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.

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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.

Assist Prof Dr Jaya Singh Dhas L | Data Science | Best Researcher Award

Head of the Department at Scott Christian College (Autonomous),India

Dr. L. Jaya Singh Dhas is the Head of the Department of Computer Science at Scott Christian College (Autonomous), Nagercoil, Tamil Nadu, India. With over two decades of experience in academia, Dr. Dhas is a distinguished researcher and educator, specializing in areas like Artificial Intelligence, Machine Learning, Data Mining, and Cloud Computing. His work combines theoretical research with practical applications, particularly in the fields of clustering techniques, heart disease prediction, and network security. Dr. Dhas has contributed significantly to the academic community through his research publications, conference participation, and various professional development activities.

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Education 🎓

Ph.D. in Computer Science – Bharathidasan University, Tiruchirappalli (2022), First Class
M.Phil. in Computer Science – Alagappa University, Karaikudi (1998), First Class
M.C.A. (Master of Computer Applications) – Bharathidasan University, Tiruchirappalli (1996), First Class
B.Sc. in Computer Science – Madurai Kamaraj University, Madurai (1991), First Class

Dr. Dhas’ academic qualifications reflect his deep commitment to the field of computer science and his expertise in both foundational and advanced topics within the discipline.

Professional Experience 💼

Dr. Dhas joined Scott Christian College (Autonomous) in 1998, where he has served as the Head of the Department of Computer Science since then. With more than 20 years of teaching and leadership experience, Dr. Dhas has significantly influenced the department’s curriculum and research direction. He is dedicated to fostering academic growth and promoting innovative research among students and faculty.

Research Interests 🔬

Dr. Dhas’ primary research interests lie in Artificial Intelligence, Data Science, Clustering Techniques, Big Data Analytics, and Network Security. He has worked extensively on the following areas:

Clustering Techniques: Investigating different clustering algorithms for analyzing temporal relational data.
Heart Disease Prediction: Using machine learning techniques for early-stage heart disease prediction.
Network Intrusion Detection: Optimizing deep learning approaches for network security.
Big Data: Exploring synergetic filtering and neural network techniques for handling large datasets.

Awards & Honors 🏆

Dr. Dhas has received multiple recognitions for his outstanding contributions in research and education, including:

Indian Patent (2022) for “Monitoring E-Health Care System Using Artificial Intelligence Techniques”.
Member of the Internet Society and International Association of Engineers (IAENG), further reflecting his international recognition in the field.
Reviewer for several renowned journals, including International Journal of Information Technology and Decision Making (IJITDM) and Journal of Scientific Research and Reports (JSRR).

Achievements 🌟

Successfully published numerous papers in high-impact journals such as Expert Systems With Applications (Elsevier), International Journal of Engineering and Advanced Technology (IJEAT), and Indian Journal of Natural Sciences (IJONS).
Served as a reviewer for several prestigious international journals and conferences, contributing to the academic community’s growth.
Authored multiple book chapters in edited volumes on topics like data clustering and artificial intelligence, further establishing his expertise.

Upcoming Projects 🚀

Dr. Dhas is currently engaged in projects related to AI-driven healthcare systems, particularly focusing on AI in early disease detection.
He is also exploring the use of neural networks and big data analytics to tackle contemporary challenges in network security and data privacy.

Publications 📚

“Hybrid Fast Correlation-based Feature Selection with Improved Weighed Particle Swarm Optimization to Predict and Classify Heart Disease at an Early Stage”, Indian Journal of Natural Sciences (IJONS), Vol. 15, Issue 85, August 2024, Pages 76542 – 76550.
“Network Intrusion Detection: An Optimized Deep Learning Approach Using Big Data Analytics”, Expert Systems With Applications, Elsevier, Volume 251, 1 October 2024, 123919.
“Kulczynski Similarity Index Feature Selection based Map Estimated Rocchio Classification for Brain Tumor Disease Diagnosis”, International Journal on Recent and Innovation Trends in Computing and Communication (IJRITCC), December 2023.
“Identification of Clustering Techniques with Temporal Relational Data Points”, International Journal of Interdisciplinary Global Studies (IJIGS), Volume 14, Issue 04, Oct-Dec’ 2020.
“Efficient Synergetic Filtering in Big Dataset using Neural Network Technique”, International Journal of Recent Technology and Engineering (IJRTE), Volume 8, Issue 5, January 2020, Pages 1349 – 1360.