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Yubo SongView profile

Research Fellow

• Microgrid Engineering
• Power Electronics
• Power Electronic Converters
• +3 more

Yubo Song is a Postdoctoral Researcher at Aalborg University's Faculty of Engineering and Science, specializing in power electronics, microgrid systems, and reliability engineering. His work focuses on stability validation, control strategies, and the application of neuromorphic computing to power grids. His educational background includes: Ph.D. in Energy Technology from Aalborg University (awarded 2023) M.Sc. in Electrical Engineering from Shanghai Jiao Tong University (awarded 2019) B.Eng. in Electrical Engineering and Automation from Shanghai Jiao Tong University (awarded 2016) Dr. Song's research integrates microgrid engineering, power electronics reliability, and neuromorphic computing to address critical challenges in grid stability. His work pioneers Spike Talk technology for energy-efficient grid communication and develops hybrid modeling approaches for real-time power system simulation. Recent publications demonstrate expertise in damping control of grid-forming inverters, sensitivity analysis for reliability evaluation, and Bayesian risk assessment frameworks. His publication trends reveal a strategic shift toward neuromorphic solutions for power grids, with 2024-2025 works focusing on spike-based communication protocols and event-driven semantic systems. Earlier research centered on stability validation and reliability modeling for microgrids, establishing foundational frameworks still cited in current literature. Dr. Song has secured significant research funding including: Power Sentinel (Villum Foundation, 2024-2025): Developing cyber-physical safeguards for future power grids Reliability and Lifetime Analysis (2022-2025): Creating predictive models for power electronic components Stability and Reliability Validation (PhD project, 2020-2023): Establishing comprehensive microgrid assessment methodologies As Principal Investigator on multiple projects, he mentors early-career researchers while collaborating with industry partners on grid security solutions. His work with the Applied Power Electronic Systems group at AAU Energy focuses on translating theoretical advances into practical grid applications, particularly in converter reliability and neuromorphic grid communication.

Oleh KiselychnykView profile

Associate Professor

• Power Electronics
• Renewable Energy Systems
• Electric Vehicle Technology
• +3 more

Dr. Oleh Kiselychnyk is an Associate Professor in the School of Engineering at the University of Warwick, where he leads the Power and Control Systems Research Laboratory. He previously held roles as a Science City Research Fellow (2012–2015) and Assistant Professor (2015–2019). His expertise spans energy-efficient control systems, power electronics, and renewable energy integration. He coordinates the MSc Electrical Power Engineering program and teaches advanced modules on power electronic converters and drive control. Research interests focus on optimal control of electric vehicle drives, self-excited induction generators, and grid-integrated photovoltaic systems. Notable projects include EPSRC-funded initiatives on multilevel inverters, clean energy storage, and modular transportation architectures. He has supervised over 30 student projects on motor drives, power converters, and renewable energy applications. Key contributions include advancements in sensorless control algorithms for pumps/fans, neural network-based parameter estimation, and nonlinear control strategies for energy storage systems. His work bridges theoretical modeling with practical implementation in industrial and automotive sectors. Dr. Kiselychnyk collaborates with industry partners like Hyundai Motor Europe and AVL Powertrain, translating research into real-world applications. His lab facilities support experimental validation of novel control techniques and power electronic topologies.

• Mechanical Engineering
• Additive Manufacturing
• Smart Materials
• +4 more

Pascal LAFON is a Full Professor at the University of Technology of Troyes (UTT), affiliated with the Laboratory of Mechanical & Material Engineering (LASMIS) and the Department of Physics, Mechanics, Materials and Nanotechnology . He serves as the Director of Corporate Relations at UTT since 2023 and previously led LASMIS lab from 2012-2016. His academic duties include coordinating the 'Mechanics, Material and Advanced Manufacturing' master’s program (2018-2023) and the UTT doctoral program's 'Material, Mechanics, Optics and Nanotechnology' training (2012-2023). Director of Corporate Relations, UTT (2023-present) Head, LASMIS Lab (2012-2016) Master’s Program Coordinator (2018-2023) Doctoral Training Supervisor (2012-2023) His research focuses on Mechanical Optimization (mixed/random variables, nonlinear objectives), Additive Manufacturing (design, material behavior), and Smart Material Applications . Current projects integrate metamodeling (RBF, Kriging) with multi-objective optimization for manufacturing processes and structural systems. Publications and projects demonstrate expertise in: metal forming , composite materials , springback analysis , and breakwater design . He has supervised 13 PhD students since 1996, including international collaborations with Lebanese University and Northwestern Polytechnical University .

Pierre LefrancView profile

Lecturer

• Power Electronics
• Power Converters
• Optimization
• +3 more

Pierre Lefranc serves as a Lecturer at the School of Energy, Water and Environment (ENSE3) within Grenoble Institute of Technology, affiliated with the G2Elab research laboratory where he is a key member of the Power Team (Équipe de Puissance). His academic responsibilities span teaching and research in power electronics, converter design, and power switch control across undergraduate and graduate programs. His educational foundation includes: Supélec Engineer (2002) DEA in Electrical Engineering from Paris (2002) Doctorate in Electrical Engineering from INSA Lyon (2005) Dr. Lefranc's research centers on power converter modeling and optimization , developing methodologies for pre-sizing, sizing, and algorithmic optimization while addressing power-control interactions. He pioneers close control of advanced power switches (IGBT, MOSFET, HEMT-GaN), focusing on high-galvanic-isolation signal transmission, planar/coreless transformer design with large air gaps, and control circuit optimization for next-generation wide-bandgap devices. His work bridges theoretical optimization with practical implementation challenges in high-frequency power systems. Analysis of his 11 publications (2009-2013) reveals consistent innovation in virtual prototyping and constraint-based optimization for DC-DC/DC-AC converters. His research spans transportation electrification, medium-voltage multi-level converters (10-50kV), and plasma reactor applications, with strong emphasis on multi-physics constraints (thermal, spatial, electromagnetic) and real-world implementation of wide-bandgap semiconductor technologies. Dr. Lefranc maintains active international collaborations including: NTNU (Norway) on Carnot 3D-MMC project for medium-voltage modular converters CentraleSupélec on predictive control of hybrid power systems LAAS Laboratory on micro-inductor optimization While his teaching portfolio spans instrumentation electronics, power converters, and switch control across ENSE3's 1A-3A programs, the source text indicates no formal student advisement records or major scientific awards. His research continues through G2Elab's Power Team on transformer design, plasma reactors, and micro-inductor optimization.

Yousef DarestaniView profile

Assistant Professor

• Infrastructure Systems Resilience
• Risk and Reliability Engineering
• Wind Engineering
• +4 more

Dr. Yousef Darestani is an Assistant Professor in the Department of Civil, Environmental, and Geospatial Engineering at Michigan Technological University (MTU). Previously, he served as a postdoctoral researcher at Rice University's Department of Civil and Environmental Engineering. He holds a PhD in Civil Engineering from The Ohio State University (2019), an MSc in Structural Engineering from Sharif University of Technology (2014), and a BSc in Civil Engineering from the University of Tehran (2011). Affiliations: Great Lakes Research Center (GLRC), MTU Teaching: Structural Analysis, Structural Reliability His research focuses on enhancing the resilience of infrastructure systems against natural hazards, particularly wind and storm-induced risks. Key areas include machine learning applications for risk assessment, wildfire mitigation in power grids, and lifecycle cost analysis of structural components. He develops probabilistic models to evaluate infrastructure vulnerability and devise cost-effective enhancement strategies. Recent publications highlight advancements in hurricane resilience frameworks, wildfire-affected power distribution networks, and multi-hazard assessment methodologies. His work bridges engineering principles with socio-technical systems, emphasizing community resilience and climate adaptation. Teaching and research activities are complemented by interdisciplinary collaborations, including data-driven approaches in biomedical engineering (e.g., prosthetic valve performance prediction). His lab integrates computational modeling, field data analysis, and experimental validation to address real-world challenges in critical infrastructure.

Vlad MarsicView profile

Assistant Professor

• RF Engineering
• Wireless Networks
• Electromagnetic Simulation
• +4 more

Dr. Vlad Marsic is an Assistant Professor specializing in RF engineering and semiconductor technologies. He is affiliated with the Centre for E-Mobility and Clean Growth, focusing on experimental and theoretical research in magnetic sensors, GaN transistors, and energy harvesting systems. His work contributes to UN Sustainable Development Goals related to clean energy and infrastructure innovation. Education: BEng in Communication Engineering, Faculty of Electronics and Telecommunications, 'Gh. Asachi' University, Romania (2002) MSc in Low Power RF Sensing, School of Applied Sciences, Cranfield University, UK (2012) EngD in RF Communication and Location Services, Warwick Manufacturing Group (WMG), University of Warwick, UK (2019) Research Interests: RF Technologies: Wireless networks, power line communication (PLC), and remote sensing Semiconductor Devices: GaN transistors, Hall-effect sensors, and switching behavior analysis Energy Systems: Li-ion battery diagnostics and energy harvesting Research Trends: His publications (2021–2025) emphasize advancements in GaN-based sensor integration, magnetic field analysis, and battery diagnostics. Recent work addresses challenges in sensor sensitivity, noise mitigation, and energy-efficient communication systems. Awards: Best Paper Award (multiple conferences in RF experimental and modelling domains) Grants and Labs: Involved in collaborative projects with industry partners, focusing on smart infrastructure and clean energy technologies. Active in interdisciplinary teams developing novel sensing and communication solutions. Key Collaborations: Engaged with institutions across the UK and international partners in electromagnetic simulation, semiconductor design, and sustainable energy systems.

• Autonomous Systems
• Vehicle Dynamics
• Control Engineering
• +7 more

Katzourakis Diomidis is an Assistant Professor at the School of Production Engineering and Management (PEM) at the Technical University of Crete. His work focuses on autonomous systems, vehicle dynamics, and control engineering with an emphasis on automotive safety and fault-tolerant architectures. He holds an academic appointment within the PEM department and contributes to systems engineering research for cyber-physical vehicles. Research interests prominently feature autonomous driving optimization, actuator redundancy strategies, haptic feedback systems, and safety-critical control protocols. His publications span topics like motion planning constraints, steering assistance interfaces, and emergency maneuver mitigation. Recent work explores AI supervision frameworks (SSuperLLM) for autonomous vehicles and yaw rate-based suspension control systems. Key technical contributions include sensor fusion strategies for degraded position estimation, variable motion control envelopes, and redundant actuator architectures. He has developed experimental platforms for stability control validation and collaborated on open-source scaled automobile testbeds.

• Electrical Engineering
• Environmental Science
• Embedded Systems
• +3 more

Prof. György Györök serves as a Professor and Dean at Óbuda University's Alba Regia Faculty. His work bridges electrical engineering, environmental science, and embedded systems. He leads research in analog circuit design, fault detection systems, and sustainable industrial processes. His recent studies include innovation ecosystem modeling (Triple Helix Model), FPAA applications in signal processing, and environmental impact assessments of industrial processes. Research interests focus on pragmatic electrical engineering solutions, machine learning-driven systems, and sustainable technology development. Notable areas include battery management systems for electric vehicles, real-time fault detection algorithms, and environmental impact analysis of manufacturing processes. His publications reflect interdisciplinary innovation, combining hardware-software co-design with environmental and educational technology applications. He has pioneered FPAA-based measurement tools and smart monitoring systems for industrial and academic use. No awards are explicitly mentioned, but his extensive publication record indicates significant contributions in technical fields. As dean, he oversees academic governance while maintaining active research in embedded systems and sustainable engineering. Collaborations likely involve industry partners given his focus on pragmatic engineering solutions. His work integrates cutting-edge technologies like neural networks with traditional analog circuit design for real-world applications.

Bo Friis NielsenView profile

Professor

• Queueing Theory
• Matrix Analytic Methods
• Stochastic Processes
• +3 more

Bo Friis Nielsen is a Professor and Head of Section in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU). His research focuses on queueing theory, particularly matrix-analytic methods, with applications in telecommunication systems and service optimization. He currently supervises PhD students working on projects with Danske Bank (call center efficiency) and DSB S-tog (passenger counting for transport planning). His teaching includes probability theory and stochastic simulation. Education/Background: Formal academic qualifications not explicitly listed in the text. Affiliations: Head of the Mathematical Modelling Section since 2003, affiliated with DTU Compute. Research interests span theoretical advancements in queueing models and practical applications in transportation, healthcare, and industrial systems. He has collaborated with companies like Danske Bank and DSB S-tog, addressing real-world operational challenges. Recent work includes predictive maintenance strategies for multi-component systems and railway defect analysis. Publications emphasize stochastic modeling, maintenance optimization, and transportation analytics. Projects involve developing tools for public transport efficiency and reliability engineering in wind turbines and power plants.

• Surge Protection Systems
• Lightning Effects on Power Infrastructure
• High Voltage Dielectric Materials
• +3 more

Dr. Peppas Georgios is an Assistant Professor in the Department of Electrical and Computer Engineering at the Technical University of Crete. His research focuses on surge protection systems, lightning effects on power infrastructure, and high-voltage dielectric materials. He leads projects on nanofluid-based insulation solutions and transient overvoltage mitigation in renewable energy systems. His work frequently addresses challenges in electric vehicle charging stations, medium-voltage grids, and transformer oil performance. Key research areas include: Design and modeling of surge protective devices (SPDs) Lightning protection for wind farms, substations, and pipelines Dielectric properties of natural ester oils and nanofluids High-voltage insulation systems for renewable energy applications Recent studies emphasize nanomaterials' role in improving breakdown voltage and thermal stability of insulating fluids. His work also investigates aging effects and radiation impacts on protective components. Collaboration with industry partners focuses on practical implementations of SPDs in residential and industrial settings. Dr. Peppas is based in the Science/ECE Building (Office 145Α-12) and can be reached at peppas@tuc.gr. His research has produced over 50 peer-reviewed articles since 2016, with 15 new publications in 2024–2025 alone.

Shane GilroyView profile

Lecturer

• Autonomous Vehicles
• Image Sensors
• Automotive Engineering
• +3 more

Shane Gilroy is a Lecturer in Electronic Engineering at the Department of Mechatronic Engineering, ATU Sligo. His research focuses on automotive systems, particularly autonomous vehicles, image sensor technology, and object detection challenges in occluded environments. He actively contributes to improving road safety through advancements in pedestrian detection, sensor validation, and cybersecurity in connected vehicles. His work aligns with UN Sustainable Development Goals, emphasizing innovation in urban mobility and sustainable infrastructure. Gilroy’s expertise spans computer vision, robotics, and automotive engineering, with notable contributions to occlusion classification methods and lifecycle validation of automotive components. He is currently accepting PhD students to further explore these interdisciplinary areas. Key research themes include: Autonomous vehicle perception systems Occlusion challenges in road safety Image sensor performance optimization Cybersecurity for connected vehicles Lean manufacturing methodologies His publications demonstrate a strong emphasis on practical applications, from improving pedestrian detection algorithms to evaluating sensor reliability under real-world conditions. Recent work explores urban mobility solutions and the integration of machine learning models for occlusion analysis.

Bram de JongeView profile

Associate Professor

• Operations Research
• Maintenance Optimization
• Asset Management
• +3 more

Dr. Bram de Jonge is an Associate Professor and program coordinator for the BSc in Econometrics and Operations Research (EOR) at the Faculty of Economics and Business, University of Groningen. He is affiliated with the Department of Operations, where he specializes in Operations Research & Management Science with a focus on Industrial Operations Management. His academic journey began at the University of Groningen, where he earned both his MSc in Econometrics, Operations Research & Actuarial Studies (cum laude) and his PhD. Dr. de Jonge's educational background includes: MSc in Econometrics, Operations Research & Actuarial Studies (cum laude), University of Groningen PhD, University of Groningen His research primarily focuses on maintenance optimization, asset management, reliability engineering, and stochastic operations research. Dr. de Jonge has developed significant expertise in condition-based maintenance optimization, where he applies mathematical modeling and stochastic processes to solve complex maintenance problems. His work often bridges theoretical operations research with practical industrial applications, particularly in optimizing maintenance policies under various constraints and uncertainties. He has made notable contributions to understanding the economic implications of different maintenance strategies and developing data-driven approaches for maintenance optimization. Analysis of Dr. de Jonge's publication record reveals a strong trajectory in maintenance optimization research, with particular emphasis on condition-based approaches. His work demonstrates increasing sophistication in handling complex scenarios including limited data availability, mobile maintenance resources, production-maintenance integration, and multi-unit systems. He has developed innovative mathematical techniques, such as matrix algebra applications for maintenance optimization, and has contributed significantly to the theoretical foundations through comprehensive literature reviews. His research consistently addresses practical industrial challenges while maintaining rigorous mathematical foundations. Dr. de Jonge actively supervises Master's thesis projects in Operations Research and teaches multiple courses including OR Modelling, Data-driven Optimization, and Planning and Control of Stochastic Systems. His teaching portfolio reflects his research expertise, creating a strong connection between his academic instruction and scholarly work. One of Dr. de Jonge's notable contributions to the field is the Maintenance Library, a comprehensive resource containing over 1,300 scientific papers in maintenance planning and optimization. This library serves as an important tool for researchers in the field, categorizing literature from 1,836 authors published across 139 different journals. The library demonstrates his commitment to advancing the field through knowledge organization and sharing.

Thijs HazenbergView profile

Researcher

• Plasma-assisted combustion
• Metal fuels
• Combustion simulation
• +3 more

Thijs Hazenberg is a Researcher at the Department of Mechanical Engineering, Eindhoven University of Technology (TU/e), specializing in plasma-assisted combustion and metal fuel combustion. He holds a master's degree from TU/e (2019) and conducted his internship at Rolls-Royce Deutschland. His research focuses on numerical techniques for simulating plasma-assisted combustion and metal fuel oxidation, contributing to emission reduction and sustainable energy solutions. He is part of the Power & Flow group under Prof. van Oijen and collaborates on projects like MPACE (plasma-assisted combustion) and zero-carbon metal fuel studies (2020-2025). His work emphasizes aerosol combustion dynamics, flame propagation, and iron particle oxidation. Recent studies explore radiative heat transfer effects on iron-air aerosol flames and emission control strategies in iron powder burners. He has received awards including the NVV combustion award (2019) for his master's thesis on metal flame models and the KNCV Golden Master Award (2020). Key projects involve multi-scale understanding of metal fuel combustion (2020-2025) and plasma-assisted combustion efficiency (2018-2022). Collaborations span experimental and theoretical approaches, with publications in Combustion and Flame and Proceedings of the Combustion Institute . His academic contributions bridge computational modeling with sustainable energy applications.

George HearnView profile

Associate Professor

• Structural Engineering
• Bridge Engineering
• Infrastructure Maintenance
• +3 more

George Hearn is an Associate Professor of Structural Engineering & Structural Mechanics at the University of Colorado Boulder's Civil, Environmental and Architectural Engineering School. As a Professional Engineer (PE), he specializes in bridge inspection, design, rehabilitation, and management with over 35 years of industry experience. His research focuses on structural systems like the CU/NEES Lab Reaction Wall and developing national databases for highway bridge maintenance actions. He has authored numerous papers on bridge preservation strategies, performance metrics, and lifecycle management. His work emphasizes integrating nondestructive evaluation (NDE) techniques with bridge management systems (BMS), particularly in quantifying maintenance actions and tracking structural health. Key areas of interest include load posting compliance, deterioration modeling for bridge components, and optimizing maintenance prioritization frameworks. Hearn collaborates with state transportation departments to improve infrastructure decision-making processes and has contributed to AASHTO guidelines for bridge preservation. Research contributions span bridge element condition reporting, performance indices aligned with national management measures, and the development of standardized databases for tracking maintenance actions. His work bridges theoretical engineering principles with practical implementation in public infrastructure systems. Publications since 2000 have explored topics ranging from faulted pavements at bridge abutments to reliability-based repair strategies, reflecting a career-long focus on structural safety and lifecycle analysis.

Joanne M. AtleeView profile

Professor

• Software Engineering
• Software Product Lines
• Feature Interaction Detection
• +3 more

Joanne M. Atlee is a Professor at the Cheriton School of Computer Science , University of Waterloo, Canada. Her research focuses on software engineering , particularly improving software quality through feature modeling and feature interaction management in complex systems like software product lines , systems-of-systems , and the Internet of Things . She develops theories of composition, interaction detection algorithms, coordination architectures, and proof systems for interoperability. Key research areas include Feature Interaction Management Software Product Line Engineering Model-Based Engineering Formal Verification Her recent publications explore AI-generated code detection (2024), variability-aware analysis (2024), and dynamic assertion generation (2023). Collaborations span institutions like McGill University , INRIA , and Siemens Canada , with applications in automotive software and cyber-physical systems .