Krishna Pavan Inala | Smart Grids | Best Researcher Award

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Assist. Prof. Dr. Krishna Pavan Inala | Smart Grids | Best Researcher Award

Assistant Professor at BV Raju Institute of Technology | India

Dr. Krishna Pavan Inala is an accomplished researcher specializing in communication networks for smart grids, electric vehicle integration, and intelligent energy management systems. His research advances focus on Vehicle-to-Grid (V2G) communication, distributed grid voltage stability, communication-system impacts on power networks, and machine-learning-based load forecasting. He has published impactful journal articles in leading venues such as IEEE Systems Journal, IEEE Transactions on Industrial Informatics, IET Power Electronics, and the International Journal of Ambient Energy. His research output is well-recognized, with 103 citations, an h-index of 5, and an i10-index of 2 (with 100 citations, h-index 5, and i10-index 2 since 2020). His conference and book-chapter contributions, presented in prominent IEEE conferences and Springer proceedings, span optimal load prediction using machine learning, AI and IoT applications in smart-grid security, deep learning for household demand forecasting, and the role of communication networks in V2G environments. His expertise includes MATLAB, Python, communication-network simulators, and advanced data-analytics tools, enabling him to develop and evaluate innovative solutions for smart-grid communication reliability, predictive modeling, and energy optimization. In teaching and mentoring roles, he integrates concepts from communication engineering, artificial intelligence, and power systems to guide student research and project development. Dr. Inala’s research vision emphasizes building intelligent, secure, and resilient smart-grid infrastructures through robust communication frameworks, AI-driven forecasting, and sustainable energy technologies, contributing significantly to the evolution of next-generation smart electric systems.

Profile: Google Scholar

Featured Publications

1. Sah, B., Kumar, P., Rayudu, R., Bose, S. K., & Inala, K. P. (2018). Impact of sampling in the operation of vehicle to grid and its mitigation. IEEE Transactions on Industrial Informatics, 15(7), 3923–3933.

2. Inala, K. P., Sah, B., Kumar, P., & Bose, S. K. (2020). Impact of V2G communication on grid node voltage at charging station in a smart grid scenario. IEEE Systems Journal, 15(3), 3749–3758.

3. Inala, K. P., Kumar, P., & Bose, S. K. (2019). Impact of communication systems on grid node voltage and operation of a vehicle-to-grid controller in a smart-grid scenario. IET Power Electronics, 12(13), 3499–3509.

4. Inala, K. P., & Thirugnanam, K. (2022). Role of communication networks on vehicle-to-grid (V2G) system in a smart grid environment. In Proceedings of the 2022 4th International Conference on Energy, Power and Environment (ICEPE) (pp. 1–5). IEEE.

5. Manojkumar, R., & Inala, K. P. (2024). Optimised rule-based peak shaving and its impact on annual energy cost reduction. International Journal of Ambient Energy, 45(1), 2397672.

Temitayo Fagbola | Renewable Energy Prediction | Best Researcher Award

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Dr. Temitayo Fagbola | Renewable Energy Prediction | Best Researcher Award

Lecturer at University of Hull, England, United Kingdom

Dr. Temitayo Matthew Fagbola is an internationally recognized academic and researcher in Artificial Intelligence (AI), currently a Teaching Fellow at the University of Hull, United Kingdom. His work centers around applied AI in healthcare, computer vision, natural language processing, and AI ethics. With a career spanning Nigeria, South Africa, and the UK, Dr. Fagbola has published widely on generative AI, semantic segmentation, medical image analysis, and ethical AI. He has also been involved in editorial roles and numerous technical committees, demonstrating leadership in both academic research and professional service.

Publication Profile 

Google Scholar

Educational Background 🎓

  • Postgraduate Certificate in Academic Practice, University of Hull, UK (2023–2024)

  • Ph.D. in Computer Science, Ladoke Akintola University of Technology, Nigeria (2012–2015)

  • M.Sc. in Computer Science, University of Ibadan, Nigeria (2009–2011)

  • B.Tech. (Hons.) in Computer Science, Ladoke Akintola University of Technology, Nigeria (2002–2007)

Professional Experience 💼

  • Teaching Fellow, Centre of Excellence in Data Science, AI and Modelling, University of Hull, UK (2022–Present)

  • Senior Lecturer, Federal University Oye-Ekiti, Nigeria (2021–2022)

  • Honorary Research Associate, Durban University of Technology, South Africa (2020–2022)

  • Postdoctoral Fellow, Durban University of Technology, South Africa (2018–2019)

  • Lecturer / Assistant Lecturer, Federal University Oye-Ekiti, Nigeria (2012–2018)

Research Interests 🔬

  • Applied Artificial Intelligence in Healthcare: including denoising autoencoders, diffusion-based models, and cancer prognosis.

  • Generative AI and Large Language Models (LLMs): especially for medical imaging, ethical conversational agents, and knowledge graphs.

  • Natural Language Processing: topic modeling, sentiment analysis, question answering.

  • Computer Vision: semantic segmentation, image generation and classification.

  • AI Ethics: safety, transparency, and responsible AI development.

Awards and Honors🏆✨

  • Fellow of the Higher Education Academy (FHEA), UK (2024)

  • Winner, Excellence in Feedback, University of Hull (2023)

  • Finalist, Excellence in Teaching, University of Hull (2023)

  • Honorary Research Associate, Durban University of Technology, South Africa (2020–2022)

  • Postdoctoral Research Fellowship, DUT, South Africa (2018–2019)

  • Multiple Travel Grants: NeurIPS, Deep Learning IndabaX, ACM FAT*, ACM SIGKDD, and ESA workshops

  • Best Paper Award, International Journal of Computer Science and Engineering (2014)

Conclusion🌟

Dr. Temitayo Fagbola stands out as a multidisciplinary researcher and educator whose work bridges advanced AI technologies and practical applications in healthcare and education. His scholarly contributions, spanning over 20 peer-reviewed journal articles and edited volumes, are supported by his active participation in global AI conferences, grant-winning projects, and service to academic communities. His combination of academic leadership, international collaborations, and impactful publications makes him an exceptional candidate for recognition in the field of Artificial Intelligence and Computer Science.

Publications 📚

  • 🖥️ Computer-based test (CBT) system for university academic enterprise examination
    📚 International Journal of Scientific & Technology Research, 2(8), 2013
    👨‍💼 Authors: M. Fagbola Temitayo, A. Adigun Adebisi, O. Oke Alice
    🔢 Cited by: 109

  • ☁️ The Impact and Challenges of Cloud Computing Adoption on Public Universities in Southwestern Nigeria
    📚 International Journal of Advanced Computer Science and Applications (IJACSA), 2014
    👨‍💼 Authors: FTMDCY Oyeleye Christopher Akin
    🔢 Cited by: 93*

  • 🧠 Hybrid GA-SVM for efficient feature selection in e-mail classification
    📚 Computer Engineering and Intelligent Systems, 3(3), 2012
    👨‍💼 Authors: F. Temitayo, O. Stephen, A. Abimbola
    🔢 Cited by: 51

  • 📖 Cloud Computing: Master the Concepts, Architecture and Applications with Real-world examples and Case studies
    📚 Book, 2019
    👨‍💼 Authors: M.M. Kamal Kant Hiran, Ruchi Doshi, Temitayo Fagbola
    🔢 Cited by: 37*

  • 😷 Smart face masks for Covid-19 pandemic management: A concise review of emerging architectures, challenges and future research directions
    📚 IEEE Sensors Journal, 23(2), 2022
    👨‍💼 Authors: T.M. Fagbola, F.I. Fagbola, O.J. Aroba, R. Doshi, K.K. Hiran, S.C. Thakur
    🔢 Cited by: 21

  • 🤖 Towards the development of artificial intelligence-based systems: Human-centered functional requirements and open problems
    📚 2019 International Conference on Intelligent Informatics and Biomedical Sciences, 2019
    👨‍💼 Authors: T.M. Fagbola, S.C. Thakur
    🔢 Cited by: 20

  • 📆 Hybrid Metaheuristic Feature Extraction Technique for Solving Timetabling Problem
    📚 International Journal of Scientific and Engineering Research, USA, 3(8), 2012
    👨‍💼 Authors: O.E.O.O.A.C. Olabiyisi Stephen O., Fagbola Temitayo M.
    🔢 Cited by: 19

  • 📱 Development of Mobile-Interfaced Machine Learning-Based Predictive Models for Improving Students’ Performance in Programming Courses
    📚 International Journal of Advanced Computer Science and Applications, 9(5), 2018
    👨‍💼 Authors: F.T.M.A.I.A.O.A.O.O.O.E.A.O.B.E. Funmilola
    🔢 Cited by: 15*

  • 📧 An optimized feature selection technique for email classification
    📚 International Journal of Scientific & Technology Research, 3(10), 2014
    👨‍💼 Authors: O. Oludare, O. Stephen, O. Ayodele, F. Temitayo
    🔢 Cited by: 15

  • 🛰️ A survey on migration process of mobile agent
    📚 Proceedings of the World Congress on Engineering and Computer Science, 2016
    👨‍💼 Authors: M.O. Oyediran, T.M. Fagbola, S.O. Olabiyisi, E.O. Omidiora, A.O. Fawole
    🔢 Cited by: 13

  • 🧑‍🏫 Special issue: Towards a higher education of the future: Transformational roles of edge intelligence
    📚 Array, 22, 100332, 2024
    👨‍💼 Authors: R. Doshi, Y.C. Hu, L. Garg, T. Fagbola
    🔢 Cited by: 12

  • 🏥 An SAP enterprise resource planning implementation using a case study of hospital management system for inclusion of digital transformation
    📚 International Journal of Computer Information Systems and Industrial Management Applications, 2023
    👨‍💼 Authors: O.J. Aroba, A.O. Owoputi, T.M. Fagbola
    🔢 Cited by: 11

  • 📰 News article classification using Kolmogorov complexity distance measure and artificial neural network
    📚 International Journal of Technology, 10(4), 2019
    👨‍💼 Authors: T.M. Fagbola, C.S. Thakur, O. Olugbara
    🔢 Cited by: 11

  • ☁️ An exploratory study of cloud and ubiquitous computing systems
    📚 World Journal of Engineering and Pure & Applied Sciences, 2(5), 2012
    👨‍💼 Authors: S.O. Olabiyisi, T.M. Fagbola, R.S. Babatunde
    🔢 Cited by: 11

  • 🇳🇬 Lexicon-based Bot-aware Public Emotion Mining and Sentiment Analysis of the Nigerian 2019 Presidential Election on Twitter
    📚 Conference/Journal Paper, 2019
    👨‍💼 Authors: T.M. Fagbola, S.C. Thakur
    🔢 Cited by: 10