Lukas Einhaus is a Researcher and PhD student in the Embedded Systems department at the University of Duisburg-Essen since April 2020, affiliated with the Intelligent Embedded Systems (IES) research group and contributing to initiatives including Elastic AI and the IoT Garage. His academic background includes: Bachelor of Science from University of Duisburg-Essen, thesis focused on programming abstractions for concurrent embedded systems Master of Science from University of Duisburg-Essen, specializing in distributed and reliable systems with thesis research on quantizing neural networks Einhaus's research centers on designing neural networks for efficient hardware implementation on FPGAs, with primary expertise in quantized or low-precision neural networks that reduce bit depth (typically 1-3 bits) for computations and information flow. This work enables energy-efficient AI solutions for embedded and IoT devices where resource constraints are critical. His publication record from 2021-2025 reveals consistent innovation in FPGA-based neural network optimization, with applications spanning fluid flow estimation, time-series analysis, and real-time stream processing. Core themes include Elastic AI for adaptive systems, precomputation techniques for convolutional layers, and hardware-aware neural architecture design. He previously contributed to the BMBF-funded project "KI-Sprung: LUTNet" (until March 2022), developing energy-efficient AI networks using elementary lookup tables for FPGA deployment. Einhaus actively mentors students through the IoT Garage initiative, supervising practical projects including drink-mixing machines, exoskeletons, and ball-challenge systems.
Professor Qing Xiao is a faculty member in the Department of Naval Architecture, Ocean and Marine Engineering at the University of Strathclyde . With over 25 years of expertise in Computational Fluid Dynamics (CFD) , they focus on bio-inspired fluid dynamics and marine renewable energy systems. Their research includes modeling flapping-wing aerodynamics, tidal turbines, and floating wind turbines with coupled aero-hydrodynamic simulations. Research Themes: Bio-inspired robotics, offshore renewable energy, fluid-structure interaction, vortex-induced vibrations. Collaborations: EPSRC-funded projects, Supergen ORE Hub partnerships, and industrial alliances. Recent Work: AI-driven surrogate models for floating offshore wind turbines, hyperelastic material applications in wave energy converters, and digital twin frameworks for structural health monitoring. Scientific Recognition: OMAE Subrata Chakrabarti Young Professional Award (2017) Strathclyde Teaching Excellence Award (2013) Students & Supervision: Advising PhD candidates like Kobe Hoi Yin Yung and Hoi Yin Yung, with graduates Xiang Li and Yang Luo contributing to bio-inspired robotics and CFD-FSI studies. Labs & Teams: Leads an interdisciplinary CFD-FSI research group at Strathclyde, fostering academic-industrial cooperation and hosting visiting researchers.
Jesper Liniger is an Associate Professor at AAU Energy within the Faculty of Engineering and Science at Aalborg University. He works in the Esbjerg Energy Section focusing on Offshore Renewable Energy Systems and is affiliated with AAU BLUE – Marine & Maritime Research. His office is located at Niels Bohr Street 8, 6700 Esbjerg, Denmark. Research Interests Marine Growth Engineering and automated cleaning solutions for offshore structures Underwater robotics including Remotely Operated Vehicles (ROVs) and autonomous inspection systems Wind turbine engineering with emphasis on hydraulic pitch systems and fault detection Fluid power engineering applications in marine environments Development of robotic solutions for offshore renewable energy infrastructure Research Trends Dr. Liniger's recent publications demonstrate a strong focus on developing robotic solutions for offshore renewable energy infrastructure. His work bridges theoretical control systems with practical marine applications, particularly addressing marine growth (biofouling) challenges on offshore structures. The research shows increasing interdisciplinary collaboration, combining robotics, fluid mechanics, and wind energy systems to create integrated solutions that improve operational efficiency and reduce maintenance costs in offshore environments. Scientific Awards Innovation Project of the Year (2024) - For underwater robotics development Esbjerg Universitetspris (2018) - University award recognizing research excellence Advising and Research Leadership Dr. Liniger actively supervises PhD students and serves as principal investigator or supervisor on multiple major projects including "NextGen Robotics" for offshore wind farms and "Towards Enhancing Perception and Navigation for Autonomous Underwater Inspection Drone." His research portfolio includes collaborations with industry partners like Vattenfall and Business Center Funen, demonstrating strong industry-academia connections focused on practical applications with economic impact. Research Teams and Facilities Liniger is part of AAU BLUE – Marine & Maritime Research, which provides specialized facilities for marine robotics testing and development. His work involves close collaboration with researchers in control systems, fluid mechanics, and renewable energy. The research group has developed experimental frameworks for testing underwater and surface vehicle operations, with recent media coverage highlighting their innovative approaches to solving marine growth challenges on offshore structures.
Mahsa Derakhshani is a Senior Lecturer (equivalent to Associate Professor) in Digital Communications at Loughborough University's Wolfson School of Mechanical, Electrical and Manufacturing Engineering. She leads research in the Signal Processing and Networks Research Group (SPNRG) and serves as an Associate Editor for the IET Signal Processing Journal. Her academic journey includes a PhD from McGill University (2013), followed by postdoctoral roles at the University of Toronto and Imperial College London. Key awards include the Royal Academy of Engineering/The Leverhulme Trust Research Fellowship (2020-21) and NSERC Postdoctoral Fellowships (2015-2017). Research interests focus on digital communications, machine learning for signal processing, wireless networks, and reinforcement learning applications. Recent work addresses challenges in satellite communications, OTFS modulation, and opto-physiological monitoring. She has authored over 70 publications spanning topics like NOMA systems, MIMO optimization, and edge-assisted live streaming. Education: PhD (McGill, 2013), MSc (Sharif University, 2008), BSc (Sharif University, 2006) Affiliations: IEEE Senior Member, IET Member, Fellow of the Higher Education Academy Grants & Funding: Leverhulme Trust, Royal Academy of Engineering, NSERC Labs/Teams: Active in SPNRG and collaborates on projects involving 5G/6G networks, satellite systems, and biomedical signal processing. Current research emphasizes AI-driven solutions for communication networks and wearable health monitoring technologies.
Chun-Hua Guo is a Professor in the Department of Mathematics and Statistics at the University of Regina, Faculty of Science. His research focuses on matrix analysis, scientific computing, and applications in tensor computations and nonlinear matrix equations. He teaches advanced courses such as MATH 869 Numerical Analysis. Dr. Guo’s recent work emphasizes iterative methods for solving eigenvalue problems of nonnegative tensors, matrix equations arising in nano research, and convergence analysis of numerical algorithms. His publications address topics like Newton-Noda iteration, modified Newton methods for Z-eigenpairs, and algebraic Riccati equations associated with M-matrices. His research trends highlight advancements in computational techniques for matrix functions (e.g., matrix pth root), tensor Perron pairs, and stability analysis of iterative algorithms. These contributions bridge theoretical linear algebra with practical computational challenges in engineering and scientific domains. Dr. Guo’s advising and grants involve developing efficient numerical methods for complex systems. His work has implications for fields requiring high-precision matrix computations, such as control theory, stochastic modeling, and nano-material simulations.
Associate Professor Joshua San Miguel leads research in computer architecture and systems at the University of Wisconsin-Madison, with an affiliate role in Computer Sciences. His work focuses on energy-efficient computing for IoT devices, microarchitecture innovations, and networks-on-chip. He holds a PhD (2017) and BASc (2012) from the University of Toronto. Education: PhD in Electrical & Computer Engineering, University of Toronto (2017) BASc in Engineering Science (ECE), University of Toronto (2012) Research Interests: Approximate computing for energy harvesting systems Branch prediction and value prediction in processors Cache architectures and networks-on-chip for many-core processors Intermittent computing resilience His recent work emphasizes value-level parallelism (Carat/uSystolic), RTL simulation acceleration (TaroRTL), and personalized neural network inference (CAP’NN). His research has been recognized with the NSF CAREER Award (2021) and multiple IEEE Micro Top Picks. Grants & Advising: Active in supervising advanced independent studies and master’s/dissertation research. Extensive grant funding includes the NSF CAREER Award and the Grainger Faculty Scholarship. Labs & Teams: Leads research groups focused on approximate computing and energy-efficient architectures within the Electrical & Computer Engineering department.
Norm Murray is a Professor at the Canadian Institute for Theoretical Astrophysics (CITA) within the University of Toronto . With a Ph.D. from UC Berkeley (1986), his research spans nonlinear dynamics , planetary formation , solar system evolution , and active galactic nuclei . His work combines theoretical physics with observational data from radio telescopes, X-ray satellites, and cosmological simulations. Recent research focuses on galaxy formation (via FIRE simulations), dark matter interactions in dwarf galaxies, and AGN disk dynamics . He employs machine learning for planetary collision modeling and investigates the interplay of magnetohydrodynamics and radiative transfer in quasar environments. Publications highlight his expertise in computational astrophysics, spanning topics from cosmic molecular gas mapping to the stability of exoplanetary systems.
Professor Dinos Arcoumanis FREng is a distinguished academic at City, University of London, where he has served as Professor since 2000. He previously held academic positions at Imperial College London from 1988-2000, progressing from Lecturer to Reader and ultimately to Professor of Internal Combustion Engines. At City University, he has held significant leadership roles including Head of the Aeronautical, Civil and Mechanical Engineering Department, Dean of the School of Engineering & Mathematical Sciences, Pro-Vice-Chancellor for Research and International Links, and Deputy Vice-Chancellor (Research & International) until August 2014. He remains actively involved in research and academic leadership, currently serving as Director of the International Institute of Cavitation Research and Coordinator of the World Cities World Class (WC2) University Network. Professor Arcoumanis holds undergraduate and graduate degrees in Physics, Engineering and Mechanical Engineering from the Aristotelian University of Thessaloniki, Greece (1973), the University of California at Irvine, USA (1980), and the Imperial College of Science, Technology and Medicine, London (1984), respectively. His primary research focuses on internal combustion engines, with specific expertise in combustion, exhaust emissions, and engine lubrication. Professor Arcoumanis has pioneered the application of laser diagnostics and computational fluid dynamics to study internal combustion engines, with particular interest in automotive fuels including renewable and alternative fuels. His work bridges fundamental fluid mechanics with practical engine applications, addressing critical environmental engineering challenges in the transportation sector. His recent research has expanded into cavitation phenomena, fuel cell technology, and the development of sustainable propulsion systems for future transportation needs. Professor Arcoumanis's extensive publication record demonstrates a clear evolution in research focus, beginning with fundamental studies of diesel engine combustion and progressing toward advanced fuel injection systems, alternative fuels, and environmental sustainability. His work consistently bridges theoretical fluid mechanics with practical engine applications, with recent emphasis on cavitation phenomena in fuel systems and the integration of renewable energy technologies with traditional combustion systems. The interdisciplinary nature of his research connects mechanical engineering principles with environmental science, materials science, and energy systems engineering. Professor Arcoumanis has received numerous prestigious awards and honors throughout his career: 1991 Dugald Clerk Prize of IMechE 1995 and 1998 Arch T. Colwell Merit Award of the Society of Automotive Engineers Elected Fellow of the Royal Academy of Engineering (FREng) in 2001 Honorary doctorate from St. Petersburg State Polytechnic University of Russia (2009) Professor Arcoumanis has made significant contributions to academic leadership and professional service. He founded the International Journal of Engine Research (JER) in 1999 and serves as its Editor for Europe. He has coordinated the World Cities World Class (WC2) University Network since 2010, which brings together international institutions in major cities to address research challenges in transport, global health, business, and cultural industries. He has also served as a consultant to Brussels (DG17) and Bechtel Ltd. on the Auto-oil II European Programme (1998-2000), and was appointed Ambassador-at-Large of the Hellenic Republic for Energy Policy and New Technologies in September 2012. His research has been supported by various funding bodies including the Lloyd's Register Educational Trust, which funds the International Institute of Cavitation Research that he directs. Professor Arcoumanis leads the International Institute of Cavitation Research, a partnership between City University London, Loughborough University, and Delft University of the Netherlands. He has established collaborative research teams focused on engine combustion, fuel injection systems, and alternative propulsion technologies. His research group has developed advanced experimental facilities for studying fuel spray dynamics, combustion processes, and cavitation phenomena in engine systems. These teams regularly collaborate with automotive industry partners and international research institutions to address cutting-edge challenges in engine technology and sustainable transportation.
Marian Verhelst is a Professor at KU Leuven's Faculty of Engineering Science, renowned for her research in hardware-efficient computing and dedication to STEM education. Her work spans hardware acceleration for machine learning, edge AI, and in-memory computing, with a focus on energy optimization and algorithm-hardware co-design. Her research interests include: Designing flexible hardware for ultra-low-power edge AI systems Optimizing sparsity-aware architectures for deep learning workloads Advancing chiplet-based and 3D memory technologies Co-designing algorithms and hardware for probabilistic AI Pioneering STEM outreach through KU Leuven InnovationLab Recent publications (2023–2025) demonstrate strong trends in: Hardware-software co-optimization for edge ML systems Efficient data movement in heterogeneous accelerators Low-precision and sparse computation techniques RISC-V based customizable SoCs Sustainable AI accelerator design Awards & Honors: Young Academy of Europe Award (2021) for science communication and STEM advocacy She leads significant educational initiatives, including the KU Leuven InnovationLab which has engaged 150 schools and 13,000 students since 2014. The program develops hands-on STEM projects (e.g., AI-powered wheelchairs, sustainable energy systems) and provides teacher training to inspire youth in engineering.
Duc Duy (Louis) Nguyen serves as Professor in Finance at Durham University Business School, where he joined in 2021 after previously holding positions as Associate Professor of Finance at King's College London and Assistant Professor in Banking and Finance at the University of St Andrews. His academic journey includes a PhD in Finance from the University of Edinburgh, an MSc (Distinction) in Accounting, Finance, and Management from the University of Bristol, and a BSc (Hons) in Computing from the National University of Singapore. Nguyen's research spans empirical corporate finance, banking, climate finance, and household finance, with publications in top-tier journals including Review of Financial Studies , Management Science , Journal of Financial and Quantitative Analysis , and Review of Finance . His work has been featured in prominent media outlets such as Forbes , Harvard Business Review , BBC , and the Boston Globe , and has influenced policy discussions with citations by the U.S. Senate Committee on Banking and the United Nations Environment Programme. His research portfolio demonstrates evolving interests from traditional banking and corporate governance topics toward increasingly important areas like climate finance and social finance. Nguyen has established productive collaborations with researchers including Jens Hagendorff, Vathunyoo Sila, and Ivan Lim, resulting in numerous high-impact publications. David Hume Publication Prize (2015) 2025 Vietnam International Conference in Finance Best Paper Award Best Registered Report on Politics and Corporate Power, Review of Corporate Finance Studies Semi-finalist, 2018 FMA Europe Best Paper Award Finalist, 2019 FMA Asia/Pacific Best Paper Award Finalist, 2015 FMA European Best Paper Award As an active contributor to the academic community, Nguyen serves as Associate Editor for the European Journal of Finance and the British Accounting Review . He regularly presents at international conferences and meetings organized by central banks, governments, and international organizations, including the Federal Reserve Banks of New York and St Louis. His research has been funded by prestigious organizations including the British Academy/Leverhulme Trust and the Carnegie UK Trust. Nguyen currently supervises PhD students Bingzhi Zhang and Jing Wei, continuing his commitment to developing the next generation of finance scholars.
Falah Alobaid is a Full Professor (Tenured) at LUT School of Energy Systems, LUT University, specializing in energy systems engineering. He holds a Ph.D. from the Technical University of Darmstadt (2013), recognized with the university's Energy Special Prize (2014), and completed habilitation in Energy Systems (2018) with the title of Privatdozent (2019). His research focuses on power plant technologies, including combustion, gasification, and CO₂ capture, with expertise in modeling, simulation, and pilot-scale experimentation. Education: Ph.D. (Energy Systems), Technical University of Darmstadt, Germany (2013) Habilitation (Energy Systems), Technical University of Darmstadt, Germany (2018) Research interests emphasize sustainable energy solutions: Fluidized bed combustion and gasification CO₂ capture and storage technologies Renewable energy integration Process simulation and dynamic modeling of power systems Thermal energy storage systems His work bridges experimental and computational approaches, with contributions to EU projects such as SCARLET and OptiMaDyn. Publications reflect advancements in fluidized bed systems, CFD-DEM modeling, and operational flexibility of thermal power plants. Recent trends include integrating artificial intelligence for process optimization and exploring novel materials for carbon capture. Awards include the Energy Special Prize (2014) and recognition for his habilitation work. He leads the Institute of Energy Systems and Technology research group, focusing on bioenergy, waste-to-energy systems, and low-carbon technologies. Grants and collaborations span EU-funded initiatives and national projects. Advising focuses on graduate students in energy systems, though no specific names are listed. Laboratory work includes managing the Institute of Energy Systems and Technology, where experimental setups for fluidized beds and solar thermal systems are developed. Future research targets net-negative CO₂ emissions via chemical looping gasification and enhanced renewable energy storage.
Ian Sellers is Professor in Electrical Engineering at University at Buffalo's School of Engineering and Applied Sciences. He specializes in next-generation solar cells and materials for space photovoltaics, with appointments including Marie Curie Fellow (2004-2006) and Visiting Academic Fellow at Oxford (2009-2012). His research examines: Novel photovoltaic materials and architectures Ultra-low power electronic systems MEMS-based sensors and energy harvesters Beyond-CMOS computing technologies Recent publications demonstrate advances in ultra-low power sensor design (MEMS accelerometers), energy-efficient computing (MESO technology), and miniaturized imaging systems. The work shows consistent focus on optimizing power efficiency through innovations in circuit design, materials integration, and system architecture. Before joining UB, Sellers held positions as Presidential Professor at University of Oklahoma and Senior Research Scientist at Sharp Labs of Europe. His international collaborations include extended research stays in France and the UK.
Mamoun Qasem is a Lecturer in Cyber Security at the University of South Wales, Faculty of Computing, Engineering and Science. His work focuses on IoT Security, autonomous vehicle cybersecurity, wireless sensor networks, and RPL protocol enhancements. He has collaborated with industry leaders like Huawei and Thales Ltd, contributing to international standards through the IETF. Research Interests include: Defending systems from cyber threats RPL protocol optimization Adversarial deception methods in complex systems IoT threat hunting and network security Publications span top journals (e.g., IEEE Communications Letters) and conferences (e.g., IEEE WCNC). He leads projects like RsIoT for oil & gas field monitoring and supervises a KESS PhD student on adversarial deception in cyber defense. Mamoun actively reviews for journals like Elsevier Computer Networks and coordinates international conference workshops (e.g., ICSOC, CFATI). No scientific awards are explicitly listed. He coordinates interdisciplinary research initiatives and serves as a technical reviewer for multiple platforms.
He Zhu is an Assistant Professor at Rutgers, The State University of New Jersey, affiliated with the Department of Computer Science. His research focuses on programming languages, compilers, wireless communications, IoT systems, and 5G network protocols. He received the PLDI 2019 Distinguished Paper Award for his contributions to formal methods in programming systems. His work addresses challenges in vehicle-to-everything (V2X) communication, resource allocation in sidelink networks, network security, and dynamic authorization frameworks for IoT devices. Key research interests include optimizing 5G NR (New Radio) protocols for vehicular environments, developing efficient data aggregation techniques for user equipment, and enhancing service layer mechanisms for IoT systems. He leads projects funded by the NSF, such as 'Formal Symbolic Reasoning of Deep Reinforcement Learning Systems,' and has contributed to advancements in beam management, RACH protocols, and energy-efficient DRX configurations in wireless networks. His office is located in Core 315. Notable Awards: PLDI 2019 Distinguished Paper Award Grants: NSF Grant: Formal Symbolic Reasoning of Deep Reinforcement Learning Systems His research group explores intersections between compiler design, distributed systems, and network architecture, with applications in smart mobility, edge computing, and secure IoT communication. He actively contributes to standards development for 5G and future generations of wireless networks.
Konstantinos Nikitopoulos is a Professor at the University of Surrey , UK, specializing in Wireless Communications and Signal Processing . His research focuses on MIMO Systems , Open-RAN , and Non-Linear Processing for next-generation wireless networks. His recent work explores Analogue Processing for Tbps Wireless Systems and Neuromorphic Computing in MU-MIMO detection. He has developed frameworks like MIMO-SoftiPHY and SACCESS for software-based radio acceleration and power-efficient network design. Key Publications : Power-Efficient RIC, NL-COMM, NeuroMIMO Collaborators : Rahim Tafazolli, George Katsaros, Marcin Filo His research impacts 6G Network Development through innovations in Beamforming , Channel Estimation , and Software-Defined Radios .
