Ahmed Ismail Mohamed Ali is an Assistant Professor at the Department of Electrical Engineering , Faculty of Engineering , South Valley University , Egypt, and a Post-Doctoral Research Fellow at Aalto University , Finland. He holds a B.Sc. and M.Sc. in Electrical Engineering from South Valley University (2013, 2017) and a Ph.D. in Electrical Engineering from Nagoya Institute of Technology , Japan (2022). Education: B.Sc. in Electrical Engineering, South Valley University (2013) M.Sc. in Electrical Engineering, South Valley University (2017) Ph.D. in Electrical Engineering, Nagoya Institute of Technology (2022) Research Interests include power electronics, specifically PWM techniques for bidirectional AC/DC converters , single-phase and three-phase multilevel converters , modular multilevel converters (MMCs) , isolated grid-tied differentially based DC-AC inverters , EV battery chargers , and renewable energy applications . His work focuses on improving efficiency, power quality, and complexity in renewable energy systems and electric vehicle charging infrastructure. Publications (15 most recent) span 2018–2025, with a strong emphasis on photovoltaic (PV) inverters , multilevel converter topologies , model predictive control (MPC) , and leakage current minimization . Recent work (2024–2025) explores advanced modulation strategies and grid-tied renewable energy integration. Laboratory Affiliation: He is part of the Computational Electromechanics research group at Aalto University, contributing to postdoctoral research in power electronics and renewable energy systems.
James Friend is a Professor at the University of California, San Diego, holding dual appointments in the Department of Mechanical and Aerospace Engineering, Jacobs School of Engineering and the Department of Surgery, School of Medicine. He serves as the Stanford S. and Beverly P. Penner Endowed Chair in Engineering and leads the Medically Advanced Devices Laboratory in the Center for Medical Devices at UCSD. Prior to joining UCSD in November 2014, he spent 14 years as a faculty member in Japan and Australia, where he founded micro/nanofabrication facilities including the $45 million Melbourne Centre for Nanofabrication and served as inaugural director of RMIT University's $35 million MicroNano Research Facility. Jacobs School of Engineering, Department of Mechanical and Aerospace Engineering School of Medicine, Department of Surgery Stanford S. and Beverly P. Penner Endowed Chair in Engineering Director, Medically Advanced Devices Laboratory Professor Friend's research focuses on exploring and exploiting acoustic phenomena at small scales, primarily for biomedical applications. His work spans acoustofluidics, medical device development, micro/nanofabrication, and the application of surface acoustic waves for diagnostics, drug delivery, and therapeutic interventions. He has pioneered techniques for ultrasound neuromodulation, point-of-care diagnostics, and microscale fluid manipulation with applications in neurology, oncology, and pediatrics. His research bridges fundamental acoustic science with practical clinical solutions, emphasizing translational impact. His recent publications reveal a strong emphasis on advancing acoustofluidic technologies for biomedical applications. Key trends include developing point-of-care diagnostic platforms for neurodegenerative diseases, creating novel ultrasound-based neural modulation techniques, and engineering microscale propulsion systems. His work also explores fundamental aspects of acoustic wave behavior at micro and nanoscales, with applications ranging from cell manipulation to battery technology enhancement. The interdisciplinary nature of his research spans engineering, physics, neuroscience, and clinical medicine. AIAA Jefferson Goblet Student Paper Award and ASME Best Paper Award Multiple excellence awards from Monash Faculty of Engineering (2006, 2008, 2011) Future Leader award from Davos Future Summit (2008) Top 10 emerging scientific leader of Australia (2009) Top 50 papers of Applied Physics Letters past 50 years (2012) IEEE Carl Hellmuth Hertz Ultrasonics Award (2015) IEEE Fellow (2018) Highly cited author by Royal Society of Chemistry (2020) UCSD Distinguished Teaching Award (2021) Professor Friend currently supervises 7 PhD students and 1 post-doc in his Medically Advanced Devices Laboratory. Over his career, he has successfully completed 37 postgraduate students and supervised 23 postdoctoral researchers. His research has been supported by over $29 million in competitive grant funding, reflecting the significance and impact of his work. His laboratory operates at the intersection of engineering and medicine, with strong collaborations across disciplines to translate fundamental discoveries into practical medical solutions. The Medically Advanced Devices Laboratory, which Professor Friend leads, focuses on developing innovative medical devices that leverage acoustic phenomena. The lab has developed handheld acoustofluidic circuits, novel centrifugation and separation techniques using omnidirectional spiral surface acoustic waves, and acoustogeometric streaming technologies. Recent projects include superfast battery recharging systems using surface acoustic waves and point-of-care diagnostic platforms for Alzheimer's disease detection. The laboratory maintains strong industry and clinical partnerships to accelerate the translation of research into practical medical applications.
University of Applied Sciences Upper AustriaAustria
Balwin Bokor is a Researcher at Steyr University of Applied Sciences, affiliated with the Department of Production and Operations Management. His work focuses on industrial systems, simulation modeling, and sustainable manufacturing practices. Bachelor of Arts (BA), Master of Science (MSc) Research Interests: Bokor's research spans production engineering and operations management, emphasizing energy efficiency, logistics optimization, and simulation-based analysis. His studies address material requirements planning (MRP), constant work-in-process (CONWIP) systems, and flexible capacity adjustments in multi-stage production environments. Article Trends: Recent publications highlight simulation-driven approaches to production planning, energy cost balancing, and control system optimizations. These works align with Industry 4.0 trends in smart production and sustainable logistics. Scientific Awards: Recipient of the Würdigungspreis (2022), an Austrian award recognizing academic merit. Collaborations: Active in cross-institutional research networks, with collaborations in production system engineering, battery manufacturing, and energy reduction strategies. His work contributes to the 'fingerprint' research areas identified by Steyr University of Applied Sciences.
Nagham Saeed serves as Associate Professor in Electrical and Electronic Engineering at the School of Computing and Engineering, University of West London, a position she has held since April 2023. Previously, she was Senior Lecturer in Electrical Engineering at the same institution from November 2017 to April 2023, following roles as Electronic Lecturer at Uxbridge College (2012-2017) and Electronic/Control Lecturer at Brunel University (2007-2012). Her academic credentials include: Ph.D. in Optimization in Wireless Networks and Communications (Brunel University, 2007-2011) M.Sc. in Mechatronics (University of Technology, Baghdad, 1997-1999) B.Eng. in Computer and Control (University of Technology, Baghdad, 1988-1992) DTLLS Diploma in Teaching (University of Westminster, 2012-2014) BAPP in Learning and Teaching (Brunel University, 2009-2010) Assessing Competence Certification (Uxbridge College, 2014) Dr. Saeed's research spans wireless communications, IoT, electric vehicles, and AI-driven energy optimization. Her work focuses on Bluetooth Low Energy applications for healthcare monitoring, battery management systems for EVs, sustainable ICT practices, and GIS-based land use analysis. She pioneers solutions for energy-efficient radio access networks and develops AI models for vehicle classification and low-resource language processing. Analysis of her 2022-2025 publications reveals three dominant trends: (1) AI integration for sustainable energy systems in telecommunications and transportation, (2) blockchain-secured vehicular networks for 6G infrastructure, and (3) cross-disciplinary applications of IoT in healthcare and environmental monitoring. Her research consistently bridges electrical engineering with computer science to solve real-world sustainability challenges. Professional recognition includes: MDPI Reviewer Acknowledgements (2020) for Algorithms, Applied Sciences, and Information journals While her 2022 educational research on feedforward teaching approaches demonstrates pedagogical engagement, no student supervision or grant management details are documented. Current institutional affiliations show no dedicated laboratory facilities or research teams specified in available records.
Stephan Rinderknecht is a Professor for Mechatronic Systems in Mechanical Engineering at Technische Universität Darmstadt since 2009. His research focuses on Vehicle Systems Energy Systems Vibration Systems Robotics Finite Element Method (FEM) Multi-body Simulation (MBS) Hybrid and Electric Drives Rotor Dynamics Active Magnetic Bearings .
Professor Johna Leddy is a faculty member in the Department of Chemistry at the University of Iowa. Her research focuses on electrochemistry with an emphasis on magnetoelectrocatalysis, exploring how magnetic fields influence chemical reaction pathways in energy systems like fuel cells and batteries. Key areas include electrochemical energy systems, lanthanide chemistry, and thin-layer sonoelectrochemistry. She has pioneered studies on magnetic field effects on radical reactions and developed composite materials for enhanced electrochemical performance. Education: Postdoctoral Associate, Los Alamos National Laboratory, Fuel Cell Program PhD, University of Texas BA, Rice University Her work integrates fundamental theory with applied research, resulting in numerous patents (e.g., magnetic electrode designs, breath-based sensors) and innovations in electrochemical technologies. Current projects address challenges in hydrogen fuel efficiency and carbon monoxide tolerance in PEM fuel cells. She leads the Leddy Lab, advancing electrochemical methods and catalysis through interdisciplinary approaches. Notable Contributions: Development of magnetically modified electrodes for enhanced catalytic activity Advancements in thin-layer sonoelectrochemical techniques Commercialization of intellectual property through patents Her research also extends to educational innovations, including the use of 3D visualization tools and spreadsheet-based analytical methods for teaching electrochemistry.
Dr. Gianfranco Claudio is a Senior Lecturer in Photovoltaics at the Electronic Electrical and System Engineering School of Loughborough University. He holds a PhD in Electronic Engineering from the University of Surrey (2004) and a First Class Degree in Physics from the University of Bari (Italy). He is a Chartered Physicist (since 2009) and has led significant research in renewable energy systems, photovoltaic technologies, and energy storage solutions. His research focuses on advancing solar cell efficiency, thermal energy storage systems, and low-carbon district heating networks. Key projects include developing high-efficiency silicon solar cells via antireflective coatings and laser annealing techniques. He has secured grants such as the TSB grant for epitaxial silicon solar cells (2010) and Welsh Assembly grants for silicon solar cell characterization. Currently, he co-leads a TSB project on thin-film CdTe cell interconnections. Dr. Claudio’s work spans experimental and theoretical domains, including coherence correlation interferometry for photovoltaic metrology and fuzzy C-means modeling for power systems. His contributions are evident in 4th generation district heating systems and low-cost battery testing frameworks for developing countries. Grants/Projects: TSB grants (2010, ongoing), Welsh Assembly grants, M-solv collaboration on CdTe interconnects Affiliations: Centre for Renewable Energy Systems Technology (CREST), Loughborough University PV Laboratory Labs/Teams: Involved in the development of the Holywell Park PV laboratory and thermal energy storage initiatives
Dr. Pedro Ferreira is a Senior Lecturer in Manufacturing Systems at Loughborough University. He holds a MEng (equiv) and PhD from the University of Nottingham and is a Fellow of the Higher Education Academy (FHEA). His career spans academic and industry roles, including a Research Associate at the University of Nottingham, Senior Research Fellow, Technical Manager at Maersk Line IT, and Lecturer at Loughborough since 2015. Education: MEng (equiv) in Electrical, Electronic, and Computer Science Engineering, New University of Lisbon, Portugal (2006) PhD in Manufacturing Engineering and Operations Management, University of Nottingham, UK (2011) Research Interests: Dr. Ferreira's work focuses on manufacturing systems , Industry 4.0 , robotics , and sustainability . He explores human-robot collaboration , tactile sensing , and data-driven approaches for optimizing production systems. His recent studies address challenges like battery lifecycle management, cost-effective sensor solutions, and aligning education with UN sustainability goals. Article Trends: His publications emphasize robotic automation , sensor innovation , and adaptive manufacturing systems . Key themes include tactile sensor applications for hardness classification, Industry 4.0 complexity indices, and symbiotic human-machine learning frameworks. Grants & Advising: While no specific grants or students are listed, his research portfolio indicates involvement in projects related to production system optimization, wearable sensors, and educational frameworks for sustainability. Labs/Teams: Engages with cross-disciplinary teams at Loughborough, focusing on advanced manufacturing and Industry 4.0 integration.
Scott Sanders is a Professor of Mechanical Engineering at the University of Wisconsin-Madison, with additional affiliations in Electrical & Computer Engineering. His research focuses on developing optical instrumentation and sensors for critical applications in energy, manufacturing, and health. Notable projects include hydrogen leak detection via quadcopter-based imaging, compact optical sensors for liquid fuels, diamond-windowed sensors for molten materials, and fiber-optic battery temperature sensing. He has received prestigious awards such as the NSF CAREER Award and Combustion Institute Silver Medal. Sanders teaches courses including engineering design projects, thermodynamics, and advanced research supervision. His work emphasizes innovations in laser spectroscopy, tomographic imaging, and real-time combustion diagnostics. Education: PhD (2001), MS (1998) Stanford University; BS (1997) Valparaiso University Research Interests: Optical sensors for energy systems, additive manufacturing, and environmental monitoring His labs specialize in high-speed hyperspectral sensing, with applications ranging from internal combustion engines to nuclear reactor monitoring. Sanders has pioneered techniques like backscatter absorption spectroscopy and polymer film-based optical access systems. His recent work addresses SARS-CoV-2 transmission mitigation in classrooms through ventilation and mask efficacy studies. Grants and collaborations include DOE projects on advanced engine combustion strategies. Awards: ASHARE Best Paper (2020), ARO PECASE Nominee (2006), Combustion Institute Silver Medal (2000)
John Barton is a Researcher at the Centre for Renewable Energy Systems Technology (CREST). His work focuses on wind power integration, energy storage systems, and low-carbon hydrogen production. He developed the Future Energy Scenario Analysis (FESA) tool to model energy systems with high renewable penetration. Current research includes wind turbine condition monitoring and socio-technical transition pathways for energy systems. His research spans smart grids, distributed energy generation, and the socio-technical challenges of transitioning to low-carbon systems. He has collaborated with companies like Bryte Energy and Air Fuel Synthesis on hydrogen and carbon-neutral fuel technologies. Notable contributions include studies on energy storage optimization, solar integration barriers, and humanitarian portable power solutions. Key projects include the Supergen Wind project for turbine monitoring and the Realising Transition Pathways initiative exploring energy security and emissions reductions. His work links technical modeling with societal engagement, addressing both engineering and behavioral aspects of energy transitions.
Matti Huotari is a Senior Lecturer at Aalto University's Department of Electrical Engineering and Automation, where he researches AI applications for building energy optimization and occupant well-being. His work focuses on integrating IoT technologies with machine learning to enhance building efficiency while maintaining environmental comfort. Dr. Huotari completed his doctoral studies at Aalto University with a dissertation on machine learning applications in building energy systems. Research focuses on: Energy optimization in smart buildings using AI IoT-enabled indoor environment monitoring and control Machine learning for predictive maintenance of building systems Human-centered building automation Sustainable energy utilization Recent publications demonstrate strong emphasis on practical applications of machine learning in building systems, particularly air handling units and battery systems. The work integrates control theory with data-driven approaches for energy efficiency. Dr. Huotari maintains international research collaborations and has been a visiting scholar at UC Berkeley and Tokyo City University. His research contributes to sustainable building technologies and energy conservation.
Dr. Dariusz Borkowski is an Associate Professor in the Department of Electrical Engineering at the Faculty of Electrical and Computer Engineering, Jagiellonian University. His work focuses on energy systems, renewable energy integration, and automation technologies. He holds a BEng, PhD, and DSc in relevant fields. Research interests include hydropower optimization, battery storage, grid-connected systems, and advanced control algorithms. He has published 59 peer-reviewed articles, with a significant focus on small hydropower plants, renewable energy solutions, and smart grid technologies. His work emphasizes maximizing energy efficiency in variable-speed systems and improving energy conversion processes. Dr. Borkowski has supervised 2 promoted theses and contributed to 2 major scientific achievements. His research often intersects with practical applications, such as modular energy systems for green classrooms and energy recovery from municipal water networks. He leads projects on hybrid renewable systems, ADAS (Advanced Driver Assistance Systems), and sensor data processing for vehicle safety. He is affiliated with ORCID and maintains an active presence in Scopus and Web of Science. His Hirsch index (Scopus) is 12, reflecting impactful contributions to electrical engineering and energy systems.
Dr. Ed Long is a Senior Lecturer in Fluids Engineering, focusing on interdisciplinary research at the intersection of fluid dynamics, combustion systems, and environmental applications. His work spans experimental and analytical studies in laser cutting gas dynamics, aerosol technology, and sustainable energy solutions. He has contributed to advancements in engine emissions reduction, battery thermal management, and soil erosion modeling. His research often involves cutting-edge diagnostic techniques such as particle imaging velocimetry and electrochemical analysis. Key research areas include combustion optimization in compression ignition engines, mitigation of hazardous fumes in industrial processes, and improving drug delivery systems through aerosol dynamics. His studies also address environmental challenges like pollution control and sustainable manufacturing. Dr. Long's experimental work frequently employs advanced imaging and sensor technologies to analyze fluid flow, particle behavior, and thermal interactions in complex systems. Though no specific awards are noted, his prolific publication record (over 30 articles from 2006–2024) demonstrates sustained contributions to mechanical, biomedical, and environmental engineering. His research bridges theoretical models with practical applications, such as low-cost turbidity sensors and novel designs for exhaust cleaning modules. Collaborations likely span academic and industrial partners, though specific affiliations are not detailed here.
Darrell L. Robinette is an Associate Professor in the Department of Mechanical and Aerospace Engineering at Michigan Technological University (MTU), where he also serves as Area Director for Design/Dynamic Systems. He joined MTU in 2016 after nine years at General Motors, where he focused on powertrain NVH, controls, and electrification. His research emphasizes mobility systems electrification, connected/automated vehicle optimization, and propulsion system integration. Education: Robinette holds a PhD in Mechanical Engineering-Engineering Mechanics (2016) and a BS in Mechanical Engineering (year not specified), both from MTU. Research Interests: His work spans electrification of mobility systems, connected/automated vehicle control systems, automatic transmission dynamics, torque converter optimization, and drivetrain NVH reduction. He leads projects funded by GM, Ford, the Department of Energy, and ARPA-E, addressing topics like heavy-duty off-road electrification and energy-efficient vehicle control strategies. Patents: He holds 15 U.S. patents in powertrain and driveline engineering, including innovations in clutch systems, hybrid transmissions, and NVH mitigation technologies. Advising & Grants: Co-advisor for the SAE-GM Autodrive Challenge II. His funded research includes ARPA-E’s NEXTCAR program for connected vehicle optimization, DOE projects on off-road electrification, and industry collaborations on transmission testing and simulation. Labs/Teams: His work is conducted within MTU’s R. L. Smith Department, focusing on experimental and computational analysis of powertrain systems. He collaborates closely with automotive industry partners on applied research initiatives.
Arman Oshnoei is an Assistant Professor at Aalborg University, affiliated with the Faculty of Engineering and Science's Department of Power Electronics System Integration and Materials. His research focuses on renewable energy integration, battery management systems, and AI-driven solutions for smart grids. He leads and participates in high-impact projects like CROSBAT (2023-2026) and BMS-DC (2024), addressing challenges in battery safety, energy efficiency, and data center optimization. Education: Advanced degree in Power Engineering (details not specified). His research interests span power electronics, cybersecurity in energy systems, and predictive control models. Recent work includes optimizing green hydrogen production using AI and enhancing battery lifespan through advanced state-of-charge estimation. He has authored over 78 publications, including a 2025 best paper award for battery balancing techniques. Key Projects: - CROSBAT: AI-based battery lifetime optimization (2023-2026) - BMS-DC: Next-gen battery management for data centers (2024) - REPEPS: Reliable power electronic systems (2021-2023) Dr. Oshnoei also serves as a reviewer for IEEE Transactions on Sustainable Energy and holds grants totaling over €2M in research funding.
