Latest news with #DepartmentofMaterialsScienceandEngineering
Associated Press
12-06-2025
- Health
- Associated Press
University of Ioannina Launches Groundbreaking MSc in Digital Health in Greece
The University of Ioannina proudly announces the launch of its cutting-edge, two-year full-time MSc program in Digital Health. 'We remain committed to providing distinctive global experiences and training that enhance the international credentials'— DImitris I. Fotiadis IOANNINA, IOANNINA, GREECE, June 12, 2025 / / -- University of Ioannina Launches Groundbreaking MSc in Digital Health in Greece. The University of Ioannina proudly announces the launch of its cutting-edge, two-year full-time MSc program in Digital Health, inviting future innovators and leaders to shape the next era of healthcare. An innovative MA in digital health unveiled three of the most prestigious academic institutions of Greece, located in two key cultural and economic centers: Ioannina and Crete. The Department of Materials Science and Engineering of University of Ioannina has partnered with the Medical School and the Biomedical Research Institute - Foundation for Research and Technology – Hellas (FORTH) to offer a high quality program on two strategic and complementary fields: Data experts in Health and Digital Health Transformation. The MSc program aims to impart the multidisciplinary knowledge and abilities required to spur innovation in the rapidly expanding field of digital health and is designed for professionals in their early or later career stages, as well as students who just graduated. It accepts students from various fields such as Medical Sciences ( Pharmacology, Exact sciences, Engineering schools and Schools of Economics. Designed to prepare future global leaders, the new MSc in Digital Health Dual Degree in offers an outstanding academic foundation in both management and technology, along with a meaningful international experience. This will enable students not only to acquire new knowledge but also to build a broad and diverse network within three leading academic communities. The program is distinct from other master's program as it offers the opportunity to enroll in five in-demand fields like Foundation of Digital Health and Informatics, Information and Communication Technologies (ICT), Data Science, Data-driven Decision-making in Healthcare, Healthcare Research, Ethics, and Digital Transformation. Also the program stands out from other Master's degrees as it is part of the prestigious European initiative DS4Health—a collaborative project involving six renowned institutions: NOVA University Lisbon, RWTH Aachen University, the University of Ioannina, Tel Aviv University, Institut Polytechnique de Paris, and the University of Vienna. This strategic alliance fosters interdisciplinary innovation and academic excellence across borders. 'The launch of this new program in partnership with the Medical School of Ioannina and the Biomedical Research Institute - Foundation for Research and Technology – Hellas (FORTH), a world-renowned institution with a long tradition of academic excellence, represents another step in consolidating Department's of Materials Science and Engineering of University of Ioannina international offerings,' said Professor Dimitris Fotiadis, program director. 'We remain committed to providing distinctive global experiences and training that enhance the international credentials of our students and expand their opportunities in the global and multicultural job market, in strategic and innovative areas of digital health' The MSc in Digital Health is a two-year full time MSc program (four semesters), offering a total of 120 ECTS. The last but not least is that the program will take place in a magical land, Ioannina the capital of Epirus. Set on the western shore of the lovely Lake Pamvotis, Ioannina is one of northern Greece's most atmospheric cities, and one of its more cultured and wealthy, as it was famous throughout the Ottoman Empire for its silver artisans, is offered for exploration. Applications are open. For more information and entry requirements please visit: About the Department of Materials Science and Engineering of University of Ioannina The Department of Materials Science and Engineering was established in 1999 and belongs to the School of Engineering by providing 5 years of high-level education and training in Materials Science and Technology. The Unit of Medical Technology and Intelligent Information Systems (MedLab) which belongs to the Department of Materials Science and Engineering is a highly innovative and self-contained research unit strongly activated in the fields of Biomedical Engineering and development of Intelligent Information systems. It has an internationally acknowledged excellence in conducting high quality scientific research and developing innovative Information Technology (IT) applications, products, and services. About the Faculty of Medicine The Faculty of Medicine of the School of Health Sciences of the University of Ioannina was established in 1977 and recently has been highly recognized since has been ranked 1st among all Medical Faculties in Greek Tertiary Education, according to the University of Leiden Ranking (the Netherlands) for 2019, as well as for the 2018 and the 2017. About the Foundation for Research and Technology - Hellas (FORTH) The Foundation for Research and Technology - Hellas (FORTH) was founded in 1983. It is one of the largest research centers in Greece with well-organized facilities, highly qualified personnel, and a reputation as a top-level research institution worldwide. FORTH comprises ten Research Institutes. Its headquarters and central administration are based in Heraklion, Crete. In Ioannina Biomedical Research Institute (BRI) of the Foundation for Research and Technology (FORTH) was established at Ioannina in 1998 as an independent institute. In 2001, BRI joined the Foundation for Research and Technology (FORTH), becoming its seventh Institute. Research in BRI focuses in basic molecular and cellular biology areas of biomedical research with high interest in public health and biomedicine. Vasiliki Tsitsou Univeristy of Ioannina +30 697 187 8099 email us here Visit us on social media: LinkedIn Instagram Facebook X Other Legal Disclaimer: EIN Presswire provides this news content 'as is' without warranty of any kind. We do not accept any responsibility or liability for the accuracy, content, images, videos, licenses, completeness, legality, or reliability of the information contained in this article. If you have any complaints or copyright issues related to this article, kindly contact the author above.
Yahoo
05-04-2025
- Science
- Yahoo
Redefining the transistor: The ideal building block for artificial intelligence
SINGAPORE, March 28, 2025 /PRNewswire/ -- The team led by Associate Professor Mario Lanza from the Department of Materials Science and Engineering in the College of Design and Engineering at the National University of Singapore, has just revolutionised the field of neuromorphic computing by inventing a new super-efficient computing cell that can mimic the behaviour of both electronic neurons and synapses. The work, titled "Synaptic and neural behaviours in a standard silicon transistor" was published in the scientific journal Nature on 26 March 2025 and is already attracting interest from leading companies in the semiconductor field. Electronic neurons and synapses are the two fundamental building blocks of next-generation artificial neural networks. Unlike traditional computers, these systems process and store data in the same place, eliminating the need to waste time and energy transferring data from memory to the processing unit (CPU). The problem is that implementing electronic neurons and synapses with traditional silicon transistors requires interconnecting multiple devices — specifically, at least 18 transistors per neuron and 6 per synapse. This makes them significantly larger and more expensive than a single transistor. The team led by Professor Lanza has found an ingenious way to reproduce the electronic behaviours characteristic of neurons and synapses in a single conventional silicon transistor. The key lies in setting the resistance of the bulk terminal to a specific value to produce a physical phenomenon called "impact ionisation," which generates a current spike very similar to what happens when an electronic neuron is activated. Additionally, by setting the bulk resistance to other specific values, the transistor can store charge in the gate oxide, causing the resistance of the transistor to persist over time, mimicking the behaviour of an electronic synapse. Making the transistor operate as a neuron or synapse is as simple as selecting the appropriate resistance for the bulk terminal. The physical phenomenon of "impact ionisation" had traditionally been considered a failure mechanism in silicon transistors, but Professor Lanza's team has managed to control it and turn it into a highly valuable application for the industry. This discovery is revolutionary because it allows the size of electronic neurons to be reduced by a factor of 18 and that of synapses by a factor of 6. Considering that each artificial neural network contains millions of electronic neurons and synapses, this could represent a huge leap forward in computing systems capable of processing much more information while consuming far less energy. Furthermore, the team has designed a cell with two transistors — called Neuro-Synaptic Random Access Memory (NSRAM) — that allows switching between operating modes (neuron or synapse), offering great versatility in manufacturing since both functions can be reproduced using a single block, without the need to dope the silicon to achieve specific substrate resistance values. The transistors used by Professor Lanza's team to implement these advanced neurons and synapses are not cutting-edge transistors like those manufactured in Taiwan or Korea, but rather traditional 180-nanometer node transistors, which can be produced by Singapore-based companies. According to Professor Lanza, "once the operating mechanism is discovered, it's now more a matter of microelectronic design". The first author of the paper, Dr Sebastián Pazos, who is from King Abdullah University of Science and Technology, commented, "Traditionally, the race for supremacy in semiconductors and artificial intelligence has been a matter of brute force, seeing who could manufacture smaller transistors and bear the production costs that come with it. Our work proposes a radically different approach based on exploiting a computing paradigm using highly efficient electronic neurons and synapses. This discovery is a way to democratise nanoelectronics and enable everyone to contribute to the development of advanced computing systems, even without access to cutting-edge transistor fabrication processes." Read more at: View original content: SOURCE National University of Singapore Sign in to access your portfolio
Associated Press
29-03-2025
- Science
- Associated Press
Redefining the transistor: The ideal building block for artificial intelligence
SINGAPORE, March 28, 2025 /PRNewswire/ -- The team led by Associate Professor Mario Lanza from the Department of Materials Science and Engineering in the College of Design and Engineering at the National University of Singapore, has just revolutionised the field of neuromorphic computing by inventing a new super-efficient computing cell that can mimic the behaviour of both electronic neurons and synapses. The work, titled " Synaptic and neural behaviours in a standard silicon transistor" was published in the scientific journal Nature on 26 March 2025 and is already attracting interest from leading companies in the semiconductor field. Electronic neurons and synapses are the two fundamental building blocks of next-generation artificial neural networks. Unlike traditional computers, these systems process and store data in the same place, eliminating the need to waste time and energy transferring data from memory to the processing unit (CPU). The problem is that implementing electronic neurons and synapses with traditional silicon transistors requires interconnecting multiple devices — specifically, at least 18 transistors per neuron and 6 per synapse. This makes them significantly larger and more expensive than a single transistor. The team led by Professor Lanza has found an ingenious way to reproduce the electronic behaviours characteristic of neurons and synapses in a single conventional silicon transistor. The key lies in setting the resistance of the bulk terminal to a specific value to produce a physical phenomenon called 'impact ionisation,' which generates a current spike very similar to what happens when an electronic neuron is activated. Additionally, by setting the bulk resistance to other specific values, the transistor can store charge in the gate oxide, causing the resistance of the transistor to persist over time, mimicking the behaviour of an electronic synapse. Making the transistor operate as a neuron or synapse is as simple as selecting the appropriate resistance for the bulk terminal. The physical phenomenon of 'impact ionisation' had traditionally been considered a failure mechanism in silicon transistors, but Professor Lanza's team has managed to control it and turn it into a highly valuable application for the industry. This discovery is revolutionary because it allows the size of electronic neurons to be reduced by a factor of 18 and that of synapses by a factor of 6. Considering that each artificial neural network contains millions of electronic neurons and synapses, this could represent a huge leap forward in computing systems capable of processing much more information while consuming far less energy. Furthermore, the team has designed a cell with two transistors — called Neuro-Synaptic Random Access Memory (NSRAM) — that allows switching between operating modes (neuron or synapse), offering great versatility in manufacturing since both functions can be reproduced using a single block, without the need to dope the silicon to achieve specific substrate resistance values. The transistors used by Professor Lanza's team to implement these advanced neurons and synapses are not cutting-edge transistors like those manufactured in Taiwan or Korea, but rather traditional 180-nanometer node transistors, which can be produced by Singapore-based companies. According to Professor Lanza, 'once the operating mechanism is discovered, it's now more a matter of microelectronic design'. The first author of the paper, Dr Sebastián Pazos, who is from King Abdullah University of Science and Technology, commented, 'Traditionally, the race for supremacy in semiconductors and artificial intelligence has been a matter of brute force, seeing who could manufacture smaller transistors and bear the production costs that come with it. Our work proposes a radically different approach based on exploiting a computing paradigm using highly efficient electronic neurons and synapses. This discovery is a way to democratise nanoelectronics and enable everyone to contribute to the development of advanced computing systems, even without access to cutting-edge transistor fabrication processes.'
