Mr Seemant Tiwari | AI & ML | Best Researcher Award | 1086

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Mr Seemant Tiwari | AI & ML | Best Researcher Award

Ph. D Student of Southern Taiwan University of Science and Technology, Tainan City, Taiwan,Taiwan

Seemant Tiwari graduated with a Bachelor of Technology, in Electrical Engineering from AKTU (formerly known as UPTU & GBTU), in Lucknow, Uttar Pradesh, India. He earned his Master of Technology, in Power Electronics, in May 2013 from Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, in Chennai, Tamil Nadu, India. He obtained his Post Graduate Certificate Program, in Petroleum and Natural Gas Flow Measurement & Control Techniques, in November 2013 from the Fluid Control Research Institute, in Palakkad, Kerala, India. He has been working on a Ph.D. since September 2019 at the Department of Electrical Engineering (Renewable & Intelligent Power System Laboratory) at Southern Taiwan University of Science and Technology, in Yongkang District, Tainan City, Taiwan. Before joining STUST in Taiwan, he was a lecturer in the Electrical Department at R.B.S. Polytechnic, in Agra, Uttar Pradesh, India. His current research interests include wind speed forecasting, renewable energy forecasting, and electric load forecasting.

Profile

orcid

Education

  • Bachelor of Technology (B.Tech.) in Electrical Engineering from AKTU (formerly UPTU & GBTU), Lucknow, India.
  • Master of Technology (M.Tech.) in Power Electronics from Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, India (2013).
  • Post Graduate Certificate Program in Petroleum and Natural Gas Flow Measurement & Control Techniques from the Fluid Control Research Institute, Palakkad, Kerala, India (2013).

Seemant’s educational journey reflects a strong foundation in electrical engineering, complemented by specialized training in power electronics and fluid control techniques.

Experience

Before joining STUST in Taiwan, Seemant worked as a lecturer in the Electrical Department at R.B.S. Polytechnic, Agra, India. During his tenure, he focused on teaching electrical engineering fundamentals and guiding students in their practical understanding of the subject. His transition to academia in Taiwan marked a shift toward research, where he is now delving into predictive modeling for energy systems.

Awards and Recognition

Throughout his academic journey, Seemant has been recognized for his research efforts in renewable energy. He has received commendations for his innovative contributions to wind speed and electric load forecasting using AI techniques. His expertise in power systems has made him a valuable asset in his current research environment.

Academic and Professional

Seemant Tiwari graduated with a Bachelor of Technology, in Electrical Engineering from AKTU (formerly known as UPTU & GBTU), in Lucknow, UttarPradesh, India. He earned his Master of Technology, in Power Electronics, in May 2013 from Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, in Chennai, Tamil Nadu, India. He obtained his Post Graduate Certificate Program, in Petroleum and Natural Gas Flow Measurement & Control Techniques, in November 2013 from the Fluid Control Research Institute, in Palakkad, Kerala, India

Areas of Research: AI & ML

Seemant has been working on a Ph.D. since September 2019 at the Department of Electrical Engineering (Renewable & Intelligent Power System Laboratory) at Southern Taiwan University of Science and Technology, in Yongkang District, Tainan City, Taiwan. Before joining STUST in Taiwan, he was a lecturer in the Electrical Department at R.B.S. Polytechnic, in Agra, Uttar Pradesh, India. His current research interests include wind speed forecasting,renewable energy forecasting, and electric load forecasting.

 Publications: 

  • Big Data Analytics: Energy Forecasting Computational Intelligence Methods
  • Mathematics for Machine Learning
  • A Survey on Big Data Analytics for Load Prediction in Smart Grids
  • Industries Application of Type-2 Fuzzy Logic
  • Segmentation and Clustering of Time Series Data
  • Modification Metric of Class Document on Naïve Bayes for Sentiment Analysis of Online Learning Evaluation
  • Artificial Intelligence (AI) in the Sustainable Energy Sector
  • Implications of Machine Learning in Renewable Energy
  • Applications of Smart Technologies Regarding Promoting Energy Efficiency and Sustainable Resource Utilization
  • Approaches Involving Big Data Analytics Using Machine Learning
  • Electrical Load Forecasting Methodologies and Approaches
    • Conference Paper
    • Published in Eurasia Proceedings of Science, Technology, Engineering and Mathematics, 2022
    • DOI: 10.55549/epstem.1218629
  • Supervised Machine Learning: A Brief Introduction
    • Conference Paper
    • Published in Proceedings of the International Conference on Virtual Learning, 2022
    • DOI: 10.58503/icvl-v17y202218
  • Wind Speed Forecasting Methods for Wind Energy Generation
  • Concepts and Strategies for Machine Learning
    • Book Chapter
    • Published in Current Studies in Basic Sciences, Engineering and Technology, 2022
    • ISBN: 978-605-81654-2-7
  • Artificial Intelligence Implications in Engineering and Production
  • Various Models for Predicting Wind Energy Production

Conclusion

Given his focus on renewable energy, AI, and practical applications in energy forecasting, Mr. Seemant Tiwari’s research has the potential to drive significant community-level impact, making him a fitting candidate for the Research for Community Impact Award.

Dr He Zhao | Energy Storage | Best Researcher Award

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Dr He Zhao | Energy Storage | Best Researcher Award

Assistant ,South China University of Technology,China

He Zhao is a Postdoctoral Researcher at South China University of Technology, Guangdong, China. With a strong background in advanced materials science and electrochemistry, Zhao has contributed significantly to the field of high-performance energy storage and sensor technologies. His research focuses on innovative materials for solid-state lithium batteries, CO2 reduction, and ratiometric luminescent sensing. Zhao has co-authored several high-impact publications and continues to advance the frontiers of energy materials and catalytic processes.

Profile

orcid

Education

While specific educational details are not provided, given his current role as a postdoctoral researcher and the level of research undertaken, it is likely that He Zhao holds a PhD in a related field, such as Materials Science, Chemistry, or Chemical Engineering.

Experience

Postdoctoral Researcher
South China University of Technology, GuangDong, China

  • Engaged in advanced research focusing on energy storage materials, catalysis, and luminescent sensing technologies.

Research Interests

  1. Energy Storage Materials:
    Development of high-performance solid-state lithium batteries and other energy storage solutions.
  2. Catalysis:
    Enhancement of catalytic performance through novel materials and configurations, including single-atom catalysts.
  3. Luminescent Sensing:
    Design and application of metal-organic frameworks (MOFs) for sensitive and multidimensional ratiometric luminescent sensing.
  4. Material Science:
    Exploration of the physical and chemical properties of materials to improve performance in various applications.

Areas for Improvement

  1. Broader Collaboration:
    Expanding collaborations with international researchers could further enhance the impact and reach of his work.
  2. Increased Publication in High-Impact Journals:
    While He Zhao has published in reputable journals, targeting higher-impact publications could increase visibility and recognition.
  3. Grant Acquisition:
    Securing additional research funding could facilitate more extensive and innovative projects.
  4. Interdisciplinary Research:
    Exploring interdisciplinary approaches could open new avenues for research and applications.

Notable Publications

  1. High-Performance Solid-State Lithium Batteries
    Zhao, H., Liu, Y., Huang, L., Li, L., Li, X., Cui, Z., Du, L., & Liao, S. (2024). Energy Storage Materials, 71, 103625.

    • Focuses on enhancing the performance of solid-state lithium batteries through advanced electrolyte and electrode assemblies.
  2. Li-CO2 Batteries
    Huang, L., Zhao, H. (Co-first author), Zhao, Y., Chen, Z., Sun, S., Zhang, Z., & Liao, S. (2024). Chemical Engineering Journal, 493: 152723.

    • Investigates atomically dispersed Cu and Cr on N-doped hollow carbon nanocages to improve lithium-carbon dioxide batteries.
  3. Catalysts for Oxygen Reduction
    Duan, D., Huo, J., Chen, J., Chi, B., Chen, Z., Sun, S., Zhao, Y., Zhao, H., Cui, Z., & Liao, S. (2024). Small, 2310491.

    • Examines Hf and Co dual single atoms co-doped carbon catalysts for enhanced oxygen reduction reactions.
  4. Trichromatic MOF Composite for Luminescent Sensing
    Zhao, H., Ni, J., Zhang, J.-J., Liu, S.-Q., Sun, Y.-J., Zhou, H.-J., Li, Y.-Q., & Duan, C.-Y. (2018). Chemical Science, 9, 2918-2926.

    • Discusses a trichromatic MOF composite for advanced ratiometric luminescent sensing.
  5. MOF Cavity/Encapsulated Luminescent Modules
    Zhao, H., Di, L., Wang, S.-W., Zhang, J.-J., Liu, Z., Fang, W.-J., Liu, S.-Q., Ni, J., & Song, X.-D. (2021). Sensors and Actuators B: Chemical, 328, 129025.

    • Explores size effects in MOF cavities and encapsulated modules for improved vapor detection.
  6. Crystallographic Diffraction Quality of Flexible MOFs
    Zhao, H., Huang, J.-X., Zhang, P.-P., Zhang, J.-J., Fang, W.-J., Song, X.-D., Liu, S.-Q., & Duan, C.-Y. (2021). iScience, 24, 103398.

    • Investigates the impact of stable configurations on the diffraction quality of flexible MOFs.
  7. Trichromatic White-Light-Emitting MOF Composites
    Zhao, H., Zhang, J.-J. (2017). 中国化学学会第八届全国配位化学学术会议 (8th National Coordination Chemistry Conference, China).

    • Presented work on trichromatic MOF composites for ratiometric luminescence sensing.

Conclusion

He Zhao has demonstrated significant contributions to material science through his research on energy storage systems, catalysis, and luminescent sensing technologies. His work reflects a deep understanding of complex materials and their applications. Continued focus on collaborative and high-impact research will likely further his influence in the field.