, security aspects – applied to medical applications.
Alessandro Crimi
Dr Alessandro Crimi is a biomedical engineer and health economist who alternated his career between neuroimaging and healthcare management in low-income countries.
After completing his studies in engineering at the University of Palermo, he obtained a PhD in machine learning applied for medical imaging from the University of Copenhagen, and an MBA in healthcare management by the University of Basel.
Alessandro worked as post-doctoral researcher at the French Institute for Research in Computer Science (INRIA), Technical School of Switzerland (ETH Zurich), Italian Institute for Technology (IIT), and University Hospital of Zurich.
The post-doctoral years at European institutes were alternated by periods living in Ghana and other sub-Saharan countries, where Dr Crimi taught and carried out in-field projects about healthcare management for different organizations.
He taught for eight years at the African Institute for Mathematical Sciences (AIMS) in Ghana and South Africa on the machine learning in medicine course, where he also supervised numerous MSc theses. He has been the cofounder of a biotech startup operating between Ghana and Switzerland. Dr Crimi is currently involved in initiatives to promote entrepreneurship among women and individuals with immigrant backgrounds, as well as technology transfer projects for young scientists.
Tomasz Stopa
Dr Tomasz Stopa works in IBM Software Lab in Kraków, Poland. He obtained Ph.D. in theoretical solid state physics from AGH University of Science and Technology. IBM Master Inventor with multiple patents and scientific publications. As IBM Quantum Ambassador promotes IBM technologies within industry, academia and high schools.
Co-organizer of Kraków Quantum Informatics Seminar (KQIS).
Mauro Iacono
Mauro Iacono is an Associate Professor in Computing Systems at the Università degli Studi della Campania “Luigi Vanvitelli” in Caserta, Italy. He earned his Ph.D. in Electrical Engineering from the Seconda Università degli Studi di Napoli. Iacono’s research focuses on performance modeling of complex computer-based systems and privacy in computing systems. He has held multiple professorial roles across various departments at the Università degli Studi della Campania and has been a consultant for the Italian Ministry for Innovation and Technologies. Additionally, Iacono is a reserve officer in the Italian Air Force and an active member of several professional societies including IEEE and ECMS.
Mauro Iacono’s academic contributions are complemented by his engagement in various professional societies and a significant consultancy role in eGovernment projects for the Italian Ministry for Innovation and Technologies. His interdisciplinary expertise is reflected in his diverse reading and musical interests, ranging from classical literature and opera to heavy metal music, illustrating his broad cultural perspective. Iacono’s career is marked by a commitment to advancing both theoretical and applied aspects of computing and modeling, making substantial impacts in the fields of engineering and technology.
Sławomir Wiak
Professor Sławomir Wiak
Lodz University of Technology, Poland
Professor Sławomir Wiak DSc, PhD, MEng, Doctor Honoris Causa of the University d’Artois, Arras, France and Yaroslav-the-Wise Novgorod State University, Russia.
- Rector of Lodz University of Technology (2016-2020),
- Vice Rector of Lodz University of Technology (2012-2016)
- Dean of the Faculty Electrical, Electronic, Computer and Control Engineering, Lodz University of Technology (2008-2012)
- Director and the founder of the Institute of Mechatronics and Information Systems Lodz University of Technology (since 2008)
- Director of 5G Lodz University Competence Centre.
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Scientific specialization: Electrical Engineering and Computer Science (leading topics: numerical methods, data base-systems, AI (VR/AR), 5G, expert systems, e-learning systems, MEMS, mechatronic systems, engineering software).
Visiting Professor to University of Pavia (4 years), Italy and Universite d’Artois, Arras, France (8 years).
Invited lectures to foreign Universities – over 40.
Referee Reports (selected): Total number of review reports 620 (papers in Journals, PhD, DSc, books, professor titles, papers of the Conferences, grants). Referee reports of DSc: 18, Referee reports of Ph.D. degree: 24 (3 for University of Skopije, 1 for University of Vigo, 2 for INP-ENSEEIHT-LAPLACE Touluse), Referee reports of Professor title: 14 (1 for University of Pavia, Italy, 1 for École Polytechnique Fédérale de Lausanne – EPFL, 1 for University of Ghent, Belgium).
Referee of 5 Doctor Honoris Causa degree for eminent professors, among them – professor Kay Hameyer, Uniwersity RWTH Aachen.
Promoter of dr.h.c.: professor Sir Jim McDonald, Principal & Vice-Chancellor, University of Strathclyde, Glasgow, and dr Börje Ekholm, President and CEO (Chief Executive Officer) of Ericsson.
Chairman of the Session – 120 sessions at the Conferences (Conference examples: ICEM, ISEF, ACEMP, EHE, OIPE, ICAISC, etc.).
Member of International Steering Committees -17, author and co-author of over 430 publications (19 monographs and text books), member and manager of 21 national and 24 international grants. Associate Editor of Special issues of the Journals (selected): SENSORS, ELECTRONICS, IJAEM (International Journal of Applied Electromagnetics and Mechanics), COMPEL (The international journal for computation and mathematics in electrical and electronic engineering).
Recent monographs
Paolo Di Barba and Sławomir Wiak – MEMS: Field Models and Optimal Design, Springer, 2020.
Paolo Di Barba and Sławomir Wiak – Optimal Design and 3D printing and Metamaterials, IET (The Institution of Engineering and Technology), 2021.
Promotor of 14 PhD projects.
General Chairman of ISEF-International Conference on Electromagnetic Fields in Mechatronic, Electrical and Electronic Engineering.
Cooperation with the Universities (selected): University of Southampton (UK), University of West Bohemia – Pilzno (Czech Republic), University of Prague (Czech Republic), University of Arras (France), University of Maribor (Slovenia), University of Pavia (Italy), University of Vigo (Spain), Czech Academy of Sciences, Midle East Technical University in Ankara (Turkey), University of Valencia (Spain), University d’Atrois, Arras (France), Nowgorod State University (Russia), University of Skopije (North Macedonia), Université de Lorraine, Nancy (France).
Member of the Advisory Boards (selected)
National Board for FORESIGHT POLAND 2020 (2012-2016) – Nomination by Polish Ministry of Science and Higher Education
Member of National Board of Experts for Applied PhD Projects – Nomination by Polish Ministry of Science and Higher Education
Monitoring Committee of the Regional Operational Program of the Lodzkie Voivodship, 2027
Advisory Committee of Marshal of Lodz voivodship
Chairman of the Scientific Committee of Lodz Center for Teachers Competences, Development and Practical Education
Vice-Chairman of the Commission for IT Infrastructure of the Conference of Rectors of Academic Schools in Poland (KRASP)
Anti-crisis working group of the Conference of Rectors of Academic Schools in Poland (KRASP)
Monitoring Committee, Ministry of Funds and Regional Policy
Member of European University Association (EUA) Expert Group for “European Innovation Ecosystem”
Advisor of Lukasiewicz Net of Polish Research Institutes
Member of Managing Board – Bionanopark LTD. – Lodz Science and Technology Park (2020-2022)
Member of Advisory Board for Future Industry Platform of Lodz Region
Advisor for the strategy of Rector of Lodz University of Technology
Honorary distinctions (selected)
Award of Scientific Secretary of Polish Academy of Sciences
Individual Award of Scientific Secretary of IV Branch of Polish Academy of Sciences
Silver Cross of Merit and Gold Cross of Merit
Medal Pro-Patria
Honorary Medal of Lodz City Council
Medal of the 100th anniversary of Poland regaining independence
Knight’s Cross of the Rebirth of Poland (awarded by the President of the Republic of Poland in 2020), for outstanding merits in research, teaching and organizational work
Medal of 600 years granting city rights of Lodz City (metropolis of Lodz Region) in 2023
Member of Academy of Engineering in Poland
Vladimir Mityushev
Vladimir Mityushev was born in Uralsk, Kazakhstan, and went to the Kolmogorov boarding school of Moscow State University in 1975. He studied mathematics at Byelorussian State University, Minsk, and obtained his PhD in 1984. VM has worked in Polish Universities since 1991 and was a Guest Research Professor at Equipe Milieux Poreux et Fractures, Paris VI, France, in 1998-2018. His expertise lies in the fields of mathematical modeling, computer simulations, porous media, effective properties of composites with deterministic and random structures, representative volume elements, bioinformatics, and industrial mathematics. VM is a leader of the research group Materialica+.
Elżbieta Gajecka-Mirek
Assistant Professor at Cracow University of Technology – Faculty of Computer Science and Telecommunications.
Holds a PhD in mathematical science. Her scientific interests are statistics with focus on time series analysis, modeling and inference methodology.
Presents a strong academic background as well as strong backround in privat sector as a risk modeling and analytics specialist.
Anna Wójcicka
Assistant Professor at the Department of Automatics and Robotics at AGH University of Science and Technology, where she is affiliated with the research group Machine Vision Group AGH. Additionally, she plays an active role in the Center of Excellence in Artificial Intelligence. She earned her PhD in Computer Science in 2017. She has participated in numerous scientific and commercial projects at both national and international levels, including programs such NCN and NCBiR, FNP/SKILLS, FastTrac/TechVenture. She is a graduate of the TOP 500 Innovator program at Stanford University in the USA. She is passionate about computer vision and the use of artificial intelligence methods to solve various problems. Her work focuses on identifying novel approaches to implement these technologies in practical contexts, spanning academia and industry alike.
Łukasz Wąs
Łukasz Wąs, MSc., has been working continuously since 2010 at the Lodz University of Technology (PŁ) at the Institute of Mechatronics and Information Systems.
For conscientious performance of his teaching work, he received a teaching allowance from the Rector in the academic year 2019/2020 and 2021/2022. In the field of Computer Science.
He conducts classes on artificial intelligence and expert and inference systems, in which he uses current tools and techniques, e.g. convolutional neural networks and Deep Learning, as well as libraries of high-level languages (TesnsorFlow, Keras, PyTorch, PyNum) and programming (language Prolog), including the Case Study method. As part of improving his professional qualifications, he completed postgraduate studies in pedagogical preparation at the University of Social Sciences in Łódź.
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Additionally, during the pandemic period, he completed certified E-Learning courses, which he implemented as part of his classes. He has fourteen years of experience in teaching, which has resulted in, among others, to participate in teaching projects such as “E-Matura” and “E-Podręczniki” and innovation assessment for the business sector (Pricewaterhousecoopers, Telekomunikacja Polska). The experience he gained also allowed him to participate as a mentor in the international research project POLE 2013 “The Future of Digital Magazines”, co-financed by the University of Applied Sciences and Arts Narthwestern Switzerland. His research work is of significant social importance because it is used in dermatology and concerns skin image analyzes to determine the degree of skin disease using local segmentation features.
He is the author or co-author of 25 scientific articles in peer-reviewejournals and 15 papers presented at international conferences. He participated in four didactic and three research projects, including: Virtual medical data platform and modern diagnostics “MDB-MEDICAL DATA BANK”
The conducted research resulted in scientific research cooperation with the Faculty of Physics and Applied Computer Science of the University of Lodz and the Department of Dermatology and Venereology of the Medical University of Lodz. As part of the cooperation, six papaers have been published in peer-reviewed scientific journals, and the results were also presented at international conferences.
The subject of conducted research resulted in participation in research and teaching projects.
Participation in didactic projects:
- Participation in the E-Matura project, preparing substantive content and preparing and maintaining a website regarding the project under an employment contract with the Lodz University of Technology.
- Participation in the E-Podręczniki project, preparing substantive content regarding the project under an employment contract with the Lodz University of Technology.
- Conducting an assessment of IT innovation at Telekomunikacja Polska S.A. and Polska Telefonia Komórkowa – Centertel Sp. z o. o. for PricewaterhouseCoopers under an employment contract with the Lodz University of Technology.
Participation in research projects:
ASM Smart Data System (ASM SDS) – Research on the system for collecting, processing and distributing data using machine learning algorithms to modernize implementation and management processes and implement new and substantially improved research products and services at ASM-Centrum Research i Analiz Rynku Sp. z o. o. Project under the European Union program.
Digital Commune project grant – program of the Ministry of Digitization implemented under the Digital Poland program, priority axis V
Virtual platform for medical data and modern diagnostics “MDB-MEDICAL DATA BANK”
Participation in the international POLE research project “The future of Digital Magazines”, Windish, Switzerland. Project co-financed by the University of Applied Sciences and Arts Narthwestern Switzerland FHNW
Dominika Ciupek
Dominika Ciupek is a graduate of Biomedical Engineering at the Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering at the AGH University of Krakow. In 2021, she defended her engineering thesis “Multicompartment models in diffusion-relaxometry magnetic resonance imaging” and in 2022, with distinction, her master’s thesis on the analysis of the variability of microstructural parameters along the white matter pathways across the lifespan. Currently, she is pursuing her PhD at Sano as part of the Extreme-scale Data and Computing team.
Jan Fiszer
Student at AGH, studying Computer Science and Intelligent Systems, willing to use AI for more admirable purposes than suggesting a TikTok. Fascinated by the human brain and working on federated learning for magnetic resonance imaging (MRI).
More About Our Courses
Brain connectivity. How to predict neurodegeneration and brain causality with machine learning, and how those compare with traditional simulations – Alessandro Crimi
Medical imaging, particularly neuroimaging, has experienced a paradigm shift with the integration of machine learning techniques. This talk delves into the transformative role of machine learning in analyzing neuroimaging data, with a focus on its applications and implications in clinical practice.
The advent of machine learning algorithms has enabled the extraction of intricate patterns from complex neuroimaging datasets, providing insights into neurological disorders with unprecedented precision. Through the amalgamation of advanced imaging modalities such as magnetic resonance imaging (MRI), positron emission tomography (PET), and computed tomography (CT), coupled with machine learning models, researchers have achieved remarkable strides in disease diagnosis, prognosis, and treatment response prediction.
This presentation will elucidate various machine learning approaches employed in neuroimaging analysis, including but not limited to convolutional neural networks (CNNs), recurrent neural networks (RNNs), and graph-based methods. These methodologies empower the automatic segmentation, classification, and feature extraction of brain structures and abnormalities, facilitating early detection and characterization of neurological conditions such as Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, and brain tumors.
More specifically we will consider the cases of misfolded protein spreading in Alzheimer, and effective connectivity (causality) in stroke patients and how these compare to simulation based models (epidemic spreading or heat/diffusion equations).
References:
https://academic.oup.com/cercor/article/33/24/11471/7311320
https://bam.sano.science
Federated Learning in Flower – Maciej Malawski
Join our workshop on “Federated Learning in Flower” where we explore the versatile federated learning framework, Flower. This session offers a comprehensive dive into how Flower facilitates federated learning across various workloads, machine learning frameworks, and programming languages. Discover a unified approach to federated analytics and evaluation, ideal for anyone interested in the cutting-edge of distributed machine learning technologies. Engage with experts and peers to understand how Flower can tailor federated learning to diverse research and industry applications.
Analytical Representative Volume Element (aRVE) and its applications – Vladimir Mityushev
The theoretical foundation of higher precision investigations of dispersed random composites is planned to be present, as well as practical implementation of the theory to complex heterogeneous media such as composites, biological structures, clouds, etc. The current state of the art of the principles of mathematical models is outlined. We discuss the mathematical model and empirical method notions, highlighting the discrepancies when various engineering approaches overlook asymptotic analysis. The study of structurally disordered dispersed patterns and the hidden relationships between the geometric random characteristics of composites and their physical properties is a common focus in various branches of mechanics, mathematics, and physics. Our objective is to address the challenge of providing a constructive quantitative description of the chaos/regularity, e.g., dislocations, exhibited by heterogeneous media. The image analysis and computation of structural sums will be discussed. Random simulations will be performed with the participants by using the computational packages.
Image processing and analysis – Anna Wójcicka
The aim of the workshops is to familiarize machine learning engineers with the key principles of working with medical datasets. During the course, typical metrics will be discussed, and methods for handling issues with small datasets, image artifacts, and unbalanced classes will be presented. The workshop program will include both classic vision algorithms and convolutional neural networks.
Virtual platform for medical data and modern diagnostics MDB-MEDICAL DATA BANK – Sławomir Wiak
Project “Virtual platform for medical data and modern diagnostics MDB-MEDICAL DATA BANK”. will be implemented under the Operational Programme Digital Poland 2014-2020. Digital access to public sector information from administrative sources and scientific resources.
The main objective of the project is to improve the quality of data, make public sector information available, enable the reuse of complementary scientific resources held by Lodz University of Technology and the CZMP Institute, as well as create a system for storing and making available in digital form the data of the ICZMP and TUL.
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As a result of the project, a common database of medical and modern diagnostics will be created – at least 1,000,400 medical data. Before being made available, the data will be digitized, anonymized, grouped, organized, and described with metadata.
Digital technology is reshaping the standards of work of specialists. Thanks to the project, it will be possible to use the created database for biometric analyses, didactic work, self-education of doctors, statistics. It will also be a unique source of popular science information for the public.
The project will serve, for m.in, the development of oncological diagnostics or rare diseases, enabling further research on these disease entities.
IT system has been built that will integrate all sources of data owned by theand acquired by the Lodz University of Technology and the Polish Mother’s Memorial Hospital Institute. Thanks to the built system, it will be possible to share the collected information on the website and dedicated APIs, with an appropriate level of security.
Prof. Slawomir Wiak, DSc, PhD, MEng., Dr.h.c.
Algorithms of Selection and Aggregation Coefficients in Methods of Categorizing Skin Lesions – Łukasz Wąs
- As part of the existing scientific consortium, bringing together the three largest universities in the Łódź Voivodeship, research is carried out aimed at:
▸ Analysis of photos in terms of skin changes
▸ Creation of a system supporting the work of experts.
The result of the research is the development of proprietary algorithms examining the degree of variability using local features using, for example, factor analysis methods in the analysis and segmentation of dermatological images. On this basis, an expert decision support system was developed. We are rated by a scientific unit and expert dermatologists.
Scientific Committee of the 1st ECMS International School for Young Reserchers
- Mauro Iacono – School Director
- Natalia Ryłko – Edition Director
- Vladimir Mityushev – Edition Co-Director
- Daniel Grzonka – Edition Co-Director
Organisers of the School
European Council for Modelling and Simulation
Cracow University of Technology – Faculty of Computer Science and Telecommunications
Cracow University of Technology – Doctoral School
Università degli Studi della Campania Luigi Vanvitelli
Center of Excellence in Artificial Intelligence AGH
