Diego Zarie | Renewable Energy | Young Researcher Award

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Mr. Diego Zarie | Renewable Energy | Young Researcher Award

Junior Researcher, University of Cuenca, United States

Mr. Diego Zarie is a dedicated Electrical Engineering student at the University of Cuenca, Ecuador (2019–2025), specializing in Control and Automation with a strong academic foundation that also includes studies in Power Systems at the Universidad Autónoma de Ciudad Juárez, Mexico (2024) and early technical training at Unidad Educativa Técnico Salesiano, Cuenca (2012). Professionally, he has served as Project Manager at M.O. Construcciones (2023–2025), where he has been responsible for designing, planning and executing residential, commercial and industrial electrical projects, including the successful implementation of the ISO 50001 energy efficiency standard in residential construction. His research interests lie in renewable energy, energy efficiency, power systems and automation, with a focus on integrating sustainable practices into engineering solutions. Skilled in project management, system control, and programming across Assembly, C, C++,and ML, Mr. Diego Zarie combines technical expertise with leadership and organizational abilities. He has also demonstrated strong community engagement as an international volunteer in Teresina, Brazil, contributing to UN Sustainable Development Goal 4 on quality education. Recipient of recognition for his early contributions, including one indexed publication, he shows great promise as a young researcher. In conclusion, Mr. Diego Zarie exemplifies academic excellence, professional competence, and social responsibility, making him a deserving candidate for recognition.

Profile: ORCID

Featured Publications

Arévalo-Cordero, P., González, F., Martínez, A., Zarie, D., Rodas, A., Albornoz, E., Ochoa-Correa, D., & Benavides, D. (2025). Hybrid LSTM–FACTS control strategy for voltage and frequency stability in EV-penetrated microgrids. Technologies, 13(9), 402.

 

Samee Ullah Khan | Energy Informatics | Best Researcher Award

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Dr. Samee Ullah Khan | Energy Informatics | Best Researcher Award

Postdoctoral Fellow at Khalifa University, Abu Dahbi, UAE, Aerospace Research and Innovation Center, United Arab Emirates.

Dr. Samee Ullah Khan is a Postdoctoral Fellow and Co-Supervisor at the ARIC Center, Khalifa University, UAE. With extensive academic and research experience across South Korea, UAE, and Pakistan, he specializes in AI-driven solutions for smart surveillance, industrial automation, energy informatics, and computer vision. His interdisciplinary work spans collaborations with global research teams, contributing to high-impact publications and real-time applications in intelligent systems and deep learning.

Professional Profile 

Scopus Profile

Orcid Profile

Google Scholar Profile

Education 🎓📚

  • Ph.D. in Software Engineering
    Sejong University, Seoul, South Korea (2019–2023)
    CGPA: 4.44/4.5
    Dissertation: Discriminative Feature Analysis for Person Re-Identification Using Deep Learning

  • Master’s in Computer Science
    Islamia College Peshawar, Pakistan (2016–2019)
    CGPA: 3.33/4.0
    Dissertation: Efficient Computational Model for Automatic Detection and Classification of DNA Proteins

Professional Experience 🧑‍🏫💼

  • Postdoctoral Fellow, Khalifa University (April 2024–Present)
    AI-based industrial solutions, carbon fiber defect detection

  • Postdoctoral Fellow, Kyungpook National University, South Korea (Sep 2023–Mar 2024)

  • Co-Supervisor, PhD Candidates – Khalifa University (Jan 2025–Present)

  • Lab Coordinator, Intelligent Media Lab, Sejong University (2022–2023)

  • Research Assistant, Sejong University (2019–2022)

  • Research Assistant, Islamia College Peshawar (2016–2019)

Research Interest 🔬📈

  • Deep Learning for Surveillance & Re-Identification

  • AI for Smart Manufacturing and Carbon Fiber Defect Detection

  • Energy Consumption Forecasting and XAI

  • Active Learning, Data Augmentation

  • Computer Vision for Smart Cities

Awards & Recognition

  • Best Researcher Award – Sejong University (2023)

  • Best Paper Award – Korea Next Generation Computing Conference (2023)

  • Best Poster Award – 6th Int’l Conf. on Next Generation Computing (2023)

  • Fully Funded PhD Scholarships (2016, 2019)

Author Metrics

  • Total Citations (Top Publications): 285+

  • Top Journals: Sensors, Expert Systems with Applications, Mathematics, Multimedia Tools and Applications

  • Roles: Lead author on deep learning, smart energy, and Re-ID systems

Publications Top Note 📝

  1. “Towards efficient building designing: Heating and cooling load prediction via multi-output model”
    Sensors, 2020 – Cited by 63

  2. “Deep multi-scale pyramidal features network for supervised video summarization”
    Expert Systems with Applications, 2024 – Cited by 60

  3. “Sequential learning-based energy consumption prediction for residential/commercial sectors”
    Mathematics, 2021 – Cited by 58

  4. “AB-net: Deep learning framework for renewable energy forecasting”
    Mathematics, 2021 – Cited by 54

  5. “Deep-ReID: Autoencoder-assisted image patching for smart city surveillance”
    Multimedia Tools and Applications, 2024 – Cited by 50

Conclusion 🌟🎯

Dr. Samee Ullah Khan is highly suitable for the Best Researcher Award in Energy Informatics. His innovative, interdisciplinary, and internationally recognized contributions, particularly in energy forecasting, AI-driven defect detection, and smart city applications, establish him as a leading figure in next-generation energy systems research.

Xiaoming Zhang | Integrated Energy System | Best Researcher Award

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Dr. Xiaoming Zhang | Integrated Energy System | Best Researcher Award

Lecturer at Inner Mongolia University Of Science and Technology, China.

Dr. Xiaoming Zhang is a researcher in the field of thermal and renewable energy systems. He obtained his Ph.D. from Beijing University of Technology, specializing in Power Engineering and Engineering Thermophysics. With a multidisciplinary background and academic appointments, his work integrates experimental analysis, system modeling, and advanced optimization methods including AI-driven tools for improving energy system efficiency and sustainability. He has contributed to over 10 academic papers and co-authored 2 monographs in his field.

Professional Profile 

Scopus Profile

Education 🎓📚

  • B.Eng. in Thermal Energy and Power Engineering, Inner Mongolia University of Science and Technology, China (2004–2008)

  • M.Eng. in Power Engineering, Inner Mongolia University of Technology, China (2012–2015)

  • Ph.D. in Power Engineering and Engineering Thermophysics, Beijing University of Technology, China (2015–2020)

Professional Experience 🧑‍🏫💼

Dr. Xiaoming Zhang currently serves as a faculty member at the School of Information Engineering, Inner Mongolia University of Science and Technology, where he has been engaged in teaching and scientific research since July 2020. Over the past years, he has actively contributed to the advancement of new energy systems and thermal engineering. Dr. Zhang has successfully led multiple research projects, including one funded by the Inner Mongolia Natural Science Fund, one provincial and ministerial-level talent project, and one enterprise-collaborated horizontal project.

Research Interest 🔬📈

  • New energy development and utilization

  • Integrated energy system planning and optimization

  • Thermal energy storage using molten salt technology

  • Organic Rankine Cycle (ORC) systems

  • Application of machine learning in energy systems

  • Solar thermal power systems

Publications Top Note 📝

1. Zhang X., Ding C., Liang G., Yang P., Wang X.

Title: Research on integrated energy system planning based on the correlation between wind power and photovoltaic output
Journal: IET Renewable Power Generation
Year: 2024
Pages: 1–12
Highlights:

  • Investigates coordinated planning methods for integrated energy systems

  • Focuses on wind-PV output correlation to enhance energy system efficiency

2. Zhang X. M., Zhang C. C., Wu Y. T., Lu Y. W.

Title: Experimental research of high temperature dynamic corrosion characteristic of stainless steels in nitrate eutectic molten salt
Journal: Solar Energy
Volume: 209
Year: 2020
Pages: 618–627
Highlights:

  • Examines corrosion behavior of stainless steel in high-temperature molten salt

  • Provides experimental data for thermal energy storage design

3. Zhang X. M., Wu Y. T., Ma C. F., et al.

Title: Experimental Study on Temperature Distribution and Heat Losses of a Molten Salt Heat Storage Tank
Journal: Energies
Volume: 12(10)
Year: 2019
Article ID: 1943
Highlights:

  • Focus on thermal analysis of heat storage tanks using molten salt

  • Supports optimization of thermal storage in solar power plants

4. Zhang Xiaoming, Wu Yuting

Title: Energy and General Analysis of Trough Solar Thermal Power System
Journal: Journal of Solar Energy
Volume: 42(12)
Year: 2021
Pages: 9–16
Highlights:

  • Provides modeling and efficiency analysis of trough solar thermal systems

  • Useful for improving solar thermal plant design

5. Zhang Xiaoming, Wu Yuting, et al.

Title: Structure Design, Temperature Distribution and Stress Analysis of Large Molten Salt Tank
Journal: Journal of Beijing University of Technology
Volume: 47(9)
Year: 2021
Pages: 1064–1073
Highlights:

  • Covers mechanical stress and heat behavior in large-scale energy storage tanks

  • Combines finite element analysis with experimental validation

Conclusion 🌟🎯

Dr. Xiaoming Zhang is an outstanding candidate for the Research for Best Researcher Award, particularly in the field of Integrated Energy Systems. His research aligns with urgent global priorities—clean energy transition, system resilience, and optimization through AI. With high-quality publications, solid project leadership, and impactful research contributions, Dr. Zhang demonstrates the excellence and forward-thinking innovation the award intends to recognize.

Prof. Tian Tian | Renewable Energy | Best Researcher Award

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Prof. Tian Tian | Renewable Energy | Best Researcher Award

Prof. Tian Tian, Yangzhou University, China

Dr. Teng Huang is a distinguished researcher at Guangzhou University, China, specializing in Blockchain, Smart Contracts, and AI-driven Medical Image Segmentation. His work integrates Comprehensive Transformer Integration Networks (CTIN) to enhance medical diagnostics. With numerous high-impact publications in IEEE and other top journals, Dr. Teng Huang has contributed significantly to breast lesion detection, brain tumor segmentation, and privacy-preserving AI. His expertise extends to remote sensing, recommendation systems, and adversarial learning. Dr. Teng Huang’s innovative research bridges healthcare, AI, and blockchain, establishing him as a leader in computational intelligence and medical AI applications.

🌍 Professional Profile:

Orcid

🏆 Suitability for Best Researcher Award 

Dr. Teng Huang’s groundbreaking contributions in medical imaging, blockchain security, and AI-driven diagnostics make him a strong candidate for the Best Researcher Award. His work on transformer-based segmentation models, privacy-preserving AI, and federated learning has significantly advanced both healthcare and secure computing. With publications in prestigious journals like IEEE Transactions on Medical Imaging and IEEE Journal of Biomedical and Health Informatics, Dr. Teng Huang has demonstrated exceptional research impact. His multi-disciplinary expertise, innovative problem-solving, and commitment to scientific excellence set him apart as a leader in AI-driven healthcare solutions and blockchain applications.

📚 Education

Dr. Teng Huang holds a Ph.D. in Computer Science, specializing in Artificial Intelligence, Blockchain, and Medical Image Processing. His academic journey includes extensive research on deep learning architectures for healthcare and secure computing. His doctoral studies focused on optimizing transformer-based AI models for medical applications, particularly in breast cancer detection and brain tumor segmentation. He has also worked on privacy-preserving federated learning for secure data sharing in healthcare. Dr. Teng Huang’s educational background has equipped him with expertise in machine learning, optimization, and blockchain security, paving the way for his innovative contributions to AI-driven healthcare solutions.

👨‍🏫 Experience 

Dr. Teng Huang is a faculty member and researcher at Guangzhou University, China, where he leads projects on blockchain security, AI-driven diagnostics, and remote sensing applications. He has collaborated with international experts in biomedical image processing, adversarial AI, and recommendation systems. His work in privacy-preserving federated learning has been instrumental in enhancing data security in medical AI applications. With experience in designing intelligent models for 3D medical segmentation, ultrasound imaging, and smart contracts, Dr. Teng Huang continues to push the boundaries of AI research and secure computing, making significant contributions to both academia and industry.

🏅 Awards & Honors 

Dr. Teng Huang has received multiple Best Paper Awards at IEEE international conferences for his pioneering work in AI-driven medical imaging and blockchain security. He has been recognized as a Top Researcher in AI for Healthcare by leading institutions. His contributions to transformer-based medical diagnostics and federated learning security have earned him prestigious grants and funding. He is also a recipient of the Outstanding Young Researcher Award for his work in privacy-preserving AI and adversarial learning techniques. His innovative AI-driven solutions for medical imaging and remote sensing have positioned him as a global leader in computational healthcare research.

🔬 Research Focus 

Dr. Teng Huang specializes in Blockchain, Smart Contracts, Medical Image Processing, and AI-driven Healthcare Innovations. His research involves Comprehensive Transformer Integration Networks (CTIN) for advanced medical image segmentation in breast lesion and brain tumor detection. He is also working on privacy-preserving federated learning for secure medical data exchange. His expertise extends to adversarial learning, recommender systems, and remote sensing AI applications. By integrating deep learning, blockchain security, and smart contracts, Dr. Teng Huang is revolutionizing secure AI-driven diagnostics. His work significantly impacts healthcare, cybersecurity, and AI-based automation for next-generation medical solutions.

📊 Publication Top Notes:

  1. Emission and Absorption Spectroscopic Techniques for Characterizing Perovskite Solar Cells

    • Year: 2024

  2. Advancing Perspectives on Large-Area Perovskite Luminescent Films

    • Year: 2024

  3. Reducing Lead Toxicity of Perovskite Solar Cells with a Built-in Supramolecular Complex

    • Year: 2023

  1. Unlocking Multi-Photon Excited Luminescence in Pyrazolate Trinuclear Gold Clusters for Dynamic Cell Imaging

    • Year: 2024

  2. Durable Organic Nonlinear Optical Membranes for Thermotolerant Lightings and In Vivo Bioimaging

    • Year: 2023

 

 

Mr. Devesh Chand | Renewable Energy | Best Researcher Award

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Mr. Devesh Chand | Renewable Energy | Best Researcher Award

Mr. Devesh Chand, Fiji National University, Fiji

Mr. Devesh Chand is a dedicated educator and researcher in the fields of Mathematics, Physics, and Renewable Energy. He currently serves as a secondary school teacher under the Ministry of Education, Fiji, teaching Mathematics and Physics at Xavier College, Ba. With a strong academic foundation from Fiji National University, his expertise lies in problem-solving, analytical thinking, and scientific exploration. Throughout his academic journey, he has demonstrated exceptional skills in Mathematics, earning multiple awards for academic excellence. His research focuses on renewable energy solutions, aiming to develop sustainable and innovative energy technologies. Beyond academics, Mr. Chand has shown leadership through environmental initiatives and extracurricular activities. His commitment to teaching, research, and community development makes him a well-rounded professional, striving for excellence in both education and applied sciences.

Professional Profile

Orcid

🏆 Suitability for Best Researcher Award 

Mr. Devesh Chand is a promising researcher in Renewable Energy, combining his strong academic background with innovative thinking to address modern energy challenges. His exceptional performance in Mathematics and Physics, coupled with his passion for scientific discovery, makes him a suitable candidate for the Best Researcher Award. His contributions to academia as an educator have inspired students while his research in sustainable energy solutions has the potential to drive impactful change. Mr. Chand’s dedication to excellence is evident through his numerous academic achievements, awards, and involvement in environmental initiatives. His ability to integrate theoretical knowledge with practical applications sets him apart as a researcher who can contribute meaningfully to the field of renewable energy. With a strong foundation in research methodology, critical thinking, and scientific inquiry, he exemplifies the qualities of an outstanding researcher, making him a deserving nominee for this prestigious recognition.

🎓 Education 

Mr. Devesh Chand holds a Bachelor of Education in Secondary Teaching (Mathematics & Physics) from Fiji National University, College of Humanities and Education. His academic journey started at Arya Kanya Pathshala, Yalalevu, Ba, where he completed his primary education from 2008 to 2016. He later pursued his secondary education at Kamil Muslim College, Yalalevu, Ba, from 2017 to 2022, excelling in Mathematics and Technical Drawing. His outstanding academic performance earned him multiple excellence awards, showcasing his strong analytical and problem-solving abilities. Currently, he is advancing his expertise in renewable energy through independent research. His academic background has equipped him with a strong understanding of complex mathematical and physical concepts, which he applies in both his teaching and research endeavors. Mr. Chand’s continuous pursuit of knowledge and passion for STEM education contribute significantly to his professional growth and research contributions in renewable energy.

💼 Experience

Mr. Devesh Chand is currently a Secondary School Teacher at Xavier College, Ba, under the Ministry of Education, Fiji, where he teaches Mathematics and Physics. His expertise in analytical problem-solving and scientific methodology allows him to effectively engage students in STEM subjects. He is committed to fostering critical thinking and innovation in the classroom, preparing students for higher education and research. In addition to his teaching role, he has been actively involved in educational research and curriculum development. His previous experience at Fiji National University, Suva, has further strengthened his foundation in academic instruction and research methodologies. With a keen interest in renewable energy, he integrates real-world applications into his teaching, inspiring students to explore sustainable solutions. Mr. Chand’s dedication to education, research, and environmental awareness positions him as an impactful educator and a rising researcher in the field of energy sustainability.

🏅 Awards and Honors

Mr. Devesh Chand has received several prestigious awards in recognition of his academic excellence and leadership. His achievements include:

  • Best Student in Mathematics (2021) at Kamil Muslim College 🏆
  • Academic Excellence Award for 100% in Mathematics (FY13CE 2021) 🥇
  • Academic Excellence Award for 98% in Mathematics (FY12CE 2020) 📊
  • Academic Excellence Award for 97% in Technical Drawing (FY12CE 2020) 🏗️
  • Best Environmental Officer Award (2019) at Kamil Muslim College 🌍
  • Bronze Standard Award in the Duke of Edinburgh’s International Award 🏅

These accolades reflect his dedication to academic achievement, problem-solving, and environmental consciousness. His exceptional performance in STEM fields, coupled with his leadership skills, establishes him as a distinguished scholar and educator. Mr. Chand’s commitment to excellence continues to drive his research endeavors, making him a deserving candidate for recognition in research and academia.

🔬 Research Focus 

Mr. Devesh Chand’s research is centered on Renewable Energy, with a particular focus on sustainable and efficient energy solutions. His work aims to develop innovative approaches to harness renewable energy sources, including solar, wind, and hydroelectric power, to address global energy challenges. His research explores energy optimization techniques, investigating how emerging technologies can enhance energy efficiency while reducing environmental impact. Through his strong background in Physics and Mathematics, Mr. Chand applies analytical models to study energy conversion, storage, and distribution systems. His interest in clean energy solutions aligns with the global push for sustainability, and he is dedicated to contributing knowledge that will support energy security in the future. By integrating theoretical research with practical applications, he aspires to develop cutting-edge solutions that improve the accessibility and reliability of renewable energy. His research has significant potential to impact sustainable development and environmental conservation.

Publication Top Notes:

Title: Beyond Energy Access: How Renewable Energy Fosters Resilience in Island Communities
  • Publication Date: January 27, 2025