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

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

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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).

Seemantā€™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.

Ā Publications:Ā 

  • 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 NaĆÆve 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 Tiwariā€™s research has the potential to drive significant community-level impact, making him a fitting candidate for the Research for Community Impact Award.