POSTECH and IBM Researchers Unveil Hidden Mechanisms in Next-Generation AI Memory Devices.

IEEE ECIS 2025 aims to provide an international forum for sharing cutting-edge research, breakthroughs, and innovations in the fields of electronic engineering, communication systems, and intelligent science applications. This conference encourages interdisciplinary collaboration, fostering academic and industrial partnerships across borders.

Following the success of the inaugural ECIS 2024, which achieved full EI indexing for its 2024 proceedings, IEEE ECIS is delighted to invite scholars, researchers, and industry professionals from around the world to submit original research.

The integration of smart grid technology and renewable energy sources has become crucial for sustainable development. Following the success of SEGRE 2024, SEGRE 2025 continues to serve as a premier platform for global researchers, engineers, and industry leaders to exchange cutting-edge ideas, showcase innovations, and foster interdisciplinary collaborations. This conference aims to bridge theoretical advancements with practical applications, addressing challenges and opportunities in renewable energy and smart grid technologies.

An interdisciplinary research team from the LKS Faculty of Medicine of the University of Hong Kong (HKUMed), the InnoHK Laboratory of Data Discovery for Health (InnoHK D24H), and the London School of Hygiene & Tropical Medicine (LSHTM) has unveiled the world’s first artificial intelligence (AI) model designed to classify both the cancer stage and risk category of thyroid cancer, achieving impressive accuracy exceeding 90%. This innovative HKUMed AI model promises to significantly cut frontline clinicians’ pre-consultation preparation time by approximately 50%, aligning with the HKSAR Government’s initiative to harness AI technology in healthcare. The findings were published in the journal npj Digital Medicine.

Strong methods do exist for measuring animal movement in the context of energy expenditure, but these are limited by the physical size of the equipment used. Now, in a paper published in the Journal of Experimental Biology, researchers from the Marine Biophysics Unit at the Okinawa Institute of Science and Technology (OIST), in collaboration with Professor Amatzia Genin from the Hebrew University of Jerusalem, describe an innovative method for measuring energy usage during movement with video and 3D-tracking via deep learning.

A new study led by researchers at the University of California San Diego offers a first-of-its-kind look at how deeper coordination among Western U.S. states could lower the cost of decarbonizing the electric grid—and speed up the clean energy transition.