Keynote Speakers

 

 

Prof. Leopoldo Angrisani, IEEE Fellow
University of Napoli Federico II, Italy
MedITech Competence Center I4.0 - Technical-Scientific Committee Coordinator 

 

Leopoldo Angrisani is Full Professor of Electrical and Electronic Measurements with the Department of Information Technology and Electrical Engineering of the University of Naples Federico II, Italy. He is also Chair of the Board of the Ph.D. Program ICTH - Information and Communication Technology for Health of the University of Naples Federico II.
His research activity has always been focused on topics related to electrical and electronic measurements. He currently pays attention to the role of measurement in the IoT field and, more generally, in the Industry 4.0 and Health 4.0 fields, cyber-physical measurement systems, measurement of ICT systems sustainability and sustainability of measurements, sensors, sensor networks, and measurement methods in precision agriculture and livestock farming, operation and performance assessment of communication systems, equipment, and networks, measurement uncertainty, impact of quantum technologies on measurements, metrological characterization of advanced human-to-machine interfaces.
He was and is currently involved in many industrial research projects, in cooperation with small, medium, and great enterprises, for which he played and is currently playing the role of scientific coordinator. He is currently the Coordinator of the Technical/Scientific Committee of MedITech – one of the eight Italian Competence Centers on I4.0 enabling technologies.
He is Fellow Member of the IEEE Instrumentation and Measurement and Communications Societies. He was Honorary Chairman of the first (M&N 2019) and second (M&N 2022) edition of the IEEE International Symposium on Measurements & Networking, General Chairman of the second edition (MetroInd4.0&IoT 2019) of the IEEE International Workshop on Metrology for Industry 4.0 and IoT, and General Chairman of the first edition (IEEE MeAVeAS 2023) of the IEEE International Workshop on Measurements and Applications in Veterinary and Animal Sciences. He is vice-chair of the Italian Association “GMEE-Electrical and Electronic Measurements Group”, and corresponding member of the Accademia Pontaniana in Naples, the oldest Italian academy, with almost 600 years of history, which has always brought together renowned Neapolitan scholars.
In 2009, he was awarded the IET Communications Premium for the paper entitled “Performance measurement of IEEE 802.11b-based networks affected by narrowband interference through cross-layer measurements” (published in IET Communications, vol. 2, No. 1, January 2008).
The IEEE Instrumentation & Measurement Society Italy Chapter, which he has been chairing since 2015, was awarded in 2016 the prestigious recognition “I&M Society Best Chapter Award” by the IEEE Instrumentation & Measurement Society, in 2017 the prestigious recognition “Most Improved Membership Chapter for 2016” by the IEEE Italy Section, in 2018 the prestigious recognition “Most Innovative Chapter 2018” by the IEEE Italy Section, and in 2021 the prestigious recognition "Chapter of the Year 2021" by the IEEE Region 8 (Europe, Middle Est, Africa).
In 2021, he was awarded the prestigious recognition “2021 IEEE Instrumentation and Measurement Society Technical Award” with the following citation “For contributions in the advancement of innovative methods and techniques for communication systems test and measurement”.

Speech Title: Measuring with artificial intelligence: opportunities, challenges, and future perspectives
Abstract:
Artificial Intelligence (AI) is becoming increasingly relevant in many areas of engineering, ranging from electronics and telecommunications to robotics and biomedical engineering, among others. Metrology is not extempt form this trend. As a matter of fact, AI models are also starting to play a significant role in measurement tasks, especially when direct measurement of a physical quantity is complex, expensive, or not feasible. For instance, AI models can be used to estimate temperature, pressure, or displacement by processing signals or images that are easier to acquire. In simple terms, an AI model can be seen as a system that learns how to relate input quantities (usually called predictors) to output quantities (what we want to measure). Unlike traditional measurement framework, however, AI models do not follow deterministic physical laws, but rather learn their behavior from training data. This introduces an additional source of uncertainty as the model’s performance depends on the quality of the training data, the model structure, and the way it was configured. These aspects affect the trustworthiness in the output provided, and need to be considered alongside the established uncertainty contributions related to input data acquisition.
In this talk, a practical approach is presented to identify and evaluate the uncertainty introduced by the adoption of an AI model. Strategies are also outlined to reduce this uncertainty, allowing AI-based outputs to be considered as fully-fledged measurement results. This perspective opens the door to tangible benefits for our society, increasingly shaped by data-driven technologies and AI.

 

 

 

 

 

Prof. Dragica Vasileska, IEEE Fellow
Arizona State University, USA
Senior Global Futures Scientist, Global Futures Scientists and Scholars

 

Dragica Vasileska (F’2019) received the B.S.E.E. (Diploma, equivalent to M.S. Degree in USA) and the M.S.E.E. Degree from the University Sts. Cyril and Methodius (Skopje, Republic of North Macedonia) in 1985 and 1991, respectively, and a Ph.D. Degree from Arizona State University in 1995. From 1995 until 1997, she held a faculty research associate position within the Center of Solid State Electronics Research at Arizona State University. In the fall of 1997, she joined the faculty of electrical engineering at Arizona State University. In 2002 she was promoted to associate professor and in 2007 to full professor. Her research interests include semiconductor device physics and semiconductor device modeling, with strong emphasis on quantum transport and Monte Carlo device simulations. Recently her focus also includes modeling metastability and reliability of solar cells. Prof. Vasileska has published more than 200 publications in prestigious scientific journals, over 200 conference proceedings refereed papers, 25 book chapters, has given numerous invited talks and is a co-author on three books: "Computational Electronics," D. Vasileska and S. M. Goodnick, Morgan & Claypool, 2006; "Computational Electronics: Semiclassical and Quantum Transport Modeling," D. Vasileska, S. M. Goodnick and G. Klimeck, CRC Press, 2010, and "Modeling Self-Heating Effects in Nanoscale Devices," K. Raleva, A. Shaik, D. Vasileska and S. M. Goodnick, Institute of Physics Publishing, Morgan & Claypool, 2017. She is also an editor of two books: "Cutting Edge Nanotechnology," In-Tech, 2010 and "Nano-Electronic Devices: Semiclassical and Quantum Transport Modeling" (co-editor S. M. Goodnick), Springer, July 2011. She has many awards including the best student award from the School of Electrical Engineering in Skopje since its existence (1985, 1990). She is also a recipient of the 1998 NSF CAREER Award. Her students have won numerous awards at prestigious  international scientific  conferences.

 

 

 

 

 

Hüseyin ÜVET
Yildiz Technical University, Turkey

 

Dr. Huseyin Uvet is an Associate Professor in the Department of Mechatronics Engineering at Yildiz Technical University. He holds a Bachelor of Science in Computer Engineering and pursued his graduate studies at Osaka University in Japan, where he earned both a Master of Science and a Ph.D. in System Innovation, supported by the prestigious Japanese Government (Monbukagakusho) Scholarship. Following his doctoral studies, he was awarded the Japan Society for the Promotion of Science (JSPS) Fellowship to conduct post-doctoral research at Nagoya University's Micro-Nano Mechatronics Center.
With over 15 years of experience, Dr. Uvet has established himself as an expert in healthcare robotics, AI-driven medical technologies, and sports engineering. His research focuses on micro-nano robotics, holographic imaging, AI-based diagnostics, and autonomous systems. He has a proven record of leading large-scale R&D projects, securing over $10 million in research funding from institutions such as the European Union and The Scientific and Technological Research Council of Turkey (TÜBİTAK).
Dr. Uvet has successfully bridged the gap between engineering and medicine by developing groundbreaking solutions, including robotic surgical systems and AI-powered diagnostic tools. His expertise is highly sought after, and he has provided senior consultancy services to numerous prominent organizations. His consulting portfolio includes collaborations with TURKCELL on IoT 4.0 integration and digital health technologies , Turkish Airlines on a VR Flight Simulator Program , DHL Logistics on warehouse automation systems , and the Antalya Muratpaşa Municipality on Smart Cities programs and EU projects.
As an entrepreneur for two R&D startup companies and a leader in academic and administrative roles, Dr. Uvet has consistently driven innovation. His work is documented in numerous patents and high-impact publications, reflecting his significant contributions to mechatronics, and biomedical and sports technologies.

Speech Title: The Symbiotic Future of AI, Mechatronics, and Biomedical Innovation
Abstract:
Today’s toughest engineering problems call for answers that go beyond old-school boundaries. The fusion of smart computing with cutting-edge mechanical systems is opening doors, especially in medicine. This talk dives into how these fields work together, showing how clever algorithms and intricate machine designs are steering the future of tech.
We’ll look at this blend from different angles. On the big-picture side, we’ll talk about how sharp, efficient algorithms are transforming medical diagnostics with top-notch image analysis. On the smaller scale, we’ll dig into how smart control systems and high-precision vision tech allow tiny robots to move with pinpoint accuracy and spark new devices using effects like fluid dynamics. Pulling from a range of projects—like cancer detection powered by intelligent systems or guiding miniature robots without wires—this speech will shine a light on the vital role of engineers who bridge disciplines to turn complex ideas into real-world solutions that make a difference.

 

 

 

Gokturk Poyrazoglu (Senior Member, IEEE)
Department Head, Electrical & Electronics Engineering
Director, Grid Operations and Planning Laboratory
Ozyegin University, Istanbul, Türkiye

 

Dr. Gokturk Poyrazoglu is an Electrical Engineer and Assistant Professor at Ozyegin University, Istanbul, where he leads the Electrical & Electronics Engineering Department and directs the Grid Operations and Planning Laboratory. He also serves as the Standards Coordinator for IEEE Türkiye.
He earned his M.Sc. (2013) and Ph.D. (2015) in Electrical Engineering from the State University of New York at Buffalo, USA. Before joining academia, Dr. Poyrazoglu gained industry experience in the USA as a Scientist at Mitsubishi Electric Research Laboratories (MERL, Boston), a Power Systems Consultant at Alevo Analytics (Charlotte, NC), and a Grid Operations and Planning Scientist at EPRI (Electric Power Research Institute). Since 2017, he has been a faculty member at Ozyegin University.
Dr. Poyrazoglu is recognized for his leadership in university–industry collaboration. He was awarded the “University-Business World Cooperation Award” at the 2022 YÖK Outstanding Achievement Awards for his ‘Harvesting Energy Efficiency in the Electric Distribution Sector’ project (TRAFORM), conducted in partnership with eight electric distribution companies and ELDER, with support from EPDK.
He also won the “Best Paper Award” at IYCE’24 in France for his co-authored study on the spatio-temporal impacts of EV charging loads on locational marginal prices, a key contribution to sustainable energy markets and EV infrastructure planning.
His research portfolio includes over 50 international peer-reviewed journal and conference publications, with active contributions to recent works in areas such as economic dispatch with physics-informed learning, EV charging hosting capacity, overvoltage mitigation in PV-rich networks, and sustainable nanogrid techno-economic assessments.
Dr. Poyrazoglu’s core research interests lie in energy economics, operations research in energy systems, renewable energy integration, smart grid applications, and power system monitoring and control, particularly focusing on power grid resilience, efficiency, and e-mobility integration.
Speech Title: Energy and Infrastructure for Sustainable Electrification

Abstract:
The global energy landscape is undergoing a rapid transformation driven by decarbonization, decentralization, and digitalization. At the center of this transformation lies sustainable electrification, which requires the integration of renewable energy resources and the development of flexible, resilient, and intelligent infrastructures.
This keynote will address electrification's technical, economic, and regulatory dimensions, with a particular emphasis on distribution networks, energy storage systems, and e-mobility integration. The talk will showcase pioneering initiatives such as the country’s first battery implementation at the distribution level, the first sustainable EV charging pricing model, and university–industry partnerships that have set new energy efficiency and digitalization standards.
Special attention will be given to grid flexibility, forecasting, and optimization frameworks, where artificial intelligence and operations research play an increasing role in managing uncertainty and ensuring efficiency. The keynote will also discuss the evolving role of distribution system operators and highlight how regulatory mechanisms, market design, and innovative business models can accelerate sustainable electrification.