Ramesh C | Energy | Best Researcher Award

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Dr. Ramesh C | Energy | Best Researcher Award

Kalaignar Karunanidhi Institute of Technology | India

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Early Academic Pursuits 📚

Dr. Ramesh C embarked on his academic journey with an exceptional foundation in mechanical engineering. Completing his Diploma in Mechanical Engineering at the Government Polytechnic College, Tuticorin, with distinction, he progressed to earn a Bachelor’s degree from P.S.R. Engineering College, Sivakasi. His quest for excellence led him to pursue a Master’s in Thermal Engineering at the Government College of Technology, Coimbatore, followed by a Ph.D. in Mechanical Engineering from Anna University, Chennai, where his work received high commendation in September 2022.

Professional Endeavors 🛠️

Dr. Ramesh has been a cornerstone at the Kalaignar Karunanidhi Institute of Technology (KIT), Coimbatore, serving as an Associate Professor in Mechanical Engineering since June 2012. His tenure spans over 12 years and 7 months, during which he has inspired countless students and contributed significantly to academic excellence. He has also undertaken critical administrative roles, including Assistant Controller of Examinations and Overall Examination Cell Coordinator, showcasing his leadership in maintaining academic integrity and efficiency.

Contributions and Research Focus 🔬

Dr. Ramesh's contributions to the field of thermal and renewable energy systems are profound. With 18 international journal publications, including groundbreaking research in solar energy and nanofluid applications, his work is highly cited (109 citations, h-index: 6, i10-index: 3). His research focuses on optimizing solar energy systems, enhancing energy efficiency, and developing sustainable technologies. Key projects include performance analysis of solar collectors and integration of photovoltaic systems for maximum energy output.

Accolades and Recognition 🏆

Dr. Ramesh’s scholarly output and impactful research have earned him recognition in reputed journals with significant impact factors. His innovative work has been featured in prestigious platforms like Sustainability and Energy & Environment. He has also contributed to international book chapters and presented his findings in multiple international and national conferences, further solidifying his reputation as a thought leader in mechanical engineering.

Impact and Influence 🌟

As an educator, Dr. Ramesh has adeptly handled diverse subjects, ranging from Heat and Mass Transfer to Renewable Energy Sources, equipping students with practical and theoretical knowledge. His administrative acumen has improved examination processes and ensured seamless academic operations. His commitment to research and education continues to inspire peers and students alike.

Legacy and Future Contributions 🌍

Dr. Ramesh’s dedication to innovation, sustainability, and academic excellence sets a benchmark for future engineers and researchers. His ongoing work in renewable energy technologies promises to contribute significantly to addressing global energy challenges. With a legacy rooted in excellence and impact, Dr. Ramesh is poised to shape the future of engineering and technology, inspiring generations to come.

 

Publications

📘 Optimizing Performance of a Solar Flat Plate Collector for Sustainable Operation Using Box–Behnken Design (BBD)
 Authors: C. Ramesh, Hariprsad P., Almeshaal, M., Manoj Kumar, P.
Year: 2025
 Journal: Sustainability

📘 Enhanced Honey Badger Optimization of Performance Analysis of Evacuated Tube Heat Pipe Solar Collector Integrated with PCM Storage Unit
Authors: C. Ramesh, M. Vijayakumar, G. Kumaresan, Benjamin Franklin Selvanayagam
 Year: 2023
Journal: Energy & Environment

📘 Solar Thermal System Integration Studies to Determine the Influence on Solar Photovoltaic Module Efficiency
Authors: Ramesh C., Vijayakumar M., Sathessh Kumar S., Vijaya Kumar M.
 Year: 2022
Journal: NeuroQuantology

📘 Mechanical and Morphological Studies of Sansevieria trifasciata Fiber-Reinforced Polyester Composites with the Addition of SiO2 and B4C
 Authors: Hariprasad P., Kannan M., Ramesh C., Felix Sahayaraj A., Jenish I., Fayaz Hussain, Nidhal Ben Khedher, Attia Boudjemline, Suresh V.
 Year: 2022
 Journal: Advances in Materials Science and Engineering

📘 Analyzing Thermal Performance of a Solar PV Using a Nanofluid
 Authors: Kedri Janardhana, Sivakumar A., Suresh R., Ramesh C., Syed Musthafa A., Satyendra Vishwakarma
Year: 2022
 Journal: Materials Today

 

Logeeshan Velmanickam | Energy | Best Researcher Award

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Dr. Logeeshan Velmanickam | Energy | Best Researcher Award

University of Moratuwa | Sri Lanka

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🎓 Early Academic Pursuits

Dr. Logeeshan Velmanickam's academic journey is marked by excellence and dedication. He earned his Ph.D. in Electrical and Computer Engineering from North Dakota State University (NDSU) in 2019, graduating with the highest honors, equivalent to Summa Cum Laude, with a perfect GPA of 4.0/4.0. Before that, he completed his B.Sc. in Electrical and Electronic Engineering from the University of Peradeniya, Sri Lanka, in 2014, where he graduated with First Class Honors.

💼 Professional Endeavors

Dr. Velmanickam has an extensive and impactful career, serving as a Senior Lecturer at the Department of Electrical Engineering, University of Moratuwa (UoM) since 2021. His teaching repertoire includes a variety of subjects such as Theory of Electricity, Circuit Theory, and Digital Signal Processing for undergraduate students, as well as specialized courses like Sensors and Actuators for Automation and Industrial Communication Systems for postgraduate students. His commitment to education is further evident through his involvement in curriculum revision, practical coordination, and supervision of numerous MSc and final year projects.

🔬 Contributions and Research Focus

A prolific researcher, Dr. Velmanickam's work intersects the realms of AI, IoT, and biomedical instrumentation. His research efforts have led to groundbreaking developments in lab-on-a-chip technologies and smart sensors. Notably, he has contributed to the integration of AI techniques in electrical engineering, particularly in designing next-generation biomedical devices. His patent portfolio includes innovations in dielectrophoretic and surface plasmonic apparatuses, which are pivotal in improving the detection of biological molecules.

🏆 Accolades and Recognition

Dr. Velmanickam's academic and professional excellence has been recognized through numerous awards. He has won multiple Best Presenter and Best Paper Awards at prestigious conferences such as the IEEE World AI IoT Congress and the Moratuwa Engineering Research Conference. His achievements also include winning the NDSU Innovation Challenge Competition and receiving the NDSU College of Engineering Graduate Research Assistant of the Year Award. Additionally, he has been honored with memberships in esteemed societies like Phi Kappa Phi and IEEE-Eta Kappa Nu, reserved for those with exemplary academic records.

🌍 Impact and Influence

Dr. Velmanickam's influence extends beyond the classroom and laboratory. As a consultant and senior lecturer, he has been instrumental in the development of rapid COVID-19 detection devices and other innovative solutions in collaboration with institutions like the Arthur C. Clarke Institute for Modern Technologies. His mentorship has shaped the careers of numerous students, fostering a new generation of engineers and researchers.

🛠️ Legacy and Future Contributions

Dr. Velmanickam’s legacy is defined by his relentless pursuit of knowledge and innovation. His work in AI, IoT, and biomedical engineering continues to push the boundaries of what is possible, with a particular focus on developing affordable, cutting-edge solutions for healthcare. As he continues to lead in both academia and industry, his future contributions are poised to make a lasting impact on the fields of electrical engineering and beyond.

 

Publications ✍️

  • 📄 "NILM for Commercial Buildings: Deep Neural Networks Tackling Nonlinear and Multi-Phase Loads"
    Authors: M. J. S. Kulathilaka, S. Saravanan, H. D. H. P. Kumarasiri, V. Logeeshan, S. Kumarawadu, Chathura Wanigasekara
    Journal: Energies, Year: 2024
  • 📄 "Design and Analysis of a Three-Phase Interleaved DC-DC Boost Converter with an Energy Storage System for a PV System"
    Authors: Pirashanthiyah, L., Edirisinghe, H.N., De Silva, W.M.P., Logeeshan, V., Wanigasekara, C.
    Journal: Energies, Year: 2024
  • 📄 "A Secure and Smart Home Automation System with Speech Recognition and Power Measurement Capabilities"
    Authors: Irugalbandara, C., Naseem, A.S., Perera, S., Kiruthikan, S., Logeeshan, V.
    Journal: Sensors, Year: 2023
  • 📄 "Traveling Wave Based Fault Location and Fault Classification Technique for Distribution Networks with High Renewable Penetration"
    Authors: Bamunusinghe, D., Peiris, P., Nagarajah, K., Logeeshan, V., Gunawardana, M.
    Journal: ICEFEET, Year: 2023
  • 📄 "Optimum Dispatch of Turbines in a Low Head Hydropower Plant for a Given Total Flow Rate and Available Variable Head - A Case Study for Moragahakanda Power Station in Sri Lanka"
    Authors: Haputhanthree, H.G.S.V., Logeeshan, V., Wijayapala, W.D.A.S.
    Journal: MERCon, Year: 2023

 

Lei Wang | Energy | Innovation in Publishing Award

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Dr. Lei Wang | Energy | Innovation in Publishing Award

Tsinghua University | China

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Early Academic Pursuits

Lei Wang embarked on his academic journey, earning a Bachelor's degree in Electrical Engineering from Yangtze University in 2015. He furthered his studies, completing a Master's degree at Hubei University of Technology in 2019 and earning his Ph.D. from Wuhan University in Electrical Engineering in 2023.

Professional Endeavors

Lei Wang delved into the realm of academia, contributing significantly to various research projects. His roles included postdoctoral research at Tsinghua University, focusing on machine learning applications in battery prognostics and health management. He demonstrated his expertise in anomaly detection, safety assessment, and predictive modeling for battery systems.

Contributions and Research Focus

Lei Wang made substantial contributions to the "Power IoTs" project, focusing on deep reinforcement learning for adaptive uncertainty economic dispatch in power systems. His innovative models addressed the complexities of economic dispatch, showcasing adaptability to uncertain conditions, particularly in renewable energy integration scenarios.

Accolades and Recognition

Lei Wang received recognition for his pivotal role in developing a deep reinforcement learning-based approach, enhancing economic dispatch in power systems. His work contributed to grid reliability and efficiency, demonstrating practical applicability in real-world scenarios, particularly in Tianjin's Binhai New Area.

Impact and Influence

Lei Wang's research has left a lasting impact on the field, advancing the understanding of power system optimization. His work not only contributes to academic knowledge but also has practical implications for improving the efficiency and reliability of power delivery and consumption.

Legacy and Future Contributions

Lei Wang's legacy includes pioneering work in machine learning applications for battery systems and economic dispatch in power systems. Looking ahead, his expertise in artificial intelligence, spatiotemporal correlation modeling, and power equipment diagnosis positions him as a key contributor to the evolving landscape of energy research. As an emerging leader in the field, Lei Wang is poised to continue making groundbreaking contributions to the energy sector.

Notable Publications

An Unsupervised Approach to Wind Turbine Blade Icing Detection Based on Beta Variational Graph Attention Autoencoder 2023

Wind turbine blade icing risk assessment considering power output predictions based on SCSO-IFCM clustering algorithm 2024

A novel approach to ultra-short-term multi-step wind power predictions based on encoder–decoder architecture in natural language processing 2022 (18)

M2STAN: Multi-modal multi-task spatiotemporal attention network for multi-location ultra-short-term wind power multi-step predictions 2022 (22)

M2TNet: Multi-modal multi-task Transformer network for ultra-short-term wind power multi-step forecasting 2022 (19)