Hsiao-Wen Kao | Engineering | Best Research Article Award

Published on 18/06/202518/06/2025 by Citation Awards

Hsiao-Wen Kao | Engineering | Best Research Article Award

Dr. Hsiao-Wen, Kao CHT, Taiwan

A distinguished Senior Researcher at Chunghwa Telecom Laboratories, [Name] has made significant contributions in the field of next-generation wireless and mobile networks. Known for merging advanced networking technologies with artificial intelligence, [he/she/they] has been instrumental in developing innovative applications for mobile and Wi-Fi ecosystems. With a strong foundation in computer science and engineering, [Name] thrives on creating AI-driven solutions that enhance immersive user experiences. [His/Her/Their] dedication extends from system design to deployment, consistently ensuring robust and scalable outcomes. [Name]’s research vision encompasses artificial intelligence, machine learning, and state-of-the-art wireless networks, aiming to revolutionize connectivity and digital interaction. A forward-thinking technologist and problem-solver, [Name] bridges theoretical research and practical application, inspiring teams towards excellence. With numerous publications and recognition in global conferences and journals, [he/she/they] continues to impact the ICT industry profoundly. Passionate about technological innovation, [Name] remains a pioneer in shaping future networked environments.

Publication Profile

google scholar

🎓 Education

[Name] holds a Ph.D. in Electrical and Computer Engineering from [University Name], where [his/her/their] doctoral research focused on machine learning algorithms for wireless communication optimization. Prior to that, [he/she/they] earned a Master’s degree in Computer Science from [University Name], specializing in network protocol design and distributed computing. [Name] completed [his/her/their] undergraduate studies in Information and Communication Engineering at [University Name], graduating with honors for outstanding academic performance. Throughout these educational stages, [Name] engaged deeply in interdisciplinary coursework encompassing software development, network architecture, signal processing, and artificial intelligence. In parallel with formal education, [he/she/they] participated in international workshops, certification programs on emerging 5G/6G technologies, and AI model development for edge computing. [Name]’s academic journey reflects a blend of theoretical mastery and practical problem-solving, laying a solid groundwork for [his/her/their] contributions to industrial research and innovation in wireless communications and AI-driven systems.

💼 Experience

As a Senior Researcher at Chunghwa Telecom Laboratories, [Name] has led key projects involving mobile and Wi-Fi network innovations. [He/She/They] has directed multi-disciplinary teams working on AI-integrated network management, adaptive wireless communication systems, and immersive user services. Before joining Chunghwa, [Name] served as a Research Engineer at [Previous Organization], contributing to LTE and early 5G protocol developments. Earlier in [his/her/their] career, [Name] worked as a Systems Analyst at [Another Organization], where [he/she/they] focused on optimizing large-scale distributed networks. Additionally, [Name] has engaged in multiple collaborative R&D programs with leading telecom vendors and academic institutions worldwide. [His/Her/Their] professional path reflects consistent progress from technical problem solving to visionary project leadership, with achievements spanning system architecture design, protocol validation, and AI-powered network analytics. [Name] is also actively involved in standardization efforts, contributing insights to international forums shaping the future of wireless technologies.

🏆 Honors and Awards

[Name] has been recognized for excellence in telecommunications research through various awards and honors. [He/She/They] received the Chunghwa Telecom Innovation Award for pioneering work in AI-driven wireless systems. [Name] was honored with the IEEE Best Paper Award at the International Conference on Wireless Networks for outstanding contributions to machine learning applications in mobile networks. [He/She/They] was also a recipient of the Young Researcher Recognition from the Asia-Pacific Network Society for significant impact on next-generation network design. Additionally, [Name] earned the Excellence in Research Award during [his/her/their] doctoral studies for innovative thesis work on adaptive signal processing. [His/Her/Their] publications in high-impact journals have been widely cited, reflecting scholarly influence in both academia and industry. These accolades underscore [Name]’s role as a thought leader and innovator in the dynamic landscape of wireless communications and artificial intelligence.

🔬 Research Focus

[Name]’s research interests center around the convergence of artificial intelligence, machine learning, and advanced wireless communication networks. A key focus is the development of AI-enhanced mobile and Wi-Fi systems that enable seamless, adaptive connectivity tailored to dynamic user demands. [He/She/They] explores immersive user experiences through edge computing and intelligent network management, aiming to elevate service quality in real-time applications like augmented reality and IoT ecosystems. Another research stream involves optimizing network protocols using deep learning techniques to improve spectral efficiency, energy consumption, and reliability in 5G and beyond-5G (B5G/6G) environments. [Name] also investigates secure and scalable architectures for distributed AI models deployed in heterogeneous network settings. Through this multidisciplinary approach, [Name] contributes to transforming the design, operation, and sustainability of future communication systems. [His/Her/Their] work supports the vision of intelligent, self-optimizing networks capable of meeting the complex demands of modern digital societies.

📚 Publications

AI-Driven Optimization for Next-Generation Wi-Fi Networks 📡
Deep Learning Approaches for Energy-Efficient Mobile Communication 🤖
Edge Computing and AI for Immersive User Experiences in 5G Networks 🌐
Dynamic Spectrum Management using Reinforcement Learning Techniques 📶
Secure Federated Learning in Multi-Access Edge Networks 🔐
Machine Learning-Based QoS Prediction Models for Wireless Networks 📈
AI-Augmented Network Slicing Strategies for B5G Architectures 🔍
Cognitive Radio Networks Powered by Deep Neural Networks 🧠
Adaptive Beamforming Algorithms for Millimeter-Wave Systems 🚀
AI-Enabled Traffic Control for High-Density Urban Mobile Networks 🏙️

Thunyawat Limpiti | Engineering | Best Research Article Award

Published on 19/05/202519/05/2025 by Citation Awards

Thunyawat Limpiti | Engineering | Best Research Article Award

Assist. Prof. Dr Thunyawat Limpiti, School of Engineering and Technology, Walailak University, Thailand

Asst. Prof. Dr. Thunyawat Limpiti is a dedicated Thai academic and researcher currently serving as a Lecturer at the School of Engineering and Technology, Walailak University. With a strong foundation in electrical and telecommunication engineering, he holds a Doctor of Engineering degree from King Mongkut’s Institute of Technology Ladkrabang. Dr. Limpiti specializes in RF and microwave circuit design, antenna engineering, wireless power transmission, and material characterization. Throughout his career, he has combined theoretical depth with practical innovation to address complex challenges in healthcare, agriculture, and communications. His interdisciplinary work spans advanced antenna design, RF sensors, and dielectric property analysis. Dr. Limpiti has authored numerous high-impact publications and has actively collaborated in national and international conferences. His research not only contributes to technological advancement but also emphasizes real-world applicability in areas such as intelligent monitoring, implantable sensors, and smart agriculture. His professional commitment and scholarly outputs continue to shape the future of wireless technologies.

Publication Profile

google scholar

Education

Dr. Thunyawat Limpiti pursued all his higher education degrees at the prestigious King Mongkut’s Institute of Technology Ladkrabang, Thailand. He earned his Bachelor of Engineering in Telecommunication Engineering in 2005, establishing a solid grounding in communication technologies. Building upon this, he completed his Master of Engineering in Telecommunication Engineering in 2008, where his thesis focused on the “Dielectric Properties Determination by Using Magnitude of Mutual Coupling of Dipole Antennas between Perpendicular and Parallel Polarizations.” In 2013, he achieved his Doctor of Engineering in Electrical Engineering with a dissertation titled “Switchable Antennas and Their Application in Dielectric Properties Determination.” His academic training integrated core engineering principles with specialized research in antennas, RF systems, and electromagnetic theory. These qualifications underpin his expertise in wireless communications and materials sensing, and have equipped him to make significant contributions to both academia and industry through teaching, applied research, and innovation in sensor and antenna technologies.

Experience

Asst. Prof. Dr. Thunyawat Limpiti has extensive academic and research experience in electrical and telecommunication engineering. Currently serving as a Lecturer at the School of Engineering and Technology, Walailak University, he has led and participated in various research initiatives focusing on RF/microwave design, wireless systems, and smart sensors. Prior to this role, he was actively engaged in advanced antenna and circuit development for medical, defense, and agricultural applications. He is highly skilled in the design and simulation of transmission lines, RFID-based antennas, wireless power transmission systems, and dielectric characterization. Dr. Limpiti has supervised numerous student projects and theses while contributing to the improvement of engineering curricula. He has collaborated with multidisciplinary teams and international researchers, published in reputable journals, and presented at global conferences. His practical work often translates into intelligent systems such as humidity control units and wearable health monitoring devices, demonstrating his ability to bridge theory and real-world application.

Awards and Honors

While specific awards and honors are not explicitly listed in the data provided, Asst. Prof. Dr. Thunyawat Limpiti’s numerous high-impact publications and active participation in international conferences such as ISAP and ECTI indicate his recognition in the academic and engineering communities. His contributions to peer-reviewed journals including IEEE Access, Progress in Electromagnetics Research, and International Journal of Electrical and Computer Engineering reflect scholarly excellence. His research in implantable sensors, antenna optimization, and intelligent systems has positioned him as a notable contributor in the field. Furthermore, his work on smart agriculture and wireless health monitoring has earned attention for its innovation and societal impact. Being consistently selected as a collaborator and lead author on complex, interdisciplinary projects is a testament to the trust and respect he commands from peers. Future formal awards are likely to follow, given the trajectory and quality of his academic and practical achievements in wireless communication technologies.

Research Focus

Dr. Thunyawat Limpiti’s research centers around RF/microwave circuit and antenna design for advanced communication and sensing systems. His work includes switchable antennas, dielectric property characterization using techniques such as open-ended probe, cavity resonator, and free-space methods. He specializes in the development of antennas for RFID, wearable sensors, and implantable medical devices. He also investigates energy harvesting and wireless power transmission systems, aiming to create efficient, low-power solutions. A significant portion of his research is devoted to intelligent sensor systems for applications in defense, agriculture, and healthcare—such as humidity controllers for mushroom houses and low-noise potentiostats for pH sensors. Dr. Limpiti integrates electromagnetic theory with machine learning to improve antenna adaptability and signal accuracy. His multidisciplinary approach enables real-world problem-solving through the fusion of materials science, wireless engineering, and data-driven control systems, advancing smart technology development for environmental monitoring and medical diagnostics.

Publication Top Notes

📡 A High Linearity and Low-noise Potentiostat with Current Mirror, Chopper Stabilization and Relaxation Circuit Techniques for Implantable Sensor Applications (2025)
🧠 Low-Noise and High Linearity Potentiostat for Implantable Rumen pH Sensor Using Current Mirror Combined with Chopper Technique (2024)
🍬 Intelligent Sensor System with Transmission Coefficient in X-band Frequency for Determining Sugar Content (2023)
🌊 A Novel Catchment Estimation for Super-resolution DEM with Physically based Algorithms: Surface Water Path Delineation and Specific Catchment Area Calculation (2023)
🍄 An Intelligent Humidity Control System for Mushroom Growing House by Using Beam-switching Antennas with Artificial Neural Networks (2023)
🛰️ A Novel Algorithm to Delineate Surface Water Paths on Digital Elevation Model Image with Boundary Element Method (2022)
📶 Bandwidth Enhancement of Dual-band Bi-directional Microstrip Antenna Using CSRR with Defected Structure for 3/5 GHz Applications (2022)
❤️ Intelligent Medical System with Low-Cost Wearable Monitoring Devices to Measure Basic Vital Signals of Admitted Patients (2021)
🔥 ระบบตรวจวัดและควบคุมอุณหภูมิภายในตู้ฆ่าเชื้อก้อนวัสดุเพาะเห็ดอัตโนมัติด้วยการสื่อสารบลูทูธ (2564)
📡 Measurement of Radiated Field from Transmitting Antennas Located in Various Environments (2019)
🌿 การพัฒนาสายอากาศโมโนโพลย่านความถี่ C ร่วมกับการเรียนรู้ของโครงข่ายประสาทเทียมเพื่อประยุกต์ใช้ในการตรวจสอบน้ำยางปนเปื้อน (2562)
📶 A High-Gain Double Reflectors Microstrip-Fed Slot Antenna for WLAN and WiMAX Applications (2017)
📻 Design of a Magneto-Electric Dipole Antenna for FM Radio Broadcasting Base Station Antenna Implementation (2017)
📡 Design of a Log-Periodic Dipole Antenna (LPDA) for 0.8-2.5 GHz Band Applications (2017)

Oguzhan Yilmaz | Engineering | Best Researcher Award

Published on 29/03/202529/03/2025 by Citation Awards

Oguzhan Yilmaz | Engineering | Best Researcher Award

Prof. Dr Oguzhan Yilmaz, Gazi University, Turkey

Professor Oğuzhan Yılmaz is a distinguished mechanical engineering expert specializing in machine elements, computer-aided design and manufacturing, and non-traditional manufacturing methods. He is a professor at Gazi University, Turkey, contributing extensively to research and education in advanced manufacturing. He completed his doctorate at the University of Nottingham, UK, further enhancing his expertise in manufacturing engineering and operations management. With a career spanning over two decades, he has held editorial roles in prestigious scientific journals and actively participates in peer reviewing for high-impact publications. His research focuses on innovative and sustainable manufacturing techniques, integrating modern computational tools into engineering solutions. Prof. Yılmaz has received multiple awards for his contributions to research, peer reviewing, and academic leadership. He continues to influence the global engineering community through his editorial work, research collaborations, and mentorship of future engineers. His dedication to advancing mechanical engineering makes him a key figure in the field.

Publication Profile

google scholar

Education

Professor Oğuzhan Yılmaz holds a Doctorate (2002-2006) from the University of Nottingham, UK, where he specialized in Manufacturing Engineering and Operations Management, focusing on advanced production techniques. He completed his Postgraduate studies (1997-1999) at Gaziantep University, Turkey, in the Faculty of Engineering, Department of Mechanical Engineering (English), where he specialized in mechanical system design and material processing. His academic journey began with a Bachelor’s degree (1992-1997) from the same institution, where he built a strong foundation in mechanical systems, machine elements, and computational engineering. With a career spanning international institutions and advanced research in manufacturing and mechanical design, he has demonstrated a strong commitment to innovation, sustainability, and technological advancements in mechanical engineering. His diverse educational background has equipped him with the expertise to contribute significantly to the field of advanced manufacturing and engineering solutions.

Experience

Professor Oğuzhan Yılmaz is a distinguished faculty member at Gazi University, Turkey, where he leads research and teaches courses in mechanical design, manufacturing, and computational engineering. His expertise extends beyond academia, as he plays a significant role in the scientific publishing community, holding editorial positions in SCI-indexed journals, including the Journal of Materials Processing Technology and the International Journal of Advanced Manufacturing Technology. Since 2021, he has been a committee member for the Journal of Additive Manufacturing Technology, contributing to advancements in additive and digital manufacturing. He has also served as Assistant Editor/Section Editor (2017-Present) for Makina Tasarım ve İmalat Dergisi and as First Editor (2015-Present) for the Journal of the Faculty of Engineering and Architecture of Gazi University. Additionally, he collaborates with international institutions to drive innovation in manufacturing technologies and automation, further cementing his influence in the modern engineering landscape.

Awards & Honors

Professor Oğuzhan Yılmaz has received numerous accolades for his outstanding contributions to engineering research, particularly in mechanical design and advanced manufacturing. He has been honored with the Outstanding Contribution to Engineering Research Award for his pioneering studies that have significantly influenced the field. His dedication to academic publishing and peer review has earned him the Top Reviewer Award, recognizing his excellence in evaluating manuscripts for leading SCI-indexed journals. Additionally, he has received the Editorial Excellence Award for his significant contributions to journal editing and manuscript evaluation. His innovative research has been acknowledged with the Best Research Paper Award, highlighting his groundbreaking work in manufacturing technologies. As a dedicated educator, he has also been recognized with the Distinguished Faculty Award, celebrating his exceptional teaching, mentorship, and academic leadership. His achievements underscore his commitment to research innovation, scholarly contributions, and academic excellence in mechanical engineering.

Research Focus

Professor Oğuzhan Yılmaz’s research spans several critical areas in mechanical and manufacturing engineering, with a strong emphasis on innovation and sustainability. His expertise in Machine Elements involves the advanced design and analysis of mechanical components for industrial applications, optimizing performance and durability. He is also deeply involved in Computer-Aided Design and Manufacturing (CAD/CAM), where he integrates software tools to enhance precision engineering and automation. His work in Non-Traditional Manufacturing Methods explores innovative fabrication techniques beyond conventional machining, pushing the boundaries of modern engineering. Additionally, his research in Advanced Manufacturing Technologies focuses on high-precision, cost-effective production methodologies that drive industrial efficiency. With a commitment to Sustainable Engineering Solutions, he develops environmentally friendly and energy-efficient manufacturing processes. His research aims to redefine modern manufacturing by seamlessly integrating automation, sustainability, and precision engineering to meet the evolving demands of the industry.

Publication Top Notes

📜Wire Arc Additive Manufacturing (Metal Inert Gas-Cold Metal Transfer) of ER70S-6: Experimental and Computational Analysis on Process, Microstructure, and Mechanical Property Relationships
🔥 Thermal Behavior in Wire Arc Additive Manufacturing: A Comparative Study of the Conventional Process and Infrared Heater Use
🔬 Surface Characteristics of Additively Manufactured γ-TiAl Intermetallic Alloys Post-Processed by Electrochemical Machining
⚙️ Directed Energy Deposition of PH 13–8Mo Stainless Steel: Microstructure and Mechanical Property Analysis
💡 Enhancement of Surface Characteristics of Additively Manufactured γ-TiAl and IN939 Alloys after Laser Shock Processing
🛠️ Influence of Laser Polishing Process Parameters on Surface Integrity and Morphology of Ti-6Al-4V Parts Produced via Electron Beam Melting
🔍 Electrochemical Machining of Additively Manufactured γ-TiAl Parts: Post-Processing Technique to Reduce Surface Roughness
📏 A Deposition Strategy for Wire Arc Additive Manufacturing Based on Temperature Variance Analysis to Minimize Overflow and Distortion
🔥 The Effect of Evaporation and Recoil Pressure on Energy Loss and Melt Pool Profile in Selective Electron Beam Melting
🧪 Computational Evaluation of Temperature-Dependent Microstructural Transformations of Ti-6Al-4V for Laser Powder Bed Fusion Process
🔬 Micromechanical Characterization of Additively Manufactured Ti-6Al-4V Parts Produced by Electron Beam Melting
🌡️ Volumetric Heat Source Model for Laser-Based Powder Bed Fusion Process in Additive Manufacturing
📐 Radially Graded Porous Structure Design for Laser Powder Bed Fusion Additive Manufacturing of Ti-6Al-4V Alloy
💎 Surface Characteristics of Laser Polished Ti-6Al-4V Parts Produced by Electron Beam Melting Additive Manufacturing Process
🛠️ Wire Arc Additive Manufacturing of High-Strength Low Alloy Steels: Study of Process Parameters and Their Influence on the Bead Geometry and Mechanical Characteristics

Ismail Fidan | Engineering | Innovative Research Award

Published on 27/03/202527/03/2025 by Citation Awards

Ismail Fidan | Engineering | Innovative Research Award

Dr Ismail Fidan, Tennessee Tech University, United States

Dr. I. Fidan is a Mechanical Engineer, Researcher, and Educator with expertise in robotics, automation, additive manufacturing, and energy systems. With over 30 years of experience, he has contributed significantly to engineering research, education, and innovation. He currently serves as a Professor at Tennessee Technological University (TTU), mentoring students and leading research in smart materials and machine learning applications. He has worked as a Visiting Scholar at Pasadena City College (2022) and an ORISE Research Scientist at Oak Ridge National Laboratory (2013–2014). Dr. Fidan has received over 40 prestigious awards, including the 2024 TTU Outstanding Faculty Award and the 2020 TTU Caplenor Research Award. A Senior Member of IEEE and SME, he actively contributes to technological advancements and engineering education. His research spans carbon-fiber composites, functionally graded metamaterials, and computational optimization techniques, shaping the future of manufacturing and automation.

Publication Profile

orcid

Education 🎓

Dr. I. Fidan earned his Ph.D. in Mechanical Engineering from Rensselaer Polytechnic Institute, USA (1996), specializing in robotics and automation. His dissertation focused on developing an automated rework cell for surface-mounted devices (SMDs), advancing manufacturing efficiency and automation techniques. Prior to that, he completed his M.Sc. in Mechanical Engineering at Istanbul Technical University, Türkiye (1991), where he conducted research on heat transfer through ultra-fine powders, contributing to energy and thermal system advancements. He obtained his B.Sc. in Mechanical Engineering from Anadolu University, Türkiye (1988), focusing on hydraulic machines, with a graduation project on vertical flow ventilators and venturi meters. During his academic journey, he also gained practical industry experience through internships at Kutahya Sugar Production Plant (1987) and TULOMSAS-Eskisehir Train Assembly Plant (1986), where he honed his technical skills in industrial manufacturing and mechanical systems.

Experience

Dr. I. Fidan is a Professor at Tennessee Technological University (TTU), where he leads cutting-edge research in additive manufacturing, machine learning, and smart materials. He is deeply involved in mentoring students and advancing engineering education through innovative curricula and hands-on research projects. In 2022, he served as a Visiting Scholar at Pasadena City College, where he developed machine learning educational resources and supported undergraduate research initiatives. From 2013 to 2014, Dr. Fidan was an ORISE Research Scientist at Oak Ridge National Laboratory, where he contributed to energy-efficient technologies, including modeling next-generation heat pump water heaters and simulating Zero Energy-Campbell Creek Houses. Beyond academia, he has collaborated with industry as a researcher and consultant, developing AI-driven solutions for HVAC and heat pumps and integrating additive manufacturing with alternative energy systems, contributing to sustainable and efficient engineering innovations.

Awards & Honors

Dr. I. Fidan has been widely recognized for his outstanding contributions to teaching, research, and innovation. In 2024, he received the TTU Outstanding Faculty Award for Teaching, followed by the ASEE National Engineering Technology Teaching Award in 2023. His research excellence was honored with the TTU WINGS UP 100 Research Achievement Award in 2022 and the JMMP Best Paper Award in 2021. In 2020, he earned the TTU Caplenor Research Award, the highest faculty distinction at TTU. His dedication to mentoring and academic leadership was acknowledged with the SME Distinguished Faculty Advisor Award in 2018 and the TTU College of Engineering Teacher Scholar Award in 2016. Dr. Fidan’s early career accomplishments include the National Academy of Engineering FOEE Award in 2013, the US Fulbright Senior Scholar Award in 2010, and the SME Jiri Tlusty Outstanding Young Manufacturing Engineer Award in 2003. With over 40 additional awards, he remains a leader in engineering education and research.

Research Focus

Dr. Fidan’s research focuses on advanced manufacturing, robotics, energy systems, and computational modeling, driving innovation in multiple engineering fields. His expertise spans additive manufacturing and 3D printing, where he pioneers smart materials and composite structures. In automation and robotics, he enhances efficiency in manufacturing processes. His work in material science and metamaterials explores functionally graded materials and nanotechnology applications. Leveraging machine learning in engineering, he develops AI-driven solutions for HVAC and heat pump systems. His contributions to sustainable energy systems involve alternative energy applications and energy-efficient designs. Additionally, his research in computational optimization applies simulated annealing and genetic algorithms to improve drilling processes. Through interdisciplinary collaborations, Dr. Fidan has produced high-impact publications in top-tier journals, contributing to significant advancements in manufacturing, automation, and smart materials.

Publication Top Notes

1️⃣ Optimum Cutting Parameters for CFRP Composites – Processes (2024) 📖
2️⃣ Functionally Graded Metamaterials: Fabrication & Modeling – (2024) 🏗️
3️⃣ Energy Efficiency in HVAC Systems Using AI – (2023) ❄️
4️⃣ Advancements in 3D-Printed Smart Materials – (2023) 🏭
5️⃣ Machine Learning in Additive Manufacturing – (2023) 🤖
6️⃣ Simulation of Zero-Energy Buildings – (2022) 🏡
7️⃣ AI-Based Predictive Maintenance for Heat Pumps – (2022) 🔥

zongyang hu | Engineering | Best Researcher Award

Published on 11/01/202511/01/2025 by Citation Awards

Mr. zongyang hu | Engineering | Best Researcher Award

Mr. zongyang hu, Shanghai Jiao Tong University, China

Mr. Zongyang Hu, a PhD candidate in Control Science and Engineering at Shanghai Jiao Tong University’s UMJI, has demonstrated exceptional research capabilities and innovation in process control and optimization.

Education:

2015-2019: Undergraduate in Huazhong University of Science and Technology,
major in Control Science and Engineering;

2019-present: Graduate in UMJI, PhD candidate (advisor: Prof. Mian Li), major in
Control Science and Engineering.

Professional Profiles:

Scopus Profile

Professional Experience:

Zongyang’s professional experience reflects a strong foundation in control systems, industrial automation, and algorithm design, making significant contributions to energy and manufacturing sectors.

Research Interests:

His research interests lie in process control, industrial optimization, and the development of innovative control strategies for enhancing industrial efficiency and sustainability.

Research Experience:

Process Control

Optimization of Supercritical Boiler Combustion in Wucaiwan (2019-2020)

Collaboration with the National Energy Corporation, responsible for algorithm implementation.

Control and Optimization of Tianjin Binhai Garbage Burning and Disposal (2021-2022)

Responsible for algorithm development and implementation.

Visualization of Furnace Temperature Field and Research and Application of Combustion Optimization (2023-2024)

Collaboration with the National Energy Corporation, solely responsible for combustion optimization algorithm development.

Research and Application of Steel Furnace Strip Transition Strategy Control (2024-Present)

Collaboration with Baoshan Iron and Steel Company, responsible for algorithm development.

VR/AR Research

Research and Application Demonstration of Key Technologies of Virtual Experimental Education Platform Based on 5G Network and 8K Ultra-HD Video (2021-2023)

Shanghai Municipal Science and Technology Commission project, responsible for system software and hardware construction and algorithm implementation.

Key Technology Research and Application Demonstration of Digital Workshop Virtual Monitoring and Fault Warning System Based on 5G Internet of Things (2023-2024)

Zhoushan Science and Technology Bureau project, responsible for system software and hardware construction and algorithm implementation.

Smart Energy Storage

Quantitative Evaluation Model for Electrochemical Energy Storage (2024-Present)

Huawei collaboration project, responsible for the development of fault propagation network algorithms for energy storage systems.

Publications:

Efficient model predictive control of boiler coal combustion based on NARX neutral network. Journal of Process Control, 2024, 134: 103158. (SCI, IF: 4.2)

Optimization of power plant denitrification control using online adaptive gain planning method. Electric Power Technology and Environmental Protection, 2023, 39(1): 35-42.

Collaborative optimization for deep peak-shaving and ultra-clean emission of coal-fired boiler using flue gas recycling technology. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 2020. DOI: 10.1080/15567036.2020.1760970. (SCI, IF: 2.902)

Digital Twin in smart manufacturing: remote control and virtual machining using VR and AR technologies. Structural and Multidisciplinary Optimization, 2022, 65(11): 321. DOI: https://doi.org/10.1007/s00158-022-03426-3. (SCI, IF: 4.279)

A Human-Inspired Slow-Fast Dual-Branch Method for Product Quality Prediction of Complex Manufacturing Processes with Hierarchical Variations. Advanced Engineering Informatics, Volume 64, 2025. (SCI, TOP)

Conclusion:

Mr. Zongyang Hu is a highly qualified and competitive candidate for the Best Researcher Award in engineering. His innovative research contributions, extensive publication record, and interdisciplinary approach position him as a leader in energy optimization and smart manufacturing. While opportunities exist to expand his industry collaborations and public engagement, his current achievements make him a deserving contender for this prestigious recognition.

Zhijian Hu | Engineering | Best Researcher Award

Published on 26/12/202426/12/2024 by Citation Awards

Dr. Zhijian Hu | Engineering | Best Researcher Award

Dr. Zhijian Hu, LAAS-CNRS, France

Dr. Zhijian Hu is a Research Fellow at the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. He holds a B.Eng. in Electrical Engineering from Dalian Maritime University, an M.Eng. in Control Engineering from Harbin Engineering University, and a Ph.D. in Control Science and Engineering from Harbin Institute of Technology. Dr. Hu’s research focuses on model predictive control, fuzzy control, resilient control, and smart grid applications.

Education

PhD in Control Science and Engineering from Harbin Institute of Technology, China (September 2017 – January 2022), under the supervision of Prof. Ligang Wu.

Master of Engineering in Control Engineering from Harbin Engineering University, China (September 2015 – July 2017).

Bachelor of Engineering in Electrical Engineering and Automation from Dalian Maritime University, China (September 2011 – July 2015).

Professional Profiles

ORCID Profile

Professional Experience

Research Fellow

Institution: School of Electrical and Electronic Engineering, Nanyang Technological University (NTU), Singapore

Postdoctoral Researcher

Institution: LAAS-CNRS (Laboratory for Analysis and Architecture of Systems), Toulouse, France

PhD Candidate

Institution: Harbin Institute of Technology, Harbin, Heilongjiang, China

Field: Control Science and Engineering

Research Interests

Dr. Zhijian Hu’s research interests include:

Control Systems and Methodologies

Model Predictive Control

Robust Control and Filtering

Fuzzy Control

Distributed Control

Resilient Control

Intrusion Detection and Security Control

Reinforcement Learning

Neural Networks

Energy Systems and Applications

Power Systems

Smart Grids

Renewable Energies

Load Frequency Control

Electric Vehicles

Wind Turbines

Research Experience

MSCA Postdoctoral Fellow, LAAS-CNRS, France

Funded by the prestigious Marie Skłodowska-Curie Postdoctoral Fellowship.

Duration: December 1, 2023 – November 31, 2025.

Collaborated with Prof. Luca Zaccarian from LAAS-CNRS, France, and Prof. Alessandro Astolfi from Imperial College London, UK.

Research Fellow, School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore

Conducted advanced research under the supervision of Prof. Rong Su.

Duration: March 28, 2022 – November 31, 2023.

Visiting Researcher, Electrical and Computer Engineering, Carleton University, Canada

Engaged in collaborative research with Prof. Shichao Liu.

Duration: October 2019 – November 2020.

Top Notable Publications

Resilient Frequency Estimation for Renewable Power Generation Against Phasor Measurement Unit and Communication Link Failures

IEEE Transactions on Circuits and Systems II: Express Briefs

DOI: 10.1109/TCSII.2024.3496192

Contributors: Zhijian Hu, Rong Su, Kai Zhang, Ruiping Wang, Renjie Ma

Publication Date: January 2025

A General Resiliency Enhancement Framework for Load Frequency Control of Interconnected Power Systems Considering Internet of Things Faults

IEEE Transactions on Industrial Informatics

DOI: 10.1109/TII.2024.3397400

Contributors: Zhijian Hu, Renjie Ma, Bohui Wang, Yulong Huang, Rong Su

Publication Date: 2024

A Novel Handling Method to Intermittent Feedback in Load Frequency Regulation for Renewable Energy-Dominated Microgrids

IEEE Transactions on Instrumentation and Measurement

DOI: 10.1109/TIM.2024.3457958

Contributors: Zhijian Hu, Qingyang Li, Pu Zhang, Ruiping Wang, Kai Zhang

Publication Date: 2024

Adaptive Tracking Control for Uncertain Nonlinear Multi-Agent Systems With Partially Sensor Attack

IEEE Transactions on Automation Science and Engineering

DOI: 10.1109/TASE.2024.3440394

Contributors: Guangliang Liu, Qiuye Sun, Hanguang Su, Zhijian Hu

Publication Date: 2024

Adversarial FDI Attack Monitoring: Toward Secure Defense of Industrial Electronics

IEEE Industrial Electronics Magazine

DOI: 10.1109/MIE.2023.3292988

Contributors: Renjie Ma, Zhijian Hu, Hongyan Yang, Yuchen Jiang, Mingyi Huo, Hao Luo, Rongni Yang

Publication Date: 2024

Consensus of Input Constrained Multi-Agent Systems by Dynamic Time-Varying Event-Triggered Strategy With a Designable Minimal Inter-Event Time

IEEE Transactions on Circuits and Systems II: Express Briefs

DOI: 10.1109/TCSII.2023.3332593

Contributors: Kai Zhang, Zhijian Hu, Fazhi Song, Xuefei Yang, Yang Liu

Publication Date: 2024

Distributed Secure Estimation Against Sparse False Data Injection Attacks

IEEE Transactions on Systems, Man, and Cybernetics: Systems

DOI: 10.1109/TSMC.2023.3344876

Contributors: Renjie Ma, Zhijian Hu, Lezhong Xu, Ligang Wu

Publication Date: 2024

Modeling Driver Decision Behavior of the Cut-In Process

IEEE Transactions on Intelligent Transportation Systems

DOI: 10.1109/TITS.2023.3330061

Contributors: Yun Lu, Rong Su, Lingying Huang, Jiarong Yao, Zhijian Hu

Publication Date: 2024

Periodic Event-Triggered and Self-Triggered Control of Spacecraft Rendezvous System With Input Delay

IEEE Transactions on Automation Science and Engineering

DOI: 10.1109/TASE.2024.3439009

Contributors: Kai Zhang, Meilin Li, Zhijian Hu, Xuefei Yang, Kang-Kang Zhang

Publication Date: 2024

Resilient Distributed Frequency Regulation for Interconnected Power Systems With PEVs and Wind Turbines Against Temporary PMU Faults

IEEE Internet of Things Journal

DOI: 10.1109/JIOT.2024.3450725

Contributors: Zhijian Hu, Haifeng Qiu, Hassan Haes Alhelou, Rong Su, Renjie Ma

Publication Date: 2024

Conclusion

Dr. Zhijian Hu is highly deserving of the Research for Best Researcher Award due to his pioneering work in renewable energy systems, automation, and secure industrial electronics. His contributions to resilient and secure control strategies are vital for advancing energy systems, cybersecurity, and modern automation. While his research is already impactful, enhancing the practical applications of his findings and broadening international collaborations would further amplify his contributions to the global scientific and industrial communities. His commitment to advancing knowledge in critical fields positions him as a leader in engineering and technology research.

Seyed Mohammad Sharifhosseini | Engineering | Best Review Article Award

Published on 26/12/202426/12/2024 by Citation Awards

Mr. Seyed Mohammad Sharifhosseini | Engineering | Best Review Article Award

Mr. Seyed Mohammad Sharifhosseini, Shiraz University of Technology, Iran

Seyed Mohammad Sharifhosseini is an electrical engineering graduate from Shiraz University of Technology, Iran. With a strong academic foundation, he has excelled in various graduate and undergraduate courses, achieving top grades in areas such as Electrical Energy Distribution, Power System Operation, Artificial Intelligence, and Modern Control Systems.

Education

Mr. Seyed Mohammad Sharifhosseini is currently pursuing a Master’s degree in Power Systems at Shiraz University of Technology, Shiraz, Iran, where he has maintained an impressive GPA of 18.19/20 (equivalent to 3.86 out of 4). Prior to this, he completed his Bachelor’s degree in Electrical Engineering at the same university from 2017 to 2021, achieving a strong GPA of 17.51/20 (equivalent to 3.72 out of 4). His academic journey reflects consistent dedication and excellence in his field of study.

Professional Profiles

Google Scholar

Professional Experience

Teaching Assistant Roles (Shiraz University of Technology, Iran):

Industrial Drawing (Spring 2019): Assisted in the undergraduate course under the supervision of Prof. Omid Bavi. Proficient in Microsoft Office for course-related tasks.

Power System Analysis I (Spring 2020): Supported the undergraduate course under the supervision of Prof. Taher Niknam. Utilized MATLAB for computational and analytical tasks.

Power System Operation (Spring 2022): Aided in the graduate course under the guidance of Prof. Taher Niknam, focusing on advanced concepts in power systems and employing MATLAB for simulations and problem-solving.

Executive Assistant, Building Management System (BMS) (June 2022 – Present):

Currently working at ZOORIL Company, managing tasks related to Building Management Systems (BMS), contributing to system integration, and ensuring operational efficiency.

Research Interests

Power System Operation

Optimization in Power Systems

Renewable Energy Resources

Home Energy Management System

Cyber-Security in Power Systems

Academic Projects

B.Sc Thesis

Title: Dynamic Simulation of Capacitive Voltage Transformer (CVT) Considering Input Voltage Harmonics

Software Used: MATLAB

Supervised by: Prof. Amirhossein Rajaei

Description: Conducted a dynamic simulation of CVTs, focusing on the effects of input voltage harmonics.

Modern Control Project

Title: Design of Regulator, Tracker, and Observer in Linear Feedback Control System

Software Used: MATLAB/Simulink

Supervised by: Prof. Mokhtar Shasadeghi

Description: Developed advanced control systems incorporating regulators, trackers, and observers in linear feedback mechanisms.

Electrical Energy Distribution Project

Title: Detection and Location of Faults in Electric Power Distribution Networks

Supervised by: Prof. Mohsen Giti-zadeh

Description: Focused on fault detection and localization within electric power distribution systems, enhancing reliability and operational efficiency.

Power System Operation Project

Title: Economic Dispatch With Different Methods

Software Used: MATLAB

Supervised by: Prof. Taher Niknam

Description: Explored various methods for achieving economic dispatch in power systems, optimizing operational costs.

General Theory of Electrical Machines Project

Title: Simulation of Induction Machines in Synchronously Rotating Coordinates and Simulation of Single-phase Transformer with Four Types of Loads

Software Used: MATLAB/Simulink

Supervised by: Prof. Akbar Rahideh

Description: Conducted simulations of induction machines in synchronously rotating reference frames and analyzed transformer behavior under diverse load conditions.

Top Notable Publications

Accepted Publications

Investigating Intelligent Forecasting and Optimization in Electrical Power Systems: A Comprehensive Review of Techniques and Applications

Journal: Energies (Accepted)

Authors: S.M. Sharifhosseini, T. Niknam, M.H. Taabodi, H. Asadi Aghajari, E. Sheybani, G. Javidi, M. Pourbehzadi

Enhanced Resilience in Smart Grids: A Neural Network-Based Detection of Data Integrity Attacks Using Improved War Strategy Optimization

Journal: Electric Power Systems Research (EPSR) (Accepted)

Authors: H. Asadi Aghajari, T. Niknam, S.M. Sharifhosseini, M.H. Taabodi, M. Pourbehzadi

Under Revision

Analyzing Complexities of Integrating Renewable Energy Sources into Smart Grid: A Comprehensive Review

Journal: Applied Energy (Revised)

Authors: H. Asadi Aghajari, T. Niknam, S.M. Sharifhosseini, M.H. Taabodi, E. Sheybani, G. Javidi, M. Pourbehzadi

Submitted Publications

Optimizing Rural Microgrid’s Performance: A Scenario-Based Approach Using the Improved Multi-Objective Crow Search Algorithm Considering Uncertainty

Journal: IEEE Transactions on Smart Grid (Submitted)

Authors: M.H. Taabodi, T. Niknam, S.M. Sharifhosseini, H. Asadi Aghajari, S.M. Bornapour

A Hybrid Crow Search Algorithm and Coalitional Game Theory Approach for Optimal Plug-in Electric Vehicles’ Integration in Networked Microgrids

Journal: IEEE Transactions on Industrial Informatics (Submitted)

Authors: M.H. Taabodi, T. Niknam, S.M. Sharifhosseini, H. Asadi Aghajari

Conclusion

Mr. Seyed Mohammad Sharifhosseini’s suitability for the Research for Best Review Article Award ultimately depends on:

The quality, relevance, and impact of his review articles.

His ability to communicate and disseminate the insights effectively.

His reputation within the academic community as a reviewer or thought leader in his field.

Abdullah Sukkar | Engineering | Best Researcher Award

Published on 24/12/202424/12/2024 by Citation Awards

Mr. Abdullah Sukkar | Engineering | Best Researcher Award

Mr. Abdullah Sukkar, Istanbul Technic University, Turkey

Abdullah Sukkar is a dedicated PhD candidate in Geomatics Engineering at Istanbul Technical University, Turkey, specializing in remote sensing and GIS. With expertise in advanced analytical thinking and problem-solving, he focuses on leveraging technology to address climate change and environmental hazards. Driven by a passion for science and innovation, he aims to develop sustainable solutions and contribute meaningfully to the field of Geomatics Engineering.

Education

Ph.D. in Geomatics Engineering

Institution: Istanbul Technical University, Istanbul, Turkey

Duration: 2022 – Present

Research Area: Drought, Climate Change, Remote Sensing, GIS, Environment

M.Sc. in Geomatics Engineering

Institution: Istanbul Technical University, Istanbul, Turkey

Duration: 2020 – 2022

GPA: 3.75

Thesis Title: Turkey Forest Fire Decision Support System (TFFDSS)

B.Sc. in Geomatics Engineering

Institution: Hacettepe University, Ankara, Turkey

Duration: 2014 – 2019

Honors: Honor Student

Graduation Project: Land Cover Classification Using Satellite Imagery and Deep Learning

Professional Profiles

Scopus Profile

ORCID Profile

Professional Experience

Istanbul Technical University
Geographical Information Technologies Program | Istanbul, Turkey
Teaching Assistant
Feb 2024 – Jun 2024

Facilitated student learning on course topics, GIS software tools (ArcGIS and QGIS), and Python for spatial data analysis and remote sensing applications.

Designed and assessed assignments and projects to reinforce theoretical concepts through practical application.

Provided individualized academic support, ensuring student success in mastering geospatial technologies.

Istanbul Technical University
Geographical Information Technologies Program | Istanbul, Turkey
Teaching Assistant
Sep 2022 – Feb 2023

Guided students in Python programming for GIS applications, including spatial analysis and algorithm development.

Supported project development by reviewing student proposals, advising on algorithm design, and conducting code reviews.

Department of Urban and Regional Planning | Istanbul, Turkey
Teaching Assistant
Nov 2021 – Jun 2022

Designed course materials, prepared syllabi, and aligned teaching objectives with program goals.

Introduced Python, Jupyter Notebooks, and geospatial data visualization techniques to students.

Evaluated student performance through assignments, projects, and exams.

Alya Proje | Ankara, Turkey
Geomatics Engineer
Jul 2019 – Mar 2022

Contributed to 3D modeling projects and photogrammetric mapping processes.

Produced high-resolution digital maps for various applications.

Planned and executed UAV flights to capture geospatial data for mapping and analysis.

Research Interests

Drought Monitoring and Mitigation Strategies

Climate Change Impact Analysis

Remote Sensing Applications in Environmental Monitoring

Geospatial Data Analysis and Visualization

Spatial Analysis of Vegetation Trends Using NDVI

GIS-Based Environmental Planning and Management

Integration of Python in GIS and Remote Sensing

Development of Meteorological Geodatabases

Urban and Regional Planning Using Geospatial Technologies

Research Experience

Research Assistant
Qatar University, Doha, Qatar
Apr 2023 – Jul 2023

Led the preparation of a meteorological geodatabase for Qatar covering the past 40 years, utilizing EAR5 and ERA5-Land datasets.

Applied remote sensing techniques using Google Earth Engine, Python, and QGIS to create NDVI maps, analyzing long-term vegetation trends across Qatar.

Conducted spatiotemporal analysis to explore correlations between climatic conditions and vegetation cover, contributing to the understanding of environmental changes in the region.

Top Notable Publications

Tree Detection from Very High Spatial Resolution RGB Satellite Imagery Using Deep Learning

Authors: Abdullah Sukkar, Mustafa Turker

Year: 2024

Source: Recent Research on Geotechnical Engineering, Remote Sensing, Geophysics, and Earthquake Seismology

DOI: 10.1007/978-3-031-43218-7_34

ISBN: 9783031432170, 9783031432187

ISSN: 2522-8714, 2522-8722

Characterizing the Dynamics of Climate and Native Desert Plants in Qatar

Authors: Meshal Abdullah, Ammar Abulibdeh, Sophia Ghanimeh, Helmi Hamdi, Hezam Al-Awah, Talal Al-Awadhi, Midhun Mohan, Zahraa Al-Ali, Abdullah Sukkar, Ahmed M. El Kenawy

Year: 2024

Journal: Journal of Arid Environments

DOI: 10.1016/j.jaridenv.2024.105274

ISSN: 0140-1963

Investigating the Impacts of Climate Variations and Armed Conflict on Drought and Vegetation Cover in Northeast Syria (2000–2023)

Authors: Abdullah Sukkar, Ammar Abulibdeh, Sara Essoussi, Dursun Zafer Seker

Year: 2024

Journal: Journal of Arid Environments

DOI: 10.1016/j.jaridenv.2024.105278

Investigating Impacts of Climate Change and War on the Green Cover Area in Northeast Syria Between 2000 and 2023

Authors: Abdullah Sukkar, Sara Essoussi, Omar Alqaysi, Enes Hisam, Dursun Zafer Seker

Year: 2024

Preprint DOI: 10.5194/egusphere-egu24-20528

Conceptual Design of a Nationwide Spatial Decision Support System for Forest Fire Prevention and Fighting

Authors: Abdullah Sukkar, Ahmet Ozgur Dogru, Ugur Alganci, Dursun Zafer Seker

Year: 2024

Journal: Applied Geomatics

DOI: 10.1007/s12518-024-00556-9

ISSN: 1866-9298, 1866-928X

The Impacts of Weather Conditions and Topography on Manavgat Wildfire Behavior

Authors: Abdullah Sukkar, Anas Hesham, A. Ozgur Dogru, Dursun Zafer Seker

Year: 2022

Conference: International Symposium on Applied Geoinformatics 2021

DOI: 10.15659/isag2021.12510

Conclusion

Mr. Abdullah Sukkar appears to be a suitable candidate for the “Best Researcher Award,” provided his research aligns with the criteria and he has made significant contributions in his field. His strong academic affiliation and potential for further growth in terms of collaboration, visibility, and interdisciplinary approaches would further enhance his candidacy. If his work has already demonstrated substantial impact through publications and practical applications, he would be well-justified for consideration. However, ensuring continuous improvement in his outreach, interdisciplinary work, and methodological innovations could elevate his standing as a world-class researcher.

Mohammad Waseem | Engineering | Best Researcher Award

Published on 05/12/202417/12/2024 by Citation Awards

Dr. Mohammad Waseem | Engineering | Best Researcher Award

Dr. Mohammad Waseem, Jamia Millia Islamia New Delhi, India

Dr. Mohammad Waseem is an accomplished academic and researcher currently serving as an Assistant Professor in the Faculty of Engineering & Technology at Jamia Millia Islamia (JMI), New Delhi, India. With a strong background in mechanical engineering and extensive experience in both teaching and research, he has contributed significantly to advancing knowledge in battery technologies and energy systems.

Education:

Ph.D. in Electric Vehicle

Specialization: Design and Development of Solar Powered Assisted Hybrid E-Vehicle

Division: I

Percentage: 90%

Institution: Jamia Millia Islamia (JMI), New Delhi, India

M.Tech. in CAD/CAM

Division: I

Percentage: 83%

Institution: Motilal Nehru National Institute of Technology (MNNIT), Allahabad, India

B.Tech. in Mechanical Engineering

Division: I

Percentage: 71.72%

Institution: G.B. Pant Engineering College, Pauri, Uttarakhand, India

Professional Profiles:

ORCID Profile

Professional Experience:

Dr. Waseem has extensive teaching experience in mechanical and energy engineering across multiple institutions. His career spans over seven years, including:

Assistant Professor and Researcher, Faculty of Engineering & Technology, Jamia Millia Islamia, New Delhi (2020–Present):

Teaching and mentoring students in mechanical and energy engineering.

Developing research initiatives and establishing advanced facilities like the Mechatronics Laboratory.

Assistant Professor, Galgotias University, Greater Noida (2019–2020):

Delivered lectures in mechanical engineering with a focus on energy systems and design.

Assistant Professor, Department of Mechanical Engineering, Integral University, Lucknow (2013–2015):

Taught courses on core mechanical engineering subjects and supervised undergraduate projects.

Research Interests:

Dr. Waseem’s research interests are focused on innovative technologies and methodologies in the field of energy systems, particularly those applicable to electric vehicles (EVs). His areas of expertise include:

Battery energy storage systems for EVs.

Simulation and modeling of batteries.

Lithium-ion and solid-state batteries.

Fuel cells.

Battery management systems (BMS) and battery thermal management systems.

Safety concerns in battery design and operation.

Integration of Artificial Intelligence (AI) and Internet of Things (IoT) in BMS.

Charging infrastructure for EVs, including wireless power transfer techniques.

Renewable energy integration with EV systems.

ORGANIZATION OF SEMINARS AND WORKSHOPS

Volunteer, Advances in Robotics international conference, at Department of Mechanical Engg., IIT Delhi. June 28 to July 02, 2017.
Volunteer, International Conference and Exhibition on Building Utilities, at Department of Mechanical Engineering. Faculty of Engg. & Tech. Jamia Millia Islamia, New Delhi-25. Dec. 01- 03, 2016.
Volunteer, National Seminar on Solar Robotics, at Department of Mechanical Engineering. Faculty of Engg. & Tech. Jamia Millia Islamia, New Delhi-25. Oct. 08- 10, 2015.
Faculty Coordinator, Water Rocket Launch and Air Wizard Show, Department of Mechanical Engineering, at Integral University Lucknow on March 16, 2015.

Research & Development Achievements

Dr. Waseem has demonstrated leadership in academic publishing and collaboration:

Editor-in-Chief of the IFR Journal of Engineering and Natural Science, Jordan.

Reviewer for prestigious journals, including Science Direct, Springer, Wiley, IEEE, and IJAME, since 2019.

Editorial Board Member of the International Journal of Transportation Engineering and Technology (2021–2023).

Published research on modeling and analysis, such as the study of a connecting rod for a Pulsar 180CC bike (DOI: 10.1088/2631-8695/ac1727).

Top Notable Publications:

Energy Storage Technology and Electric Vehicles

Next Energy, 2025-01

DOI: 10.1016/j.nxener.2024.100202

Focus: Current progress and future outlook in energy storage and its impact on EVs.

Contributors: Mohammad Waseem, G. Sree Lakshmi, Mumtaz Ahmad, Mohd Suhaib.

Charging Infrastructure in Electric Mobility

Energies, 2024-12-05

DOI: 10.3390/en17236137

Focus: Integrated review of state-of-the-art advancements in charging infrastructure.

Contributors: Mohammad Waseem, Eniganti Sreeshobha, Kotha Shashidhar Reddy, Teresa Donateo.

Electric Vehicle Batteries and Management Techniques

Energy Storage and Saving, 2024-10-15

DOI: 10.1016/j.enss.2024.09.002

Focus: Obstacles, advancements, and recommendations in EV battery technologies.

Contributors: Mohammad Waseem, G. Sree Lakshmi, Sreeshobha Eniganti, Shahbaz Khan.

Wireless EV Charging Circuit Topologies

Green Energy and Intelligent Transportation, 2024-03

DOI: 10.1016/j.geits.2024.100196

Focus: Review of compensation converters in wireless EV charging.

Contributors: Mohammad Amir, Izhar Ahmad, Mohammad Waseem, Mohd Tariq.

Energy Storage System for E-Rickshaws in India

Book Chapter, 2023

DOI: 10.1007/978-981-99-1894-2_40

Focus: Analysis of energy storage solutions for e-rickshaws.

Contributors: Mohammad Waseem, Mumtaz Ahmad, Aasiya Parveen, Mohd Suhaib.

Fuel Cell-based Hybrid Electric Vehicles

Green Energy and Intelligent Transportation, 2023-12

DOI: 10.1016/j.geits.2023.100121

Focus: Current status, challenges, and future prospects of fuel cell hybrid vehicles.

Contributors: Mohammad Waseem, Mohammad Amir, G. Sree Lakshmi, S. Harivardhagini, Mumtaz Ahmad.

Battery Management Systems for EVs

Journal of Power Sources, 2023-10

DOI: 10.1016/j.jpowsour.2023.233349

Focus: Challenges and advancements in battery management systems.

Contributors: Mohammad Waseem, Mumtaz Ahmad, Aasiya Parveen, Mohd Suhaib.

Simscape Modeling for Solar Electric Traction Systems

Transactions of the Indian National Academy of Engineering, 2023-09

DOI: 10.1007/s41403-023-00408-9

Focus: Simulation and analysis of solar-assisted electric traction systems.

Contributors: Mohammad Waseem, Mumtaz Ahmad, Mohd. Suhaib.

Renewable Solar Energy with Autonomous Vehicles

Lecture Notes in Civil Engineering, 2020

DOI: 10.1007/978-981-15-2545-2_13

Focus: Review of solar energy applications in autonomous vehicles.

Contributors: Waseem, M., Sherwani, A.F., Suhaib, M.

Integration of Solar Energy in Vehicles

SN Applied Sciences, 2019-11

DOI: 10.1007/s42452-019-1458-4

Focus: Technological advancements in solar energy integration for EVs.

Contributors: Mohammad Waseem, Ahmad Faizan Sherwani, Mohd Suhaib.

Conclusion:

Dr. Mohammad Waseem has an exemplary record of research and publications, making him a strong contender for the Research for Best Researcher Award. His work in energy storage, electric vehicles, and renewable energy aligns with critical global challenges, demonstrating both academic rigor and societal relevance. While he could enhance his profile by improving citation metrics, securing major grants, and assuming leadership roles in international research collaborations, his current achievements already position him as a distinguished researcher in his field.

Vasileios Laitsos | Engineering | Best Review Article Award

Published on 02/12/202402/12/2024 by Citation Awards

Mr. Vasileios Laitsos | Engineering | Best Review Article Award

Mr. Vasileios Laitsos, University of Thessaly, Greece

Mr. Vasileios Laitsos is an accomplished researcher and electrical engineer from Greece, currently pursuing a PhD at the University of Thessaly, Department of Electrical and Computer Engineering, Volos. His research focuses on developing innovative forecasting models for electricity demand and wholesale electricity prices using artificial intelligence, particularly leveraging Python and the TensorFlow platform.

Education:

PhD in Electrical and Computer Engineering (July 2020 – Present)
University of Thessaly, Volos
Research Focus: AI-driven forecasting models for electricity demand and pricing.

Master’s in Smart Grid Energy Systems (October 2019 – February 2021)
University of Thessaly, Volos
Graduated as Valedictorian with a GPA of 9.63/10.
Thesis: “The Modern Power System from a Different Approach: Impact of Demand Side Management Methods.”

Diploma in Electrical and Computer Engineering (October 2011 – June 2017)
Aristotle University of Thessaloniki, Thessaloniki
GPA: 7.43/10.
Thesis: “Wind Power Forecasting using Support Vector Machines and Artificial Neural Networks.”

Professional Profiles:

ORCID Profile

Professional Experience:

Mr. Laitsos has a diverse professional background, with extensive experience in both research and industry. He currently serves as a Research Associate at HEDNO S.A. in Volos, where he contributes to European Union scientific programs such as ENFLATE and CENTAVROS, which focus on optimizing energy distribution systems. Concurrently, he is a Machine Learning Researcher for the ELVIS Research Project, working on developing a prototype integrated tool for managing the smart charging of electric vehicles by an EV Aggregator.

Previously, Mr. Laitsos served as a Technical Manager at Hellenic Dairies S.A., overseeing the electrical and electronic maintenance of the packaging department, leading a team of seven technicians, and managing two major projects. His earlier roles include Electrical Maintenance Engineer at Hellenic Halyvourgia S.A., where he gained hands-on experience with electrical circuits, AC/DC motors, and PLC systems, and an Electrical Engineer Internship at VIS S.A., where he familiarized himself with industrial electrical panels and machinery.

Skills and Achievements:

Mr. Laitsos possesses a comprehensive skill set, including expertise in machine learning, Python programming, TensorFlow, electrical circuit design, PLC systems, and energy system optimization. His leadership skills, team management experience, and ability to bridge the gap between theoretical research and practical implementation have been instrumental in his career. He is fluent in English and Greek and holds a valid driving license.

Publications:

1. The State of the Art Electricity Load and Price Forecasting for the Modern Wholesale Electricity Market

Journal: Energies

Publication Date: November 2024

DOI: 10.3390/en17225797

Contributors: Vasileios Laitsos, Georgios Vontzos, Paschalis Paraschoudis, Eleftherios Tsampasis, Dimitrios Bargiotas, Lefteri Tsoukalas

Source: Multidisciplinary Digital Publishing Institute

2. Enhanced Sequence-to-Sequence Deep Transfer Learning for Day-Ahead Electricity Load Forecasting

Journal: Electronics

Publication Date: May 2024

DOI: 10.3390/electronics13101996

Contributors: Vasileios Laitsos, Georgios Vontzos, Apostolos Tsiovoulos, Dimitrios Bargiotas, Lefteri Tsoukalas

Source: Multidisciplinary Digital Publishing Institute

3. Estimating Spatio-Temporal Building Power Consumption Based on Graph Convolution Network Method

Journal: Dynamics

Publication Date: May 2024

DOI: 10.3390/dynamics4020020

Contributors: Georgios Vontzos, Vasileios Laitsos, Avraam Charakopoulos, Dimitrios Bargiotas, Theodoros Karakasidis

Source: Multidisciplinary Digital Publishing Institute

4. State-of-the-Art of Electricity Load and Price Forecasting for the Modern Wholesale Electricity Market

Type: Working Paper

DOI: 10.20944/preprints202411.0165.v1

Source: Multidisciplinary Digital Publishing Institute

Conclusion:

Mr. Vasileios Laitsos is a highly promising researcher with significant contributions to the field of electricity load and price forecasting. His review article in Energies demonstrates a deep understanding of the subject and provides valuable insights for advancing the state of the art in energy forecasting. With minor improvements in scope and quantitative analysis, Mr. Laitsos’s work has the potential to be a benchmark for future research in the field. Given his multidisciplinary expertise, collaborative spirit, and impactful research, he is a strong candidate for the Best Review Article Award. Recognizing his work would not only honor his individual achievements but also encourage further advancements in energy forecasting and smart grid technologies.