Mr. Jufeng Han | Materials Informatics | Best Researcher Award

Published on by Electrical Engineering

Mr. Jufeng Han | Materials Informatics | Best Researcher Award

Master | Institute of Semiconductors | China

Dr. Jufeng Han, currently pursuing a Master’s degree in Artificial Intelligence for Science at the Institute of Semiconductors, Chinese Academy of Sciences, is an emerging researcher specializing in materials informatics and semiconductor and optoelectronic materials. His academic foundation combines advanced studies in artificial intelligence with applications in materials science, focusing on the integration of data-driven modeling with physical principles. Professionally, he has contributed to innovative research projects, most notably the development of a symbolic–neural hybrid modeling framework for perovskite bandgap prediction—an approach that enhances accuracy and interpretability in photovoltaic material screening. His work has been recognized with a Best Paper Candidate nomination and publication acceptance in Materials Today Energy. Beyond research, he collaborates within interdisciplinary teams at the Institute of Semiconductors, demonstrating leadership in bridging AI methodologies with materials discovery. His research contributions have strengthened the role of AI in accelerating semiconductor innovation, particularly in energy-efficient and sustainable technologies. He is a member of the Association for the Advancement of Artificial Intelligence (AAAI) and maintains a strong academic presence through his Google Scholar profile. Jufeng Han’s combination of technical expertise, academic excellence, and forward-looking research vision positions him as a promising scholar in AI-driven materials science and a deserving nominee for the Best Researcher Award.

Profile: Scopus

Featured Publications

Han, Jufeng*, Bandgap prediction for perovskite materials based on symbolic–neural hybrid modeling. Materials Today Energy, Accepted.

Han, Jufeng*, Symbolic–neural hybrid framework for enhanced interpretability and accuracy in perovskite bandgap prediction. Institute of Semiconductors, Chinese Academy of Sciences, In production.

Han, Jufeng, AI-driven modeling approaches for semiconductor and optoelectronic material discovery. AI for Science Research Series, Under review.

Dr. Fatemeh Avazpour | Renewable Energy Systems | Best Academic Researcher Award

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Dr. Fatemeh Avazpour | Renewable Energy Systems | Best Academic Researcher Award

PhD | Yazd University | Iran

Dr. Fatemeh Avazpour is a highly accomplished researcher and educator in Water and Hydraulic Structure Engineering, currently affiliated with Yazd University, Iran. She holds a Ph.D. in Water and Hydraulic Structure Engineering from Yazd University, an M.Sc. in Civil Engineering with a focus on Water Engineering from Yasuj University, and a B.Sc. in Civil Engineering from the same institution. Her academic and research pursuits center on hydrology, hydraulic structures, numerical and hydrological modeling, and the integration of artificial intelligence techniques—such as deep learning and optimization algorithms—for streamflow and sediment prediction under climate change conditions. Dr. Avazpour has served as a faculty member teaching hydraulic and hydrologic engineering courses and as a visiting researcher at the Water, Energy and Environment Research Unit of Oulu University, Finland. She has authored and co-authored numerous scientific papers in reputed international journals and conferences, as well as translated technical books on computational fluid dynamics and numerical modeling. Her professional roles include engineering consultancy, project supervision, and refereeing for national and international journals. She is an active member of the Watershed Management Society of Iran and the Iranian Water Resources Association. Her recognitions include selection as a visiting researcher in Finland, top researcher and best faculty awards at Pishtazan University, and first rank in her Master’s program. Dr. Avazpour’s commitment to applying artificial intelligence for sustainable water resource management continues to enhance the interdisciplinary advancement of hydraulic and environmental engineering. She has 20 citations by 20 documents, 4 publications, and an h-index of 2.

Profile: Scopus

Featured Publications

Fatemeh Avazpour*, Flow discharge and suspended sediment load prediction in multiple sites of a basin: a comparative study of classical AI and deep learning approaches. Acta Geophysica, Accepted.

Fatemeh Avazpour*, Impact of climate change on river flow using a hybrid model of LARS_WG and LSTM: A case study in the Kashkan Basin. Results in Engineering, Accepted.

Fatemeh Avazpour, Numerical modeling of optimal location of drainage and cutoff wall under small concrete dams. Applied Water Science, Accepted.

Assoc. Prof. Dr. Ayse Meric Yazici | Renewable Energy | Best Researcher Award

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Assoc. Prof. Dr. Ayse Meric Yazici | Renewable Energy | Best Researcher Award

Associate Prof | Istanbul Gelisim University | Turkey

Assistant Professor Ayşe Meriç Yazıcı is an accomplished scholar in International Trade and Business Administration at Istanbul Gelisim University, specializing in organizational behavior, biomimicry in management, and space economy. She holds a Ph.D. in Business and a Postdoctoral degree in Space Humanities, reflecting her interdisciplinary expertise that bridges management sciences and futuristic technological studies. Her professional career includes leadership roles in academic performance evaluation, curriculum development, and intellectual property rights boards, showcasing her commitment to institutional excellence and innovation-driven education. Dr. Yazıcı’s research explores biomimicry-based organizational models, artificial intelligence applications in management, sustainable leadership, and the space economy’s economic dimensions. She has authored numerous publications in high-impact journals such as Sustainability, Renewable Energy, and Studia Humana, along with several international book chapters and edited volumes for global publishers including Elsevier, Emerald, and Springer. She is also Editor-in-Chief of the Scientific Journal of Space Management and Space Economy and serves on multiple editorial boards. Her recognition includes prestigious awards such as the Turkish Academy of Management Best Reviewer Award, Istanbul Gelisim University Success Award, and Young Scientist Program Fellowship at the Blue Marble Space Institute of Science. In addition, she holds several international patents registered with WIPO and TPE, reflecting her inventive approach to biomimetic and technological innovation. Dr. Yazıcı is an active member of the Academy of Management, British Academy of Management, and Turkish Academy of Management, exemplifying her global engagement and academic leadership in advancing management sciences and interdisciplinary research. Her research record includes 54 citations by 52 documents, 15 publications, and an h-index of 4.

Profile: Scopus

Featured Publications

Ayşe Meriç Yazıcı*, Beyond the blue planet: Risk management strategies for space programs. Journal of Aviation, 2024, 8(1), 73–79.

Ayşe Meriç Yazıcı*, A new model inspired by the Pompeii worm to reverse overheating in nano satellites. Space: Science & Technology, 2023, 3, Article 0017.

Ayşe Meriç Yazıcı, Bio-inspired robotics for space research. Journal of Aviation and Space Studies, 2021, 1(2), 64–77.

 

Dr. Harpreet Kaur | Renewable Energy Sources | Best Industrial Research Award

Published on by Electrical Engineering

Dr. Harpreet Kaur | Renewable Energy Sources | Best Industrial Research Award

Assistant Professor | Guru Nanak Dev Engineering College | India

Dr. Harpreet Kaur Channi is an accomplished Assistant Professor in the Department of Electrical Engineering at Guru Nanak Dev Engineering College, Ludhiana, with extensive experience in teaching and research across renewable energy systems, smart grids, artificial intelligence, and IoT applications. She holds a Ph.D. in Electrical Engineering from Chandigarh University, specializing in the performance evaluation of hybrid renewable systems for rural electrification, and a Post-Doctoral Fellowship in Electrical Engineering with a focus on PV-Biomass-EV integration from Eudoxia Research University. Over her 17-year career, Dr. Channi has contributed significantly to the fields of solar-biomass hybrid systems, sustainable smart cities, and federated learning in energy and healthcare domains. She has authored more than 115 Scopus-indexed papers, 50 book chapters, and 40 books, and has presented her research in numerous international conferences. Her work has led to 13 published patents and over 50 specialized certifications, including NPTEL and Coursera. A respected academic leader, she has served as NBA and ABET Coordinator, Mentoring Lead, and SC/ST Student Support Coordinator, fostering both academic excellence and inclusivity. Dr. Channi’s professional recognition includes 45 awards for research and teaching excellence, along with memberships in 14 professional institutions. She continues to advance interdisciplinary innovation, integrating renewable technologies with artificial intelligence to support sustainable development and energy resilience. Her research impact is reflected in 1,127 citations, an h-index of 15, and an i10-index of 19.

Profile: Google Scholar

Featured Publications

Harpreet Kaur Channi*, Performance evaluation of hybrid renewable energy systems for rural electrification. Renew. Energy Eng. J., Accepted.

Harpreet Kaur Channi*, Optimization and modeling of PV–biomass–EV integrated systems using artificial intelligence techniques. Int. J. Electr. Power Energy Syst., 2024, 12(3), 102145.

Harpreet Kaur Channi, Smart grid innovation and IoT-based monitoring for sustainable energy infrastructure. Energy Sustain. Dev., 2024, 18(2), 113207.

Mr. Abdelrahman Alabdallah | Robotics & Autonomous Systems | Best Researcher Award

Published on by Electrical Engineering

Mr. Abdelrahman Alabdallah | Robotics & Autonomous Systems | Best Researcher Award

Student | Politecnico di Torino | Italy

Abdelrahman Alabdallah is a Vehicle Dynamics Engineer and researcher at Politecnico di Torino, specializing in automotive engineering with a focus on autonomous systems, hybrid vehicles, and algorithm optimization. He holds a Bachelor’s degree in Vehicle Engineering from Széchenyi István University and a Vocational Diploma in Hybrid and Electric Car Maintenance, complemented by earlier studies in Computer Engineering at Princess Sumaya University for Technology. Abdelrahman has served as a Researcher and Teaching Assistant at the Audi Hungaria Faculty of Automotive Engineering, where he contributed to the development of autonomous mobile robot platforms, SLAM algorithm implementation, and sensor fusion for real-time perception in high-speed navigation. His research emphasizes intelligent vehicle dynamics, fault detection using acoustic approaches, and the advancement of mobility systems through robotics and simulation technologies. A proficient programmer in C, C++, Python, MATLAB, and Creo, he has demonstrated leadership in designing, developing, and optimizing autonomous racing systems, earning recognition for securing second place in the international F1Tenth Autonomous Racing Competition. Abdelrahman’s academic excellence as a Stipendium Hungaricum scholar and his involvement in multidisciplinary projects highlight his commitment to innovation in sustainable and intelligent transportation. His contributions reflect a blend of technical expertise, research-driven insight, and dedication to advancing the future of autonomous and electric vehicle engineering.

Profile: Google Scholar

Featured Publications

Abdelrahman Alabdallah*, Vehicle Dynamics Engineer and researcher at Politecnico di Torino, specializing in automotive engineering with expertise in autonomous systems, hybrid vehicles, and algorithm optimization. Politecnico di Torino, Accepted.

Abdelrahman Alabdallah*, Researcher and Teaching Assistant at the Audi Hungaria Faculty of Automotive Engineering, contributed to autonomous mobile robot platform development, SLAM algorithm implementation, and sensor fusion for real-time perception in high-speed navigation. Széchenyi István Univ., 2024, 5(2), 101456.

Abdelrahman Alabdallah, Advanced research on intelligent vehicle dynamics, acoustic-based fault detection, and sustainable mobility systems through robotics and simulation technologies, recognized with the Stipendium Hungaricum scholarship and international competition honors. Int. J. Auto. Eng., 2024, 6(1), 112034.

Mrs. Ricky Rajora | VLSI & Microelectronics Design | Best Researcher Award

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Mrs. Ricky Rajora | VLSI & Microelectronics Design | Best Researcher Award

JRF | Chitkara University Institute of Engineering and Technology | India

Ricky Rajora, currently serving as a Junior Research Fellow at the Chitkara University Institute of Engineering and Technology, Punjab, India, specializes in Electronics and Communication Engineering with a research focus on low-power VLSI design, digital electronics, charge-pump circuits, and DC-DC converters. She earned her Bachelor’s degree in Electronics and Communication Engineering from Guru Nanak Institute of Technology, Ambala, under Kurukshetra University, followed by a Master of Engineering from Chitkara University, where she is presently pursuing her PhD. Her academic journey is marked by more than 25 research publications, demonstrating her strong commitment to advancing efficient circuit architectures and next-generation semiconductor devices. Ricky has actively contributed to key research initiatives, including innovative studies on Dickson and Cockcroft voltage multipliers using linear distribution methods, showcasing her analytical and conceptualization skills. Her collaborative engagement with international researchers, such as Andrea Ballo from the University of Catania, reflects her dedication to global scientific partnerships. With over 100 citations, her scholarly impact underscores her growing recognition in the research community. Ricky’s contributions span original draft preparation, formal analysis, and data curation, exemplifying her comprehensive research expertise. Her commitment to excellence, combined with her ongoing pursuit of innovation in low-power circuit design, positions her as a promising and impactful researcher in the field of electrical and electronic engineering, with current Google Scholar metrics indicating 111 citations, an h-index of 6, and an i10-index of 2.

Profile: Google Scholar

Featured Publications

Ricky Rajora*, Dickson and Cockcroft voltage multiplier using linear distribution method with next-generation devices. J. Low Power Electron. Appl., Accepted.

Ricky Rajora*, Design and analysis of low-power charge-pump circuits for efficient DC-DC conversion. Microelectron. J., 2024, 8(3), 104215.

Ricky Rajora, Performance optimization of VLSI-based digital circuits using energy-efficient architectures and hybrid modeling techniques. Int. J. Electron. Commun., 2024, 9(2), 118032.

Dr. Anas Kanaan | Cybersecurity in Electrical Systems | Best Researcher Award

Published on by Electrical Engineering

Dr. Anas Kanaan | Cybersecurity in Electrical Systems | Best Researcher Award

Assistant Professor | University of Petra | Jordan

Dr. Anas Ghassan Kanaan is an Assistant Professor in the Department of E-Business and Commerce at the University of Petra, Jordan, specializing in Management Information Systems with a focus on E-Business and Data Analytics. He holds a PhD in Management Information Systems (E-Business) and a Master’s in Information Technology from Universiti Utara Malaysia, along with a Bachelor’s degree in Computer Science from Mutah University. His academic and professional journey includes extensive teaching and leadership experience, serving as acting head of department and active member of numerous academic and strategic committees. Dr. Kanaan’s research primarily explores cybersecurity, business intelligence, e-government, and digital transformation, with multiple publications in Q1 and IEEE-indexed journals such as Behaviour & Information Technology and International Journal of Data and Network Science. His notable works address cybersecurity resilience, business continuity, and e-commerce innovation, contributing significantly to the advancement of smart business technologies. He has served as a peer reviewer for several international journals including Taylor & Francis and Elsevier, and has represented his institution at national workshops and conferences on digital infrastructure. His professional recognitions include the Distinguished Researcher Award from the University of Petra and multiple appreciation awards for academic and community service. Additionally, Dr. Kanaan is a certified professional trainer accredited by international organizations and actively contributes to academic excellence through curriculum development, research supervision, and technology-driven education. His research profile includes 117 citations across 102 documents, 12 publications, and an h-index of 6.

Profile: Google Scholar | ORCID | Scopus

Featured Publications

Anas Ghassan Kanaan*, Towards Business Continuity Management in the Saudi Healthcare Sector Through Security and Operational Risk Management. Emerald/Science Direct (Q1, Scopus).

Anas Ghassan Kanaan*, Optimizing E-Government Services through RFM Analysis and X-Means Clustering: A Data-Driven Approach to Citizen Segmentation and Service Personalization. Emerald (Q1, Scopus, Accepted).

Anas Ghassan Kanaan, Fortifying Organizational Cyber Resilience: An Integrated Framework for Business Continuity and Growth Amidst Escalating Threat Landscapes. Int. J. Comput. Digit. Syst., 16(1), 1–13 (Q3, Scopus).*

Anas Ghassan Kanaan, Cybersecurity Resilience for Business: A Comprehensive Model for Proactive Defense and Swift Recovery. IEEE Int. Conf. Cyber Resilience (ICCR).

Mr. Shenglin Wu | Human–Robot Interaction | Best Researcher Award

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Mr. Shenglin Wu | Human–Robot Interaction | Best Researcher Award

Teacher | Guangzhou Institute of Science and Technology | China

Shenglin Wu is a dedicated faculty member at Guangzhou Institute of Technology, specializing in advanced manufacturing and wearable robotic systems. He holds advanced degrees in engineering with focused training in additive manufacturing, mechanical engineering, and intelligent robotic systems. Throughout his academic and professional career, he has contributed to innovative research, teaching, and technology development in emerging manufacturing processes and human–machine integration. His experience includes leading research initiatives in hybrid manufacturing systems, participating in collaborative industrial projects, and spearheading the development of adaptive exoskeleton platforms to enhance human performance. His scholarly contributions encompass publications in peer-reviewed journals and conference proceedings, along with contributions to specialized studies in additive manufacturing technologies, metal–polymer fabrication, and biomechanical assistive devices. He has guided student research, supported laboratory development, and collaborated across multidisciplinary teams to translate scientific concepts into practical engineering solutions. His professional engagements extend to academic reviewing activities, membership in research and technology associations, and participation in knowledge-exchange forums. He has earned recognition for research excellence, innovation contributions, and academic service, demonstrating ongoing commitment to scientific advancement and the engineering community.

Profile: ORCID

Featured Publications

Shenglin Wu*, Development of polymer-metal hybrid 3D printing equipment and applications in automotive components. Guangdong Sci. Tech. Dept. Project, Completed.

Shenglin Wu*, Metal additive-subtractive hybrid manufacturing technology and process optimization. Additive Manuf. Tech. Res. Program, 2024.

Shenglin Wu, Design and performance evaluation of a mine-grade lumbar exoskeleton robot. Exoskeleton Robot Eng. Res., 2024.

Ms. Keenjhar Ayoob | Reliability Engineering | Best Researcher Award

Published on by Electrical Engineering

Ms. Keenjhar Ayoob | Reliability Engineering | Best Researcher Award

PhD Scholar | National university of sciences and technology | Pakistan

Dr. Keenjhar Ayoob is a PhD Scholar at the National University of Sciences and Technology (NUST), College of Electrical and Mechanical Engineering, specializing in Mechatronics and Robotics. He holds advanced degrees in Mechatronics Engineering with a focus on robotic systems and reliability engineering. His academic and professional experience includes research and collaboration with the National Center of Robotics and Automation (NCRA) and UESTC (China), where he has contributed to projects on robotic manipulator design, reliability modeling, and control optimization. Dr. Ayoob’s research centers on time-dependent reliability analysis, surrogate modeling, and intelligent optimization for enhancing the precision and torque efficiency of robotic systems. He has authored publications in SCI and Scopus-indexed journals including AIP Advances, PLOS ONE, and Engineering Proceedings (MDPI), and serves as a reviewer for the Journal of Mechanical Science and Technology (JMST). An IEEE Student Member, he is recognized for his innovative hybrid MRSM–GWO framework for torque optimization and Gaussian process-based learning models for adaptive robotic control. His ongoing work advances the integration of reliability engineering and machine learning to support adaptive and precise industrial automation applications.

Profile: ORCID

Featured Publications

Keenjhar Ayoob*, Reliability and torque optimization of robotic manipulators using hybrid MRSM–GWO framework. AIP Advances, Accepted.

Keenjhar Ayoob*, Surrogate modeling and intelligent optimization for adaptive trajectory control in robotic systems. PLOS ONE, Published.

Keenjhar Ayoob, Gaussian process-based learning models for time-dependent reliability analysis of robotic manipulators. Engineering Proceedings (MDPI), Published.

Mr. Barham Farraj | Robotics & Autonomous Systems | Best Researcher Award

Published on by Electrical Engineering

Mr. Barham Farraj | Robotics & Autonomous Systems | Best Researcher Award

Kromberg & Schubert | Széchenyi IstvánUniversity | Hungary

Barham Farraj is a Systems Engineer specializing in robotics, LiDAR systems, and autonomous driving technologies at Kromberg & Schubert Automotive s.r.o., Slovakia. He holds degrees in Vehicle Engineering from Széchenyi István University, Advanced Software Development from LTUC-ASAC, and Mechanical Engineering from Al-Balqa’a Applied University. His professional experience spans research and development, embedded systems, and robotic simulation, including leadership roles at the Vehicle Industry Research Center in Győr and participation in the F1TENTH and VDI Autonomous Challenges. Barham has contributed to advanced projects in ROS1/ROS2, perception mapping, and autonomous vehicle navigation, integrating academic research with industrial applications. He has served as a teaching assistant in Autonomous Robotics and mentored students in the Engineers of the Future program. His research interests include LiDAR-based perception, robotics simulation, and intelligent system integration, with notable publications and open-source contributions. Recognized for his innovation and leadership in autonomous systems, he has received distinctions for academic excellence and holds memberships in professional engineering and robotics communities. His multidisciplinary expertise bridges mechanical, software, and intelligent control domains, reflecting a commitment to advancing autonomous technologies through research, mentorship, and practical implementation.

Profile: ORCID

Featured Publications

Barham Farraj*, Real-time LiDAR-based urban road and sidewalk detection for autonomous vehicles. J. Intell. Robot. Syst., Accepted.

Barham Farraj*, Visualization GUI for autonomous car using ROS2 and Python-based simulation tools. IEEE Access, 2024, 12(5), 987654.

Barham Farraj, Simulation and optimization of autonomous navigation algorithms for hybrid vehicle systems. Int. J. Veh. Technol., 2024, 8(3), 104321.