Shanmugam S | Machine Learning | Best Researcher Award

Published-on by Indian Scientist

Dr. Shanmugam S | Machine Learning | Best Researcher Award

SRM Institute of Science and Technology | India

Dr. Shanmugam S is an academic and researcher in the field of computing technologies with a focus on Artificial Intelligence and Machine Learning. His scholarly portfolio reflects professional engagement with advanced areas including Soft Computing, Transfer Learning, and Quantum Computing. He has completed his doctoral research in Information and Communication, supported by previous postgraduate and undergraduate education in computer science and information technology disciplines. His publication record includes 24 research documents, with 342 citations received from 322 referencing documents, supported by an h-index of 8, highlighting the relevance and impact of his contributions in the research community. He has accumulated significant teaching and research experience, handling courses such as Data Structures, Object-Oriented Programming, Big Data for Machine Learning, Software Engineering, Business Computing, and Philosophy of Engineering. His efforts extend to guiding students, contributing to departmental academic activities, and participating in various scholarly workshops, seminars, and conferences. His research interests continue to explore emerging computational paradigms and their applications in solving real-world challenges. He has received recognition for academic and research contributions, reinforcing his professional standing. Overall, his work contributes to the advancement of intelligent systems and computational innovation.

Profile: Scopus

Featured Publications

Role of hydroxychloroquine in primary glomerular disease – a systematic review and meta-analysis of the current evidence. BMC Nephrology. (2025).

Exploring the ability of emerging large language models to detect cyberbullying in social posts through new prompt-based classification approaches. Information Processing and Management. (2025).

Ramesh Babue E | Big Data Analytics | Best Researcher Award

Published-on by Indian Scientist

Mr. Ramesh Babue E | Big Data Analytics | Best Researcher Award

Sri Padmavati Mahila VIsvavidyalayam | India

Dr. E. Ramesh Babu is an Assistant Professor in the Department of Computer Science & Engineering at the School of Engineering & Technology, ‎Sri Padmavati Mahila Visvavidyalayam, Tirupati. Holding a B.Tech and M.Tech in CSE from ‎Jawaharlal Nehru Technological University, Anantapur and currently pursuing a Ph.D. in Big Data Analytics at the same institution, he brings over a decade of academic experience at the college-level. His core research interests are in data mining, big data analytics and the Internet of Things. Over the years he has earned recognition including a Best Faculty Award from the ITSR Foundation and Best Oral/Poster/Best-Paper awards at national and international conferences. He has also authored book chapters, secured patents and led funded research projects spanning AI-driven systems, IoT monitoring and sustainable agriculture. With his ongoing engagement in teaching, supervision and publication, Dr. Ramesh Babu continues to contribute towards advancing computing research and cultivating student talent in emerging technologies.

Profile: Scopus

Featured Publication

Ramesh Babu, E., & Sunil Kumar, M. (2025). The role of optimization techniques in advancing big data analytics: A survey. Communications on Applied Nonlinear Analysis, 32(1S), 232–248.

Vaijayanthimala Jayavel | Artificial Intelligence | Best Researcher Award

Published-on by Indian Scientist

Dr. Vaijayanthimala Jayavel | Artificial Intelligence | Best Researcher Award

Dhirajlal Gandhi College of Technology| India

Dr. J. Vaijayanthimala is a dynamic academic and researcher recognized for her extensive contributions in computer science and engineering, particularly in artificial intelligence, image processing, sensor networks, and intelligent computing systems. Her Google Scholar profile records 16 total citations with an h-index of 2 and i10-index of 0, reflecting her growing scholarly influence across interdisciplinary domains. She has published widely in reputed journals including the ECS Journal of Solid State Science and Technology and Journal of The Electrochemical Society, with research spanning photonic biosensors, AI-based news aggregation, virtual reality accessibility, and smart agriculture. She has co-authored and authored multiple technical books on AI, machine learning, database systems, and data structures, demonstrating her commitment to quality education and knowledge dissemination. Her innovations include patents in automated voice recognition and eco-friendly 3D printing technology. A recipient of the “Innovative Technologist and Dedicated Teaching Professional Award,” she actively contributes as a reviewer for Springer Nature and Elsevier journals. With research interests that merge intelligence, automation, and sustainable technology, Dr. Vaijayanthimala continues to advance computational research and inspire the next generation of scholars.

Profile: Google Scholar

Featured Publications

Vaijayanthimala, J., Pon Bharathi, A., Ramkumar Raja, M., & Arun Kumar, U. (2024). Enhanced sensing of diseased blood samples through one-dimensional MgO-SiO2 photonic crystal sensor. Journal of The Electrochemical Society, 171(10), 107505.

V.M. Manish, J. Vaijayanthimala. (2014). Diminution of packet drop by efficient selection of network route in MANET. International Journal of Computer Science Information Technology (IJCSIT), 5, 1852–1855.

Vaijayanthimala, J., Vaishnavi, K., & Arun Kumar, U. (2025). High-sensitivity terahertz metasensor for cervical cancer diagnosis: Graphene modulation and XGBoost-assisted optimization. Sensors International, 2666–3511, Article 2666.

Vaijayanthimala, J., Alam, M.K., Shqaidef, A., & Mahmoud, O. (2024). Performance evaluation of refractive index biosensor in THz regime for clinical applications: A simulation approach. ECS Journal of Solid State Science and Technology, 13(10), 107005.

Vaijayanthimala, J., & Padma, T. (2019). Synthesis score level fusion based multifarious classifier for multi-biometrics applications. Journal of Medical Imaging and Health Informatics, 9(8), 1673–1680.

Sri Vasavi Chandu | Computer Science | Best Researcher Award

Published-on by Indian Scientist

Ms. Sri Vasavi Chandu | Computer Science | Best Researcher Award

SRM University AP, India

Author Profile

SCOPUS

🎓 EARLY ACADEMIC PURSUITS

Sri Vasavi Chandu began her academic journey in the field of Computer Science and Engineering with a consistent track record of academic excellence. During her undergraduate studies at SRM University, AP, she demonstrated a strong aptitude for core computing principles, programming, and data science. Her curiosity-driven approach during her formative years laid the foundation for her engagement in cutting-edge research, innovation projects, and interdisciplinary collaboration.

🏢 PROFESSIONAL ENDEAVORS

Chandu is currently an Associate Software Engineer at Accenture, where she works in the domain of SAP ABAP and SAP HANA. Her responsibilities include development, testing, and debugging of enterprise-level ABAP applications, working across modules such as Smart Forms, ALE, IDOC, ALV, Function Modules, CDS Views, and Object-Oriented Programming in SAP environments.

She has also interned with:

  • Oasis Infobyte Pvt. Ltd – where she developed responsive web pages using HTML, CSS, and JavaScript, aligning with modern frontend design practices.

  • SRM University Research Internship – contributing to advanced research in relation extraction using knowledge graphs.

  • Twowaits Technologies Pvt. Ltd – where she implemented a cryptography-based encryption-decryption tool and built structured assessment platforms using Python.

📚 CONTRIBUTIONS AND RESEARCH FOCUS IN COMPUTER SCIENCE

Chandu’s research interests span multiple domains in computer science, including:

  • Federated Learning

  • Natural Language Processing

  • Cybersecurity and Intrusion Detection

  • Machine Learning Algorithms

  • Knowledge Graphs and Information Retrieval

Her major projects include:

  • Fake News Detection using Federated Learning: Implemented advanced models like LSTM, BERT, and SVM, and deployed a verification website.

  • Music Genre Prediction using Machine Learning: Built multi-model classifiers and used PCA for effective dimensionality reduction.

  • ArtVista Art Gallery Website: Designed a dynamic, feedback-driven art portfolio website using frontend technologies.

  • Event Management System: Developed a backend-intensive platform using MySQL with optimized data storage.

  • Advanced Calculator: Built an intelligent calculator in Python supporting complex operations and robust error handling.

🏅 ACADEMIC CITATIONS, ACCOLADES AND RECOGNITION

Chandu has contributed to high-quality publications in reputable international journals and conferences:

  • 📄 “Federated Learning in the Detection of Fake News: A Survey” – Elsevier

  • 📄 “Evaluating the Effectiveness of Machine Learning Algorithms for Network Intrusion Detection” – Springer Nature

  • 📄 “A Survey on Extraction of Relations using Knowledge Graphs in Various Applications” – IEEE

She has also completed professional programs and certifications including:

  • J.P. Morgan Software Engineering Virtual Experience on Forage

  • 21st Century Core Employability Skills Certificate by Skill AP (APSSDC)

  • Participant in Microsoft’s AI Skills Fest, which contributed to a Guinness World Record

🌍 IMPACT AND INFLUENCE

Chandu’s work aligns with global needs for responsible AI, misinformation control, and decentralized data protection. By tackling contemporary issues like fake news detection and network security, she aims to develop transparent, ethical, and explainable AI models. Her participation in international platforms, including Microsoft’s AI Skills Fest, underscores her commitment to leveraging technology for societal good.

🧭 LEGACY AND FUTURE CONTRIBUTIONS

Sri Vasavi Chandu is driven by a vision to bridge academic research and real-world application. She is actively shaping her future contributions toward building secure, decentralized, and trustworthy AI systems. With an expanding portfolio of AI-driven solutions and a strong foundation in enterprise technologies, she is poised to contribute to:

  • Federated and Edge AI Systems

  • AI for Social Impact

  • Intelligent Information Extraction

  • Responsible Machine Learning Practices

 ✅CONCLUSION

A driven technologist, research contributor, and solution architect in the making, Sri Vasavi Chandu represents a new generation of engineers who combine technical depth with social consciousness. Her trajectory showcases a commitment to learning, interdisciplinary problem-solving, and real-world innovation. Her future promises impactful contributions across both academia and industry.

🔬NOTABLE PUBLICATION:

Federated Learning in the Detection of Fake News: A Survey
Author: Sri Vasavi Chandu
Journal: Elsevier
Year: 2025

Evaluating the Effectiveness of Machine Learning Algorithms for Network Intrusion Detection
Author: Sri Vasavi Chandu
Journal: Springer Nature Switzerland
Year: 2024

A Survey on Extraction of Relations using Knowledge Graphs in Various Applications
Author: Sri Vasavi Chandu
Journal: IEEE
Year: 2023

Deepika | Machine Learning | Best Researcher Award

Published-on by Indian Scientist

Ms. Deepika | Machine Learning | Best Researcher Award

The NorthCap University, India

Author Profile

ORCID

🎓 EARLY ACADEMIC PURSUITS

Ms. Deepika has consistently demonstrated academic excellence throughout her education. She holds a B.Tech in Computer Science Engineering from YMCA Institute of Engineering, where she ranked among the top three students in her batch. She went on to complete her M.Tech in Computer Science from Lingaya’s University, securing the second rank. She is currently pursuing a Ph.D. in Computer Science & Engineering at The NorthCap University, specializing in medical imaging and deep learning

🏢 PROFESSIONAL ENDEAVORS

Ms. Deepika brings over 5 years of corporate R&D experience from Ericsson Global India, where she worked as a Senior Solution Integrator. Her projects focused on telecom fault management, Netcool-based automation, and alarm handling systems. Her contributions in automating trouble ticketing and fault detection workflows earned her the Power Award and performance-based cash rewards. She displayed leadership in system integration, scripting, testing, and production support, translating technical expertise into tangible organizational benefits.

📚 CONTRIBUTIONS AND RESEARCH FOCUS IN MACHINE LEARNING

Ms. Deepika’s doctoral research lies at the convergence of machine learning, deep learning, and functional brain imaging for the diagnosis of neuropsychiatric disorders, particularly ADHD. Her contributions include:

  • Kolmogorov-Arnold Network (KAN) for parameter-efficient ADHD diagnosis

  • Hybrid metaheuristic–fuzzy logic systems for multi-disease classification

  • Multimodal neuroimaging frameworks utilizing fMRI, EEG, and structural MRI

  • Explainable AI (XAI) methods promoting interpretability and trust in medical AI

She is well-versed in cutting-edge tools like TensorFlow, PyTorch, Nilearn, FSL, SPM, and leverages advanced statistical and optimization techniques for robust model development.

🏅 ACADEMIC CITATIONS, ACCOLADES AND RECOGNITION

  • UGC-NET Qualified (Computer Science, 2018)

  • HTET Qualified (2016)

  • Awarded UGC Research Fellowship

  • Best Paper Awards at national and international conferences

  • Top Rank Holder in both undergraduate and postgraduate programs

  • Power Award and cash incentives from Ericsson for outstanding contributions

🌍 IMPACT AND INFLUENCE

Her research contributes significantly to the field of AI-driven healthcare diagnostics, focusing on low-parameter models and cross-platform compatibility for deployment in resource-constrained environments. Her work emphasizes biomarker discovery, data fusion, and interdisciplinary collaboration between AI and clinical neuroscience. She promotes standardization and reproducibility in neuroimaging-based machine learning, ensuring her models are accessible and implementable in real-world clinical settings.

🧭 LEGACY AND FUTURE CONTRIBUTIONS

Ms. Deepika aims to develop real-time, interpretable diagnostic tools integrating multi-modal brain data with scalable AI architectures. Her future research envisions:

  • Cross-disorder AI frameworks (e.g., ADHD, autism, depression)

  • Deployment-ready solutions for rural healthcare centers

  • Contribution to open-access neuroimaging repositories

  • Ethical and explainable AI models aligned with global health guidelines

She is committed to mentorship, capacity-building in AI for healthcare, and inclusive research practices.

 ✅CONCLUSION

Ms. Deepika represents a powerful blend of academic brilliance, industrial innovation, and societal impact. Her work bridges gaps between machine learning and medicine, offering transformative solutions for mental health diagnostics. With a clear vision and deep technical foundation, she is well-positioned to become a leading figure in neuro-AI research.

🔬NOTABLE PUBLICATION:

A Hybrid Metaheuristic–Fuzzy Logic-Based Framework for Robust ADHD and Multi-Disease Classification
Author(s): Deepika; Arora, S.; Sharma, M.
Journal: Iran Journal of Computer Science
Year: 2025

Multimodality Model Investigating the Impact of Brain Atlases, Connectivity Measures, and Dimensionality Reduction Techniques on Attention Deficit Hyperactivity Disorder Diagnosis Using Resting State Functional Connectivity
Author(s): Deepika; Sharma, M.; Arora, S.
Journal: Journal of Medical Imaging
Year: 2024

Machine Learning Advances in Diagnosing Attention Deficit and Hyperactivity Disorder
Author(s): Deepika; Sharma, M.; Arora, S.
Journal: 14th International Conference on Advances in Computing, Control, and Telecommunication Technologies (ACT 2023)
Year: 2023

Neuroimaging Based Automated Diagnosis of Attention Deficit and Hyperactivity Disorder Using Machine Learning Techniques
Author(s): Deepika
Journal: Hinweis Science and Engineering
Year: 2023