Ms Jayasree Varadarajan | Artificial Intelligence | Best Researcher Award

Ms Jayasree Varadarajan | Artificial Intelligence | Best Researcher Award

AI Technical Analyst Lead at Manchester Metropolitan University,United Kingdom

Jayasree Varadarajan’s journey in Artificial Intelligence (AI) is a story of relentless pursuit of knowledge, groundbreaking contributions, and inspiring leadership. From her early academic foundations to becoming a beacon of innovation and expertise in AI, her accomplishments reflect her dedication and profound impact on the field.

Profile

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🎓 Early Academic Pursuits

Jayasree’s academic journey began in India, where she earned a Bachelor’s degree in Electronics & Communication Engineering from Periyar Maniammai University in 2012. Demonstrating exceptional aptitude, she pursued a Master’s in VLSI Design from Kings College of Engineering, graduating in 2014 as an academic topper.

Eager to explore the nexus of satellite technology and AI, she earned an MSc in Satellite Data Science from the University of Leicester, UK, in 2022. Her academic foundation provided her with a deep understanding of complex systems, preparing her to address real-world challenges in AI and beyond.

💼 Professional Endeavors

Jayasree’s professional trajectory showcases her versatility in various roles and industries:

  • AI Technical Analyst Lead (2023 – Present): At the Center for Digital Innovation, MMU, UK, funded by UKRI-Innovate UK, Jayasree has been instrumental in leading the design and development of AI-driven healthcare and IT solutions. Her work bridges the gap between academic research and practical applications while ensuring ethical AI practices.
  • AI Technical R&D Analyst (2023): In this role at GM AI Foundry, she accelerated SME businesses by integrating AI into their operations, emphasizing ethical standards and innovative problem-solving.
  • Machine Learning Research Assistant (2022): At Space Park Leicester, she contributed to a SPRINT project that utilized aerial LiDAR data and machine learning algorithms to estimate carbon sequestration potential.
  • AI Data Scientist (2016–2021): Jayasree led projects such as the “E-Doctor Alexa System,” which addressed healthcare challenges through predictive modeling. Her work demonstrated a profound ability to develop business solutions using AI and machine learning.

🔬 Contributions and Research Focus

Jayasree’s research has centered on applying AI and ML technologies to solve critical problems in healthcare, environment, and business. Her publications in journals like MDPI and Heliyon delve into the applications of AI for societal benefit.

As a resource person for Faculty Development Programs, Jayasree has conducted numerous webinars and seminars, empowering students and academics with advanced AI tools. She has also shared her expertise on global platforms such as:

  • AI Summit London (2023)
  • AI Summit Singapore (2024)

🏆 Accolades and Recognition

Jayasree’s exemplary work has earned her several accolades:

  • Finalist in the Promising Professional Category (IIW Awards 2024): This recognition underscores her growing influence and contributions to AI.
  • Academic Excellence: She consistently ranked as a topper during her undergraduate and postgraduate studies.
  • UK Global Talent Visa: Endorsed as an exceptional talent in AI by UKRI, Jayasree’s recognition in 2024 highlights her leadership in the field.

She has also earned certificates of appreciation from academic institutions for her role as a resource person and technical expert.

🌍 Impact and Influence

Jayasree’s expertise in programming (Python, R), cloud technologies (Microsoft Azure), and AI domains like NLP, Generative AI, and Prompt Engineering has influenced diverse industries. Her ability to deliver custom AI tools, mentor professionals, and provide actionable solutions showcases her as a transformative leader in AI.

Her role as a mentor and thought leader inspires a generation of budding AI enthusiasts and professionals. By demystifying AI concepts and advocating for ethical AI use, she fosters responsible innovation and sustainable development.

🌟 Legacy and Future Contributions

Looking ahead, Jayasree aims to:

  • Expand her research on healthcare applications of AI, focusing on predictive analytics and AI-driven health solutions.
  • Continue empowering students and professionals through education and mentorship.
  • Advocate for responsible AI practices on global platforms to ensure its positive impact on society.

Her journey from academic brilliance to professional excellence positions her as a trailblazer in AI. Jayasree Varadarajan’s story is not just about achievements; it is about the meaningful impact of technology when guided by passion, ethics, and a vision for a better future.

Publication Top Notes

Artificial Intelligence

  • Md Abu Sufian, Jayasree Varadarajan (2024). “Enhancing prediction and analysis of UK road traffic accident severity using AI: Integration of machine learning, econometric techniques, and time series forecasting in public health.” Heliyon, 10(7).
  • Md Abu Sufian, W Hamzi, B Hamzi, ASMS Sagar, M Rahman, Jayasree Varadarajan, et al. (2024). “Innovative machine learning strategies for early detection and prevention of pregnancy loss: the Vitamin D connection and gestational health.” Diagnostics, 14(9), 920.
  • Md Abu Sufian, W Hamzi, S Zaman, L Alsadder, B Hamzi, Jayasree Varadarajan, et al. (2024). “Enhancing Clinical Validation for Early Cardiovascular Disease Prediction through Simulation, AI, and Web Technology.” Diagnostics, 14(12), 1308.
  • Md Abu Sufian, Jayasree Varadarajan, M Hanumanthu, L Katneni, A Jamil, V Lal, et al. (2024). “Optimizing E-Sports Revenue: A Novel Data Driven Approach to Predicting Merchandise Sales Through Data Analytics and Machine Learning.” Science and Information Conference, 522-567.
  • Md Abu Sufian, Md Ashraful Islam, Jayasree Varadarajan (2023). “AI Models for Early Detection and Mortality Prediction in Cardiovascular Diseases.” TechRxiv.
  • Jayasree Varadarajan, Md Abu Sufian (2023). “Neuro App: AI-driven 4D brain image processing on standalone platforms.” Journal of Computer Engineering & Information Technology, 12.
  • Jayasree Varadarajan, Jeyaseelan (2014). “Design of Ultrasound Biomicroscopy in Open Platform Using FPGA.” Second International Conference On Science, Engineering and Management, 2.

 

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).

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.