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
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).
Seemantās 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
- Book Chapter
- Published in Lecture Notes in Networks and Systems, 2024
- DOI: 10.1007/978-3-031-60591-8_15
- Mathematics for Machine Learning
- Conference Paper
- Presented at the 3rd International Conference for Innovation in Technology (INOCON 2024)
- DOI: 10.1109/INOCON60754.2024.10511475
- A Survey on Big Data Analytics for Load Prediction in Smart Grids
- Book Chapter
- Published in Lecture Notes in Electrical Engineering, 2023
- DOI: 10.1007/978-981-99-0248-4_3
- Industries Application of Type-2 Fuzzy Logic
- Conference Paper
- Published in Lecture Notes in Networks and Systems, 2023
- DOI: 10.1007/978-3-031-25344-7_16
- Segmentation and Clustering of Time Series Data
- Conference Paper
- Presented at International Conference for Advancement in Technology (ICONAT 2023)
- DOI: 10.1109/ICONAT57137.2023.10080820
- Modification Metric of Class Document on NaĆÆve Bayes for Sentiment Analysis of Online Learning Evaluation
- Conference Paper
- Presented at 1st International Conference on Advanced Engineering and Technologies (ICONNIC 2023)
- DOI: 10.1109/iconnic59854.2023.10467513
- Artificial Intelligence (AI) in the Sustainable Energy Sector
- Conference Paper
- DOI: 10.3390/ECP2023-14609
- Implications of Machine Learning in Renewable Energy
- Conference Paper
- DOI: 10.3390/ECP2023-14610
- Applications of Smart Technologies Regarding Promoting Energy Efficiency and Sustainable Resource Utilization
- Conference Paper
- Presented at International Conference on Futuristic Technologies (INCOFT 2022)
- DOI: 10.1109/INCOFT55651.2022.10094395
- Approaches Involving Big Data Analytics Using Machine Learning
- Conference Paper
- Presented at IEEE 3rd Global Conference for Advancement in Technology (GCAT 2022)
- DOI: 10.1109/GCAT55367.2022.9972108
- 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
- Conference Paper
- Presented at International Conference on Informatics (ICI 2022)
- DOI: 10.1109/ICI53355.2022.9786880
- 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
- Conference Paper
- DOI: 10.3390/ASEC2022-13823
- Various Models for Predicting Wind Energy Production
- Conference Paper
- DOI: 10.3390/ASEC2022-13792
Conclusion
Given his focus on renewable energy, AI, and practical applications in energy forecasting, Mr. Seemant Tiwariās research has the potential to drive significant community-level impact, making him a fitting candidate for the Research for Community Impact Award.