Jialin Li | Environmental Science | Best Researcher Award

Mr. Jialin Li | Environmental Science | Best Researcher Award

Doctor | Fudan university | China

Mr. Jialin Li is an accomplished researcher and Doctor at Fudan University, specializing in the preparation, functionalization, and application of advanced carbon-based porous materials for hydrogen storage, energy storage, and carbon dioxide capture. His educational background includes a master’s and doctorate in chemical engineering and materials science, where his primary focus was on nano-pore interface micro-environment regulation, design of multi-level nano-pore structures, and surface chemical modification of functional porous carbon fibers, carbon nanofibers, carbon aerogels, and porous carbon materials. Professionally, Mr. Jialin Li has been involved in significant research projects such as the coupling regulation of ultra-fine pores and hydrogen-bond microenvironment of polyacrylonitrile porous carbon nanofibers and investigating hydrogen adsorption mechanisms under confined conditions. He has made valuable contributions to material design strategies for energy applications and has played a key role in translating research findings into practical solutions, including patented technologies for preparing biomass textile fabric electrodes and pre-oxidized fiber fabric electrodes for flow batteries. As a dedicated researcher, Mr. Jialin Li has authored 14 documents, 124 citations, 6 h-index, which highlights his consistent research output and influence in the scientific community. His research has been widely published in reputable international journals, including the Chemical Engineering Journal, Journal of Colloid and Interface Science, ACS Nano, and International Journal of Hydrogen Energy, all indexed in Scopus and SCI, reflecting his ability to contribute to high-quality peer-reviewed publications. Mr. Jialin Li’s research interests include developing new porous carbon materials with ultra-high specific surface areas, improving gas adsorption performance at ambient conditions, and creating novel strategies for hydrogen and carbon dioxide storage. His research skills span advanced material synthesis, nano-structuring, micro-environment modulation, adsorption mechanism analysis, and interface chemical engineering, combined with hands-on experience in experimental design and data interpretation. He is also actively engaged in collaborative research that bridges chemistry, materials science, and environmental engineering, reflecting his interdisciplinary approach. Beyond his technical expertise, Mr. Jialin Li has contributed to mentoring younger researchers, fostering collaboration within his team, and supporting sustainable energy initiatives. His honors include recognition for scientific excellence through peer-reviewed publications, contribution to multiple high-impact studies, and the development of patented solutions that support energy sustainability.

Profile:  Scopus

Featured Publications

Li, J., Wang, Y., Zhang, Y., Zhao, W., Bao, W., Duan, Y., Yu, J., Zhu, B., & Qiao, K. (2024). Dipole-induced hydrogen bonds enhanced P/O co-doped Lyocell-based porous carbon fiber cloth for hydrogen storage under ambient pressure. Chemical Engineering Journal, 490, 151633. Citations: 35

Li, J., Duan, Y., Wang, Y., Zhang, Y., Zhou, J., Zhao, W., Yu, J., Zhu, B., & Qiao, K. (2024). Microenvironment modulation of interpenetrating-type hierarchical porous foam carbon by mild-homogeneous activation for H₂ storage and CO₂ capture under ambient pressure. Journal of Colloid and Interface Science, 675, 783–791. Citations: 28

Yu, J., Li, J., Chen, F., Chi, C., Zhang, W., Bao, W., Zhao, X., Zhu, B., & Qiao, K. (2024). Micro-nano scale synchronous “carving” of viscose fiber in activation process for atmospheric hydrogen storage. International Journal of Hydrogen Energy, 63, 411–417. Citations: 19

Zhang, Y., Zhu, B., Zhao, S., Zhao, W., Zhou, M., Sun, Y., Qiao, K., Liu, J., Zhou, J., & Li, J. (2024). In situ synthesis of self-assembly supramolecular crystal seeds within continuous carbon nanofibers for improved fiber graphitic structure. ACS Nano, 18(17), 11360–11374. Citations: 22

Bao, W., Yu, J., Chen, F., Du, H., Zhang, W., Yan, S., Lin, T., Li, J., Zhao, X., & Zhu, B. (2023). Controllability construction and structural regulation of metal-organic frameworks for hydrogen storage at ambient condition: A review. International Journal of Hydrogen Energy, 48(92), 36010–36034. Citations: 20

 

 

MADHIARASAN M | Renewable Energy Technologies | Best Researcher Award

MADHIARASAN M | Renewable Energy Technologies | Best Researcher Award

Dr MADHIARASAN M, French Institute of Pondicherry, India

Publication profile

google scholar

EDUCATIONAL PROFILE

Dr. Madhiarasan M holds an impressive educational background in electrical engineering. He earned his Ph.D. in Electrical Engineering from Anna University, Chennai (2018). He completed his M.E. in Electrical Drives and Embedded Control with a CGPA of 8.403 (2013) and a B.E. in Electrical and Electronics Engineering from Anna University (2010). His recent postdoctoral fellowships include roles at the Transilvania University of Brașov (2022-2023) and IIT Roorkee (2020-2022). These credentials position him as a scholar with robust expertise in both engineering theory and practical applications.

FIELD OF INTEREST & ACADEMIC PROJECTS

Dr. Madhiarasan’s research interests span SCADA-based supervisory control, robotics for power transmission line inspection, and hybrid neural network models for renewable energy forecasting. His UG and PG projects focused on control systems and robotics, while his Ph.D. tackled neural network applications in energy forecasting. His research aligns with global energy sustainability initiatives, showcasing his commitment to solving pressing electrical engineering challenges.

EXPERIENCE

He has accumulated extensive academic and research experience, starting as a lecturer in 2010. He has taught at various institutions, including the Madras Institute of Technology and Anna University. As an assistant professor at the Bharat Institute of Engineering and Technology (2018-2020), and later as a research fellow, his contributions to academia are significant. His current role at the French Institute of Pondicherry further extends his research prowess.

AWARDS

Among his accolades, Dr. Madhiarasan received the UGC Fellowship and Transilvania Fellowship for young researchers. In 2023, he was honored with the Best Researcher Award at the 10th Global Research Awards on Artificial Intelligence and Robotics. His accolades highlight his excellence in research, particularly in AI and renewable energy applications.

PROJECT GUIDANCE

His project supervision includes the development of IoT-based systems, including energy monitoring and robotics for military use. His work has practical applications, particularly in power transmission monitoring and control, emphasizing his capability to guide impactful projects in the field of electrical and computer engineering.

WORKSHOPS/SEMINARS/CONFERENCE ORGANIZATION

Dr. Madhiarasan has organized key academic events, such as the World Entrepreneurs’ Day TECHFEST 2023 and national workshops on research writing. He also co-coordinated AICTE-sponsored faculty development programs on artificial intelligence at IIT Roorkee. His leadership in academic forums demonstrates his active engagement in sharing knowledge with the broader research community.

EDITOR & REVIEWER

He has contributed as an editor for various international journals and special issues, including those on renewable energy and embedded technologies. His editorial work in prestigious journals like Sensors (MDPI) reflects his strong academic standing in the field of electrical engineering and renewable energy research.

CO-CURRICULAR CERTIFICATIONS

Dr. Madhiarasan has completed numerous certifications related to wind and solar energy, electronics, and design thinking, which reflect his commitment to continuous learning. These certifications from top global universities via Coursera strengthen his expertise in energy systems and innovation.

ACHIEVEMENTS

Throughout his career, Dr. Madhiarasan has excelled in academics, including ranking second in his M.E. program. His extracurricular achievements include awards in oratory competitions and television appearances. His participation in national seminars and debates further demonstrates his well-rounded profile as a scholar and communicator.

RESEARCH FOCUS

M. Madhiarasan’s research primarily focuses on applying artificial neural networks (ANNs) and machine learning techniques to wind speed forecasting. His work includes developing methods to optimize neural network architectures, such as selecting the appropriate number of hidden neurons for improved prediction accuracy. He has explored various ANN models, including backpropagation, radial basis function, and spiking neural networks, enhancing their performance with optimization algorithms like Grey Wolf Optimization. Additionally, his studies cover different forecast horizons, long-term predictions, and comparative analyses of network architectures for wind energy applications. 🌬️🌐🤖📊

CONCLUSION

Dr. Madhiarasan M is highly suitable for the Best Researcher Award. With his comprehensive educational background, extensive research experience, and significant contributions to the field of electrical engineering and renewable energy, he stands out as a leader in academic and industrial collaborations. His awards, editorial roles, and leadership in organizing academic events further support his candidacy for this prestigious honor.

PUBLICATION TOP NOTES

Comparative analysis on hidden neurons estimation in multi layer perceptron neural networks for wind speed forecasting

A novel criterion to select hidden neuron numbers in improved back propagation networks for wind speed forecasting

Accurate prediction of different forecast horizons wind speed using a recursive radial basis function neural network

Analysis of artificial neural network: architecture, types, and forecasting applications

Long-Term Wind Speed Forecasting using Spiking Neural Network Optimized by Improved Modified Grey Wolf Optimization Algorithm

A comprehensive review of sign language recognition: Different types, modalities, and datasets

ELMAN Neural Network with Modified Grey Wolf Optimizer for Enhanced Wind Speed Forecasting

New criteria for estimating the hidden layer neuron numbers for recursive radial basis function networks and its application in wind speed forecasting

Performance investigation of six artificial neural networks for different time scale wind speed forecasting in three wind farms of coimbatore region

Analysis of artificial neural network performance based on influencing factors for temperature forecasting applications

A Novel Method to Select Hidden Neurons in ELMAN Neural Network for Wind Speed Prediction Application