جستجوی استاد راهنمای دانشگاهی

• Renewable Energy
• Wave Energy
• Electric Vehicle Integration
• +۷ مورد دیگر

Valeria Castellucci is a Senior Lecturer and Associate Professor in the Department of Electrical Engineering at Uppsala University, Sweden, affiliated with the Division of Electricity. She holds the title of Docent in Engineering Science with Specialisation in Science of Electricity, reflecting her advanced academic standing and research contributions. Her research focuses on renewable energy systems, particularly wave energy and the integration of electric vehicles into power grids. Key areas include demand-side flexibility, peak load management, load shifting, and the optimization of wave energy parks. Her work combines theoretical modeling with real-world applications, often based on case studies in Uppsala, such as microgrid operations and EV charging infrastructure in parking garages. The recent publications highlight a strong trend toward smart grid technologies, grid stability, and the role of distributed energy resources in modern power systems. Her research emphasizes practical solutions for integrating variable renewable sources and managing electricity demand efficiently. Docent in Engineering Science with Specialisation in Science of Electricity Valeria Castellucci is actively involved in research collaboration, particularly with colleagues such as Carl Flygare, Alexander Wallberg, and Rafael Waters. Her work has been cited in policy sources and referenced in Wikipedia, indicating broader impact beyond academia. She contributes to both journal publications and conference proceedings, maintaining a high level of scholarly output in energy and electrical engineering. She is based at Ångströmlaboratoriet in Uppsala and is a key contributor to Uppsala University's wave energy research, including work at the Lysekil Research Site. Her doctoral thesis, Sea Level Compensation System for Wave Energy Converters (2016), laid the foundation for much of her ongoing research in marine renewable energy systems.

• Wave Energy Conversion
• System Identification
• Optimal Control
• +۶ مورد دیگر

Mauro Bonfanti is a Fixed-term Assistant Professor at the Department of Mechanical and Aerospace Engineering (DIMEAS) at Politecnico di Torino, Italy. His academic work focuses on wave energy conversion systems, mechatronics, and applied mechanics within the field of industrial and information engineering. Dr. Bonfanti's primary research interests include wave energy conversion systems, system identification, optimal control, mechatronics, and renewable energy systems. His work centers on developing advanced control strategies for wave energy converters, with particular emphasis on improving energy extraction efficiency through innovative mechanical designs and control algorithms. He has made significant contributions to the understanding of wave-structure interactions, hydrodynamic modeling of floating bodies, and optimization of wave energy converter systems under various sea conditions. His research bridges theoretical modeling with practical implementation, often involving high-fidelity numerical simulations validated through experimental testing. His publication record demonstrates a strong focus on advancing wave energy conversion technology, with particular emphasis on control systems, hydrodynamic modeling, and optimization techniques. The research shows progression from fundamental modeling approaches to increasingly sophisticated control strategies and system integration. Recent work has expanded to include hybrid renewable energy systems that combine wave and wind energy technologies. Dr. Bonfanti serves as a Scientific Responsible for several research projects including OCEANGLIDE, AQUALEV, and WISE, which focus on innovative wave energy conversion technologies. He holds multiple patents related to wave energy conversion systems, including the WISE (Water-air Injectable Swath Elevator) and AQUALEV magnetic support systems. He actively supervises PhD students including Alessandro Brusasco, Matteo Mastorakis, Francesco Balestrieri, and Domenico Edoardo Sfasciamuro, guiding research in sustainable materials, mechanical engineering, and wave energy conversion systems. His teaching responsibilities include courses on System Identification and Optimal Control of Wave Energy Conversion Systems, as well as Mechatronics across multiple academic years. Dr. Bonfanti is a member of the Mechatronics and Servosystems research group at DIMEAS, where he collaborates on projects related to marine renewable energy systems and advanced control technologies.

Yong Kang Chenمشاهده پروفایل

استاد

• Applied Mechanics
• Renewable Energy Systems
• Energy Storage
• +۶ مورد دیگر

Professor Yong Kang Chen is a Professor of Applied Mechanics at the University of Hertfordshire, where he leads the Energy and Sustainable Design research group and serves as Head of the Automotive, Mechanical and Mechatronic Division in the School of Physics, Engineering & Computer Science. He holds a PhD, MSc, and BEng, and is a Chartered Engineer (CEng) with fellowships from the Institution of Mechanical Engineers (FIMechE) and Higher Education Academy (FHEA). His research focuses on applied mechanics with specialized interests in renewable energy systems, computational fluid dynamics, nanomaterials, and structural integrity. Key research themes include: Energy storage systems and flywheel technology optimization Phase change materials for building efficiency Wind turbine design for urban environments Surface engineering of polymer nano-composites Nano-fluid applications in thermal systems His publication portfolio demonstrates strong emphasis on sustainable energy solutions, with recent work exploring wind turbine shroud systems, PCM-enhanced building materials, and flywheel energy storage optimization. Nanomaterial research constitutes a significant secondary focus, particularly carbon quantum dots for optoelectronic applications. Honors include: Fellow of The Institution of Mechanical Engineers (FIMechE) Fellow of the Higher Education Academy (FHEA) He has secured over £1.3 million in research funding from EPSRC, Innovate UK, EU FP7 programs, and industrial partnerships. Notable projects include leadership roles in EU MAAT and SHELL consortiums, thermal analysis for Global Invacom Ltd, and development of structural health monitoring for wind turbine blades. He leads multiple active laboratories focusing on energy systems and advanced materials characterization.

• Digitalization
• Multi-Agent Systems
• Semantic Web
• +۵ مورد دیگر

Prof. Dr. Thomas Farrenkopf is a full-time Professor in the Department of Business Informatics at the Technische Hochschule Mittelhessen , serving as Dean of Studies . He leads the Business Informatics Bachelor program and specializes in digitalization, multi-agent systems, and AI-driven decision support. Expertise Areas : Industry 4.0, Smart Factory, Semantic Web, full-stack software development Contact : thomas.farrenkopf@mnd.thm.de Research Focus : His work bridges knowledge-based methods with practical applications in artificial intelligence, particularly through multi-agent systems for traffic modeling and business simulations. He developed AGADE Traffic (a knowledge-based traffic simulator) and ATHOS (a domain-specific language for multi-agent simulations), focusing on scalability and complexity reduction. Recent studies explore individual preferences' impact on traffic policies and agent-based feedback mechanisms in business contexts. Academic Contributions : With over 15 publications since 2013, his research spans agent-based modeling, semantic web applications, and smart manufacturing - notably improving throughput times in toolmaking by 90% through Industry 4.0 implementations. Teaching & Supervision : Actively supervises Bachelor's Practical Projects (BPP), providing guidance for internship-related academic work through structured evaluation processes and electronic reporting systems. Collaborations : Works with international researchers like Johannes Nguyen, Simon T. Powers, and Michael Guckert, publishing in venues such as SN Computer Science , Lecture Notes in Computer Science , and Journal of Artificial Societies and Social Simulation .

Elham Delzendehمشاهده پروفایل

دانشیار

• Digital Built Environment
• Building Information Modelling (BIM)
• Sustainable Architecture
• +۳ مورد دیگر

Dr. Elham Delzendeh is an Associate Professor and College Academic Lead for Employability at the College of Built Environment, Birmingham City University. She specializes in Digital Built Environment and Technological Design, with research emphasizing cutting-edge digital technology, building energy performance, occupant behavior, and Building Information Modelling (BIM). Her academic background includes a PhD in Architecture and Built Environment, an MSc and BSc in Architectural Engineering. PhD in Architecture and Built Environment MSc in Architectural Engineering BSc in Architectural Engineering Her research bridges practical and academic expertise in design and construction, focusing on occupant behavior analysis, energy-efficient building simulation, and Industry 4.0 technologies like digital twins. She has contributed extensively to energy performance modeling, occupant-driven systems, and sustainable urban interventions. Selected scientific awards include Fellow of the Higher Education Academy (FHEA) . She has supervised postgraduate research in digital built environments and occupant behavior, integrating real-world industry insights into her pedagogy.

Gareth Taylorمشاهده پروفایل

استاد

• Power Systems
• Smart Grids
• Renewable Energy Systems
• +۷ مورد دیگر

Professor Gareth Taylor is a Professor of Power Systems and Director of the Brunel Interdisciplinary Power Systems (BIPS) Research Centre at Brunel University London's College of Engineering, Design and Physical Sciences. He serves as Module Leader for the MSc Sustainable Electrical Power program and has been actively involved with the university since May 2000, progressing from National Grid Post-doctoral Scholar to his current position as Professor (appointed in 2012). He previously served as Head of the Department of Electronic and Electrical Engineering from May 2019 to June 2023 and holds a Visiting Professor position at Imperial College London (2023-2026). Professor Taylor earned his BSc in Applied Physics from Royal Holloway College, University of London (1987), followed by an MSc in Scientific and Engineering Software Technology from the University of Greenwich (1992), and completed his PhD in Computational Solid Mechanics at the University of Greenwich in March 1997. His doctoral research focused on finite volume methods for material non-linearity within multi-physics frameworks. His research spans power systems engineering with particular emphasis on smart grid technologies, renewable energy integration, and advanced computational methods. Professor Taylor has contributed to over 250 research publications in areas including power system operation and management, reactive power control, voltage regulation, and high-performance computing applications in electrical power systems. His work addresses critical challenges in modern power systems, particularly those related to the integration of renewable energy sources and the development of more resilient grid infrastructure. Analysis of his recent publications reveals a strong focus on addressing contemporary power system challenges, particularly the integration of renewable energy sources, smart grid technologies, and advanced computational methods. His work spans from fundamental power system analysis to practical applications in grid operation, with increasing emphasis on cybersecurity aspects of power system monitoring and the challenges posed by reduced system inertia in grids with high renewable penetration. Senior Member of IEEE Fellow of the Institute of Engineering and Technology (FIET) Chartered Engineer Fellow of the Higher Education Academy (FHEA) UK Regular Member for CIGRE Study Committee D2 (2016-2022) Member of Strategic Advisory Group for CIGRE Study Committee D2 (2023) Professor Taylor has led numerous significant research projects including TDX-ASSIST (€5.2M), e-HIGHWAY2050 (€8.2M), and HiPerDNO (€5.4M), with funding from EPSRC, European Commission, National Grid, and other major organizations. His current research portfolio includes projects on novel decoupled active/reactive power oscillation response, digitalization of power systems operation, and examining net zero policy in European energy markets. He also directs the BIPS Research Centre, which focuses on interdisciplinary power systems research with strong industry connections.

Zoltán Sütőمشاهده پروفایل

دانشیار

• Power Electronics
• Control Systems
• Power Converters
• +۵ مورد دیگر

Zoltán Sütő is an Associate Professor at the Budapest University of Technology and Economics, affiliated with the Department of Automation and Applied Informatics. His research focuses on advanced power electronics and control systems, with expertise in real-time implementation using FPGA technology. He maintains an active presence through institutional contacts at Budapest 1117, Magyar tudósok krt. 2., Q.B114, and can be reached via phone (+36 1 463-2337) or email (Suto.Zoltan@aut.bme.hu). Dr. Sütő's research encompasses: Design and optimization of power converters (dual active bridge, multilevel inverters) Real-time control algorithms for grid-connected systems and microgrids FPGA-based hardware-in-the-loop simulation methodologies Nonlinear dynamics in power electronic systems Artificial intelligence applications for fault diagnosis in drive systems His work bridges theoretical control models with practical implementations in renewable energy integration and power quality management. Recent publications demonstrate a strong focus on predictive control techniques, adaptive compensation methods, and optimization of power converter topologies. Research trends emphasize real-time validation, FPGA implementation, and AI-enhanced diagnostics across applications ranging from energy storage systems to industrial drives. Articles consistently address efficiency improvements, stability challenges, and novel modulation strategies in power conversion.

• Artificial Intelligence
• Educational Technology
• Power Systems
• +۶ مورد دیگر

Luiz Felipe Rocha de Faria is a Senior Lecturer at the Instituto Superior de Engenharia do Porto (ISEP), Instituto Politécnico do Porto, where he has served since 2020. His career spans over two decades in academic roles, including positions as Professor Adjunto (Assistant Professor) from 2010–2020 and earlier roles as a permanent lecturer. He holds a PhD in Electrical and Computer Engineering from Universidade do Porto (2002), a Master’s in the same field (1996), and a Licenciatura in Computer Engineering (1993). He is a founding member of e-IPP (eLearning Unit) and has led the Computer Engineering Department. His research focuses on Artificial Intelligence for Education and Power Systems , particularly through Adaptive Hypermedia , Intelligent Tutoring Systems , and Cyber-Physical Systems . He has contributed to projects like TINSEL (electrical installation design tutoring) and GECAD (intelligent systems for power grid control). A key theme in his work is User Modeling for personalized learning and Context Awareness in training environments. The 15 most recent articles highlight his expertise in adaptive educational technologies and power systems training . These works span from 2024 to 2010, with recurring subfields such as knowledge-based systems , user adaptation , intelligent alarm processing , and collaborative maintenance . His publications often integrate pedagogical modeling with real-time inference for complex systems. As a supervisor, Faria has mentored 10 MSc students and co-supervised 2 others, along with co-supervising 1 PhD thesis. He has participated in 32 research projects, including EU-funded initiatives like NORTEXCEL2020 and PIANiSM, focusing on medical devices , renewable energy integration , and smart education ecosystems . His current projects include the Lab Associate of Intelligent Systems (2021–2025) and HEIComp (2023–2025), addressing industry-academia alignment. He co-developed the PCMAT platform for mathematics education and TheRoute for tourism route customization. His work emphasizes practical implementation , collaborative learning , and decision support systems across engineering domains.

Tanushree Royمشاهده پروفایل

استادیار

• Cybersecurity
• Fault diagnostics
• Socio-technical systems
• +۴ مورد دیگر

Dr. Tanushree Roy serves as an Assistant Professor in the Department of Mechanical Engineering at Texas Tech University's Whitacre College of Engineering and is an Affiliate Faculty member at the National Wind Institute. Her research pioneers resilient human-centric smart city infrastructures through the integration of control theory, mathematical modeling, and machine learning to address critical challenges in safety, security, and resource optimization for urban systems. Her academic foundation includes: Ph.D. in Mechanical Engineering from The Pennsylvania State University (2022) M.S. in Mathematics from University of Central Florida (2015) M.E. in Electrical Engineering from Indian Institutes of Engineering Science and Technology, India (2011) B.Tech in Applied Electronics and Instrumentation from Maulana Abul Kalam Azad University of Technology, India (2009) Dr. Roy's research centers on cybersecurity , fault diagnostics , and socio-technical systems with specialized applications in smart transportation networks and battery energy storage systems. She develops innovative frameworks that merge human-centric sensing with technical measurements to combat cyberattacks and physical faults in cyber-physical-social systems, emphasizing safety-critical resilience for urban citizens. Her methodology uniquely combines model-based control with data-driven machine learning to address challenges like social data integrity, human behavior modeling, and multi-scale anomaly characterization. Analysis of her 15 most recent publications (2021-2025) reveals dominant trends in cyberattack detection for connected vehicles, thermal fault tolerance in battery systems, and socio-technical traffic modeling. Key technical approaches include Koopman operator theory for secure estimation, control barrier functions for safety certification, and redundancy-based data fusion techniques. These works consistently bridge theoretical control systems with practical smart city implementation, demonstrating strong interdisciplinary connections between transportation engineering, energy systems, and cybersecurity. No scientific awards are documented in the provided information. Dr. Roy actively mentors three PhD students—Sanchita Ghosh (since 2022), Faysal Ahamed, and Soumyoraj Mallick (both since 2024)—alongside undergraduate researcher Mercedes Hernandez. Her research is executed through the Smart Human-centric Automation Resilience (SHARE) Lab, which has secured projects including the secure autonomous mobility testbed and participates in workforce development via Texas Tech's Engineering Research Internship Experience (ERIE) program for high school students. The SHARE Lab operates at the intersection of transportation and energy systems, maintaining two primary research thrusts: resilient human-centric transportation networks and safeguarding battery energy storage infrastructure. Current projects include SUMO-based cyberattack validation for connected vehicle platoons, self-learning voltage estimation under sensor attacks, and thermal fault-tolerant battery management. The lab maintains active collaborations with national conferences (ACC, CCTA) and industry partners to advance real-world implementation of resilient smart city technologies.

Alan Mantoothمشاهده پروفایل

استاد

• Analog and Mixed-Signal IC Design
• Power Electronics
• Semiconductor Device Modeling
• +۳ مورد دیگر

Alan Mantooth is a Distinguished Professor holding the Twenty-First Century Research Leadership Chair in Engineering within the Department of Electrical Engineering at the University of Arkansas, Fayetteville. He serves as Director of the National Center for Reliable Electric Power Transmission (NCREPT), Executive Director for GRAPES (NSF I/UCRC) and SEEDS (DoE Center), and Deputy Director of the NSF Engineering Research Center for Power Optimization of Electro-Thermal Systems (POETS). His educational background includes: B.S. in Electrical Engineering, University of Arkansas M.S. in Electrical Engineering, University of Arkansas Ph.D. in Electrical Engineering, Georgia Institute of Technology Dr. Mantooth's research centers on analog/mixed-signal IC design, power electronics CAD, and semiconductor device modeling with emphasis on harsh-environment applications. His pioneering work in silicon carbide (SiC) and gallium nitride (GaN) power systems has enabled high-temperature operation for electric vehicles and renewable energy infrastructure, significantly advancing reliability in extreme conditions. His 2025 publications reveal strong trends toward AI-driven power electronics (e.g., SolarFormer++ for PV profiling), wide-bandgap device modeling (β-Ga2O3, SiC), and innovative packaging solutions. Key themes include reliability engineering for extreme environments, multi-physics optimization, and explainable AI for safety-critical power systems. Major scientific recognition includes: IEEE Fellow (2009) for power electronic device modeling Three R&D 100 Awards (2009, 2014, 2016) for SiC power modules IEEE Power Electronics Society Technical Achievement Award (2019) Multiple university teaching/research awards including SEC Faculty Achievement Award (2015) As an exceptional mentor (UA Outstanding Mentor 2006-2008), he co-founded Lynguent and Ozark Integrated Circuits. His centers NCREPT, GRAPES, and SEEDS have secured major funding from NSF, DoE, and industry partners, supporting over 350 refereed publications and numerous patents. Current research focuses on AI-enhanced power electronics, recyclable packaging, and next-generation wide-bandgap device characterization. He leads the NCREPT test facility and multi-institutional teams developing grid-connected power electronic systems, secure energy delivery architectures, and thermal management solutions for high-power-density applications, with direct impact on electric transportation and renewable energy integration.

Kai Li Limمشاهده پروفایل

پژوهشگر

• Electric Vehicles
• Autonomous Vehicles
• Data Engineering
• +۱۲ مورد دیگر

Dr Kai Li Lim is the St Baker Fellow in E-Mobility at the Dow Centre for Sustainable Engineering Innovation , part of the Faculty of Engineering, Architecture and Information Technology at The University of Queensland (UQ) . Specializing in data engineering , telematics , and autonomous vehicle systems , his research examines electric vehicle (EV) usage patterns , charging reliability , and spatiotemporal data analysis to inform policy and sustainable transport strategies. Education : BEng (Hons) in Electronic and Computer Engineering (University of Nottingham), MSc in Computer Science (Lancaster University), PhD in Artificial Intelligence and Robotics (The University of Western Australia, funded by Australian Government Research Training Programme). Research Interests include: Electric vehicle telematics and data analytics Computer vision and deep learning for autonomous navigation Policy development for sustainable transport Infrastructure planning for EV and hydrogen systems Integration of cloud computing and IoT in mobility solutions Publication Trends reveal a focus on EV charging behaviors , data platform architectures , and autonomous driving frameworks , with recent work addressing regional emission disparities , modular safety systems , and online assessment integrity . Scientific Awards : St Baker Fellow in E-Mobility, Visiting Fellowship at UC Davis Electric Vehicle Research Center, Australian Government Research Training Programme (PhD funding). Supervision and Grants : Available for supervision, Dr Lim has secured funding from Energy Consumers Australia , iMove CRC , and Australian Urban Research Infrastructure Network (AURIN) for projects on EV charging incentives, freight emissions modeling, and longitudinal vehicle data databases. Labs and Collaborations : Collaborates with UC Davis Electric Vehicle Research Center , UQ School of Civil Engineering , and UQ School of Electrical Engineering and Computer Science . Leads the UQ Teslascope Project and contributes to the Green Australian Vehicle Ownership (GreenAVO) Capability for AURIN .

• Logic-in-memory
• Machine learning
• Nanocomputing
• +۷ مورد دیگر

Marco Vacca is an Associate Professor in the Department of Electronics and Telecommunications (DET) at Politecnico di Torino and a member of the Interdepartmental Center PIC4SeR - PoliTO Interdepartmental Centre for Service Robotics. His work bridges electronics, nanotechnology, and computing architecture with a focus on innovative solutions to the memory wall problem. His research spans Logic-in-memory computing, Machine learning hardware acceleration, and Nanocomputing with specific emphasis on circuit architectures for probabilistic computing, magnetic devices, hybrid technologies integration, and CAD tools for emerging technologies. Dr. Vacca leads research in RISC-V extensions, hardware accelerators for AI, and autonomous robot systems for agricultural applications through the VLSILAB research group. Recent publications reveal a strong trend toward solving fundamental computing challenges through nanoscale innovations, particularly in memory-centric architectures, molecular field-coupled computing, and novel transistor technologies. His work demonstrates how logic-in-memory approaches can overcome traditional von Neumann limitations while improving energy efficiency for AI workloads. Editorial board member of ELECTRONICS (2021-2023) Program committee member for Design, Automation and Test in Europe Conference (DATE) 2020-2021 Dr. Vacca supervises PhD student Alessandro Varaldi working on 'Hardware AI Accelerators for Automotive Applications' and has led significant research projects including 'Device for Storage and Processing Data and Related Method' (2020-2021) and 'Quantum Computing and Quantum Communication: State of the Art and Applications in the Telco Sector' (2020). His grant portfolio shows strong industry and competitive funding support. As a core member of the VLSILAB research group, Dr. Vacca contributes to advancing VLSI theory and design applications with particular focus on implementing Big Data, Machine Learning, and Neural Networks in specialized hardware architectures that push the boundaries of conventional computing.

• Artificial Intelligence
• Machine Learning
• Distributed Learning
• +۷ مورد دیگر

Berta María Guijarro Berdiñas is a Researcher in the Department of Computer Science and Artificial Intelligence at the University of A Coruña , Spain. She is affiliated with the Laboratory for Research and Development in Artificial Intelligence and teaches courses like Machine Learning , Development of Intelligent Systems , and Programming at both undergraduate and postgraduate levels. Research Focus: Her work lies at the intersection of Artificial Intelligence , Machine Learning , and Knowledge-Based Systems . Key contributions include frugal learning (limited data), anomaly explanation , and distributed learning for edge devices. She applies these to areas like health informatics , forest fire management , and human-robot interaction . Recent Publications span explainable AI , anomaly detection , multi-agent systems , and low-power machine learning . Her articles appear in top venues like Expert Systems with Applications and IEEE Transactions on Neural Networks and Learning Systems . Grants & Projects include EU-funded initiatives, Spanish Ministry of Science grants, and regional collaborations. She focuses on AI for healthcare , smart systems , and distributed learning .

• Intelligent Control Systems
• Fault and Anomaly Detection
• Virtual and Robust Sensors
• +۵ مورد دیگر

Dr. José Luis Calvo Rolle serves as a Professor in the Department of Industrial Engineering at the School of Engineering, Universidade da Coruña (UDC), specializing in Systems Engineering and Automation. His research focuses on intelligent control systems, fault detection, and virtual instrumentation within the Cybernetic Science and Technology Research Group. Teaches across multiple programs including Master's in Industrial Computing and Robotics, Textile Technology, and Occupational Risk Prevention Coordinates thesis supervision across Industrial Engineering and related disciplines His research spans intelligent control systems and optimization, with significant contributions in virtual sensors, fault detection, and AI-driven modeling for industrial applications. Current projects integrate machine learning with industrial processes for naval construction, wastewater treatment, and precision livestock farming, demonstrating cross-disciplinary impact from energy systems to agricultural technology. Recent publications reveal strong trends in applying deep learning to industrial metaverse frameworks, wastewater optimization, and livestock monitoring systems. His work bridges theoretical control engineering with practical implementations in energy management, naval manufacturing, and sustainable agriculture, frequently utilizing dimensionality reduction and one-class classification techniques. Dr. Calvo Rolle actively mentors students through thesis supervision across multiple engineering disciplines and coordinates research projects with diverse funding sources including the European Commission, Spanish National Research Agency, and industrial partners like Navantia and Telefónica. His laboratory work centers on the Cybernetic Science and Technology Research Group, developing testbeds for industrial automation, virtual instrumentation, and AI-driven monitoring systems. Current initiatives include digital twin implementations for naval manufacturing and smart energy management systems.

• Energy Technology
• Chemical Engineering
• Bioenergy
• +۷ مورد دیگر

Leteng Lin is a Senior Lecturer at the Department of Built Environment and Energy Technology, Faculty of Technology, Linnaeus University. He holds a PhD in Chemical Engineering (2013), Master's (2005), and Bachelor's (2002) degrees from the same field. His research focuses on energy technology, chemical engineering, and sustainable resource utilization, particularly in combustion, gasification, and pyrolysis processes for biomass and waste feedstocks.