Professor Michel MAROT is affiliated with Telecom SudParis, where he holds the position of Professor in the NeSS department. His research focuses on networking, wireless communication systems, performance evaluation, smart grids, and machine learning applications in telecommunications. MAROT has contributed to advancements in vehicular networks (VANETs/V2V), IoT architectures (LoRaWAN), and energy-efficient protocols for wireless sensor networks (WSNs). He has led studies on coalition formation in smart grids, reinforcement learning for policy optimization, and network resource management in 6G systems. Key research areas include optimizing network performance through cross-layer design, improving QoS in mobile and vehicular environments, and deploying intelligent reflecting surfaces (IRS) for 6G. His work frequently addresses challenges in mobility management, collision avoidance, and energy efficiency in distributed systems. MAROT has co-authored influential papers in journals like Neurocomputing, IEEE Transactions on Smart Grid, and IEEE Open Journal of the Communications Society. His research group (SAMOVAR/NeSS) develops practical solutions for real-world networks, including cold chain monitoring systems using sensor networks and DNS-based optimizations for SCHC protocols. MAROT’s recent work explores machine learning embedded in LPWAN sensors and mobility-aware resource allocation in LoRaWAN.
Olcay Bay is a Researcher affiliated with the Faculty of Engineering at Vrije Universiteit Brussel (VUB), specializing in the Electrical Engineering and Power Electronics department. He is part of the MOBI - Electromobility Research Centre and holds a doctoral scholarship. His work focuses on advanced power electronics systems, particularly leveraging Gallium Nitride (GaN) technologies for electric vehicle applications. Key areas include high-performance power modules, thermal management of semiconductor devices, and traction inverter design. Research Interests: Evaluation of GaN-based power electronics for electric vehicles Thermal optimization of power transistors and inverters Development of low-voltage/high-current power systems Bi-directional on-board charger topologies Collaborations: Active involvement in interdisciplinary projects with industry partners, including roles in the HiEFFICIENT consortium. Recent contributions include presentations at the 2024 IEEE Vehicle Power and Propulsion Conference and the 2023 European Conference on Power Electronics. Advising & Supervision: Co-supervised Master's thesis titled "Modeling and Implementation of DC Microgrid for Lighting Application" (2023). Labs/Teams: Core member of VUB's Electromobility Research Group, contributing to the MOBI centre's mission on sustainable transportation technologies.
Uwe Kersting is a full Professor at the Institute of Biomechanics and Orthopaedics, German Sport University Cologne. He is actively engaged in research, teaching, and supervision within the fields of sports biomechanics, orthopaedics, and injury prevention. His work spans multiple projects, collaborations, and publications, focusing on athlete safety and biomechanical analysis. Academic Rank: Professor Institution: German Sport University Cologne Department: Institute of Biomechanics and Orthopaedics Email: u.kersting@dshs-koeln.de Research Interests: Uwe Kersting's research is centered on biomechanics and orthopaedics, with a strong emphasis on injury mechanisms in athletes. His work investigates knee joint vulnerability, lower limb loading, muscle activity during dynamic tasks, and the development of wearable technologies for long-term monitoring. He applies 3D biomechanical analysis to understand unplanned movements in sports such as handball and snowboarding. Publication Trends: His recent publications (2023–2025) show a consistent focus on ACL injury prevention, joint loading in change-of-direction tasks, and the use of advanced modeling and measurement systems. Themes include EMG analysis, statistical shape modeling, shear force measurement, and real-time feedback in training. The research bridges clinical orthopaedics, sports science, and engineering. Scientific Awards: No awards mentioned in the provided text. Advising and Grants: Prof. Kersting actively supervises PhD and master’s students, including Kevin Bill, Patrick May, and Jan-Peter Goldmann. He is the primary advisor on multiple doctoral theses. He leads and participates in externally funded and self-financed research projects such as LoStInCrowds and FeeTISH, which focus on injury risk in crowded environments and snowboarding technique, respectively. Labs and Teams: He is a core member of the Institute of Biomechanics and Orthopaedics, collaborating with researchers like Steffen Willwacher (formerly), Cynthia Fantini Pagani, and Jasper Kwasny. His team conducts lab-based and field biomechanical studies involving motion capture, force plates, and wearable sensors.
Prof. Dr. Walter Commerell serves as Professor at Technische Hochschule Ulm (THU) , holding the role of International Representative for the Faculty of Production Engineering and Production Management. He is the Spokesperson for ASIM (Simulation of Technical Systems Division) and Head of Steinbeis Transfer Center System Design , while also being a member of the International Energy Competence Center (IECN) and Institutes for Energy and Drive Technology/Vehicle Systems Technology.
Amoon Jamzad is an Adjunct Assistant Professor at the School of Computing, Queen's University, and a postdoctoral fellow at Med-I Lab. He holds a BSc in Electrical Engineering (Electronics) from University of Tehran (2007), an MSc in Biomedical Engineering (2010), and a PhD in Biomedical Engineering (2015). His doctoral research focused on noninvasive ultrasound analysis of kidney stones. He later served as a guest lecturer and lab instructor at University of Tehran for 3 years before joining Queen's University in 2019. BSc: Electrical Engineering (Electronics), University of Tehran (2007) MSc: Biomedical Engineering, University of Tehran (2010) PhD: Biomedical Engineering, University of Tehran (2015) Dr. Jamzad's research centers on cancer cell detection, particularly in developing ultrasonic and optical spectroscopic devices for surgical margin detection. His work integrates advanced machine learning techniques with clinical applications, focusing on breast and prostate cancer surgery. He has pioneered the use of mass spectrometry imaging for cancer margin assessment and developed open-source platforms like ViPRE and MassVision for AI-driven medical data analysis. His recent publications demonstrate expertise in self-supervised learning, domain adaptation, and uncertainty quantification within medical imaging contexts. While no specific awards are mentioned, his contributions to surgical oncology tools and multi-center prostate cancer studies indicate significant clinical impact. He has also explored temporal enhanced ultrasound for composite defect detection and electrosurgical cautery state recognition through deep learning.
Riccardo Cantoro is an Associate Professor in the Department of Control and Computer Science (DAUIN) at Politecnico di Torino, where he is a member of the College of Computer, Film and Mechatronics Engineering and the College of Mechanical, Aerospace and Automotive Engineering. He is affiliated with the CAD - Electronic CAD & Reliability Group and the CARS@PoliTO Interdepartmental Center for Automotive Research and Sustainable Mobility. His work bridges academic research and industrial applications through multiple commercially funded projects. Scientific Disciplinary Sector: IINF-05/A - Information Processing Systems ERC Sectors: PE7_4, PE6_2, PE6_11, PE6_12 His research focuses on functional safety, functional testing, and microprocessor testing, with a strong emphasis on embedded systems and reliability. He applies machine learning and formal methods to enhance test efficiency and system robustness, particularly in automotive and safety-critical domains. His work integrates computer-aided design, fault modeling, and resilience assessment in both hardware and AI systems. The recent publications highlight a trend toward data-efficient and intelligent testing methodologies, combining machine learning (e.g., TabPFN, active learning) with traditional electronic design automation. Topics include microcontroller performance screening, CNN resiliency, FeFET device testing, and system-level test optimization, reflecting a cohesive research agenda in trustworthy computing and hardware reliability. Scientific Awards: No awards explicitly mentioned in the provided texts. Advising and Grants: Dr. Cantoro supervises numerous PhD students in Computer and Systems Engineering, focusing on functional safety, test methodologies, and AI for CAD. He leads multiple industry-funded research projects, including collaborations with Infineon Technologies and Dana-TM4 Italia, on topics such as ATPG tools, speed monitor modeling, and power module reliability. His role as Scientific Manager/Head underscores his leadership in applied research and technology transfer. Labs and Teams: He is a core member of the CAD - Electronic CAD & Reliability Group (DAUIN) and contributes to the CARS@PoliTO center, fostering interdisciplinary research in automotive systems and sustainable mobility.
Cristina Emma Margherita Rottondi is an Associate Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino . She is a member of the Photonext Interdepartmental Center and contributes to research in telecommunications, computer music, and network optimization. Her work spans privacy-preserving protocols, smart grid communication, and low-latency audio streaming. Research Interests : Networked Music Performance, Optical Networks, Smart Grid Privacy, Machine Learning. Education : Not explicitly listed. Research Areas include: Smart Grid Privacy : Developing secure protocols for data aggregation and distributed energy optimization. Optical Network Design : Investigating machine learning-driven solutions and spatial division multiplexing. Networked Music Performance : Addressing latency and inclusivity in remote musical collaboration. Publication Trends highlight interdisciplinary work at the intersection of telecommunications , machine learning , and music technology . Recent articles focus on privacy-preserving smart grids , 5G-enabled musical IoT , and UDP packet trace datasets . Scientific Awards : 2020 Charles Kao Award Best Paper Awards at IEEE Online Greencomm (2014), DRCN (2017), and others N2Women Rising Star (2020) Advising includes PhD candidates working on networked music performance , accessible musical education , and medical wearable devices . She has contributed to national patents for inclusive audio hardware.
Mart Roosimaa is a physician scientist with a focus on endocrinology , bioenergetics , and metabolic disorders . He has held clinical and academic positions at the University of Tartu, Faculty of Medicine , including roles as Assistant in Pathophysiology and PhD candidate. Currently, he serves as a Medical Science Liaison at Nanordica Medical OÜ (since 2023), and has held leadership roles such as Chief Executive Officer at Keila Haigla (2022–2023) and Chief of Endocrinology at North Estonia Medical Centre (2019–2022). His academic training includes interrupted PhD studies in medicine (2011–2017) at the University of Tartu, centered on "Interactomic approach for evaluating energy metabolism in different pathophysiological states" . His research spans translational medicine , mitochondrial function , and age-related muscle weakness , with publications on diabetes management, cardiac metabolism, and skeletal muscle pathophysiology. Mart has contributed to national clinical guidelines for type 2 diabetes and chronic kidney disease , and serves in advisory roles for the Estonian Endocrine Society and Ministry of Social Affairs. His scholarly work includes 33 publications, with recent articles on GLP-1 receptor agonists , hexokinase overexpression , and mitochondrial bioenergetics .
Dr. Nutifafa Yao Doumon is an Assistant Professor in the Department of Materials Science and Engineering at Pennsylvania State University’s College of Earth and Mineral Sciences. His research focuses on next-generation optoelectronic and photovoltaic devices, emphasizing stability, reliability, and degradation mechanisms of organic and hybrid semiconductors, with applications in flexible electronics and sustainable energy systems. Ph.D. in Nanoscience (Applied Physics), University of Groningen M.A. in Leadership, Honors College, University of Groningen M.Sc. in Nanoscience and Theoretical Physics B.Sc. in Physics from University of Ghana His work spans organic solar cells, perovskite photovoltaics, and quantum dot semiconductors, with expertise in device fabrication, stability testing, and characterization under ambient conditions. He previously held positions at NREL (USA), INRS (Canada), and University of Groningen (Netherlands). Key research themes include organic/polymer solar technologies , halide perovskite stability , and multidisciplinary energy transition solutions . His lab collaborates with Penn State’s Steidle Building, Millennium Science Complex, and external institutions. 2025 Royal Society of Chemistry Emerging Investigator National Academies U.S.-Africa Frontiers Fellow Zernike Institute Topmaster Nanoscience Scholarship Dr. Doumon advocates for women in STEM , climate action, and sustainable energy deployment. His lab prioritizes diversity, equity, and inclusion in research environments.
Prof. Dr. Tolga Ovatman is a faculty member at the Department of Computer Engineering, Istanbul Technical University , where he has been serving as Head of Department since 2024. His academic career spans roles from Research Assistant (2004-2012) to Associate Professor (2019-2023) and full Professor (2023-present). He previously held administrative roles such as Vice Dean (2018-2022) and Deputy Head of Department (2016-2018). PhD in Computer Engineering (2005-2011) MS in Computer Engineering (2003-2005) BSc from Hacettepe University (1999-2003) His research focuses on model checking , replicated state machines , cloud computing , and object-oriented software . Recent work addresses computation offloading in 6G networks , collaborative text editing data structures , and energy-efficient environmental monitoring systems . Key projects led include Design of a Multiplexed State Machine Storage System for Edge Computing (2022-2024) and Microservice Compatible Symphony Infrastructure Research (2020). He has supervised numerous theses on topics ranging from collaborative text editing to AI applications in watershed management . Publications span IEEE Transactions , Springer , and conferences like CSCE and CLOSER .
Richard Arès is a professor at the University of Montreal specializing in semiconductor epitaxy, photovoltaics, and photonics. His research spans electrical engineering, mechanical engineering, and condensed matter physics. Doctorate in Physics from Simon Fraser University (1998) Master's in Physics from Université de Montréal (1993) Bachelor's in Physics from Université de Montréal (1990) His work focuses on: Advanced semiconductor growth techniques High-efficiency multi-junction solar cells Photonics device fabrication Nanomaterials engineering Surface and interface analysis Process control in ultra-high vacuum environments Recent publications highlight expertise in: Through-cell via contacts for photovoltaics Quantum dot enhanced solar cells Mesoporous semiconductor structures Nonlinear optical waveguides Temperature-sensitive epitaxy processes
Mario Marchesoni is a Professor at the Department of Naval, Electrical, Electronics and Telecommunications Engineering (DITEN) , affiliated with the University of Genoa . His academic responsibilities include coordinating the PhD program and teaching advanced courses in electrical engineering with a focus on energy transition and industrial technologies. Ranks: Full Professor Departments: DITEN Research Interests center on power electronics, control systems, and energy conversion , addressing challenges in hybrid vehicles, induction motor drives, and energy storage systems. His work emphasizes improving efficiency and reliability in electrical systems through innovative control strategies and converter topologies. Recent Publications (2024) highlight advancements in DC-DC converters for hybrid vehicles , thermal management of high-power diodes , and sensorless control of induction motors . Key themes include dynamic performance optimization, sub-harmonic reduction, and hybrid energy storage solutions. Contact: Email mario.marchesoni@unige.it or phone +39 010 33 52183. Office hours by appointment at DITEN, via all'Opera Pia 11a, first floor, Genova.
Ivan Sanchez Esqueda is an Associate Professor in the School of Electrical, Computer and Energy Engineering at Arizona State University. His research focuses on nanoelectronics, 2D materials, and neuromorphic computing, with significant contributions to radiation effects in semiconductor devices. Education: Ph.D. Electrical Engineering, Arizona State University (2011) M.Sc. Electrical Engineering, Arizona State University (2006) B.Sc. Electrical Engineering, University of Arizona (2004) Dr. Esqueda's research interests span nanoelectronics, two-dimensional (2-D) and one-dimensional (1-D) materials, device nanofabrication, characterization, analysis, and modeling. He explores new device functionalities for novel computing, sensing, and memory applications, particularly hardware implementation of neuromorphic computing and machine learning. His work includes fundamental understanding of nanoscale electronics, confinement and scattering effects in low-dimensional electronic systems, computational nanoelectronics, and modeling of semiconductor devices. A significant portion of his research focuses on defect-related mechanisms and their impact on performance, variability, and reliability of devices and circuits, including radiation and aging effects in commercial CMOS and emerging nanotechnologies. His publication record shows a clear trend toward neuromorphic computing applications using 2D materials, particularly hexagonal boron nitride memristors, and continued investigation of radiation effects in advanced semiconductor technologies. Recent work demonstrates increasing focus on practical implementations of neural networks and machine learning hardware using novel materials. As an educator, Dr. Esqueda teaches courses including EEE 436 (Fundamentals of Solid-State Devices) and EEE 531 (Semiconductor Device Theory I), and mentors numerous graduate students through thesis and dissertation research. His research team at ASU focuses on the fabrication, characterization, and modeling of advanced electronic technologies, developing novel devices based on low-dimensional materials for computing, sensing, and memory applications. They particularly investigate device behavior in extreme environments including radiation and cryogenic conditions.
Gianluigi Ferrari is a Full Professor of Telecommunications at the Department of Engineering and Architecture, University of Parma, Italy. He has been at the University of Parma since 2002, following his Laurea and PhD degrees from the same institution in 1998 and 2002 respectively. Professor Ferrari serves as the coordinator of the Internet of Things (IoT) Lab since 2006, Vice-director of the Future Technology Lab (2020-), and President of the Degree Course in Computer, Electronics and Telecommunications Engineering (2021-). He has held visiting researcher positions at USC, CMU, KMITL, NATO in Brussels, and NCTU. Professor Ferrari's research focuses on complex networked communication systems with emphasis on signal processing and network communication. His work spans Internet of Things architectures, wireless sensor networks, vehicular communications, and edge computing systems. He has made significant contributions to IoT protocols, sensor network optimization, and vehicular communication systems, with applications in smart cities, healthcare monitoring, and intelligent transportation systems. His interdisciplinary approach bridges theoretical foundations with practical implementations in real-world scenarios. His recent publications demonstrate a strong trend toward privacy-preserving techniques in IoT systems, edge intelligence for real-time analytics, and optimization of communication protocols for emerging applications. The research spans healthcare monitoring with wearable devices, vehicular communications with federated learning approaches, and novel routing protocols for BLE mesh networks. His work consistently addresses the challenges of energy efficiency, security, and reliability in networked systems. best paper/technical awards at various international conferences Senior Member of the IEEE Editor-in-Chief of Future Internet (MDPI, 2023-) Editor of ICT Express (Elsevier, 2021-) Professor Ferrari participates in numerous research projects funded by public and private institutions with research grants exceeding €5 million. He has served on the editorial boards of multiple international journals and organized several workshops and special sessions at major conferences. His professional activities include serving as Technical Team Member in NATO Research Task Group HFM-260 (2015-2018) and member of the Scientific Council of ARTEMIS association (2019-) and CNIT (2020-). As director of the IoT Lab at the University of Parma, Professor Ferrari leads a research team focused on developing innovative solutions for Internet of Things applications. The lab investigates communication protocols, network architectures, and data processing techniques for various IoT domains including smart cities, healthcare, and intelligent transportation systems. The lab maintains strong collaborations with international research institutions and industry partners, facilitating technology transfer and practical implementation of research outcomes.
Andrew A. Houck is the Anthony H.P. Lee '79 P11 P14 Professor of Electrical and Computer Engineering at Princeton University's School of Engineering and Applied Science. He serves as Dean of the School and inaugural Co-director of the Princeton Quantum Initiative. Ph.D., Harvard University (2005) B.S.E., Electrical Engineering, Princeton University (2000) His research focuses on superconducting quantum computing and quantum simulation via circuit quantum electrodynamics (cQED). Key areas include photonic bandgap engineering , nonlinear quantum optics , and machine learning optimization for quantum systems. His lab investigates robust qubit architectures, decoherence mitigation, and many-body quantum physics in photonic crystals. Recent publications demonstrate expertise in superconducting circuit design, quantum control instrumentation (QICK platform), and photonic material engineering. Collaborative work spans quantum computing hardware, error correction protocols, and nonlinear microwave photonics. Honors : Presidential Early Career Award (2010), NSF Early Career Award (2010), Packard Fellow (2009), TR35 (2009), Sloan Research Fellow (2009), Blavatnik Award Finalist (2008) Houck advises numerous graduate students, including Matthew Bland , Jeronimo Martinez , and Paal Prestegaard . His lab partners with the Co-design Center for Quantum Advantage and Princeton's Interdisciplinary Quantum Science Network .
