S.S.Subashka Ramesh | Medicinal Chemistry | Best Researcher Award-duplicate-1

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Dr. S.S. Subashka Ramesh | Data Science and Machine learning | Best Researcher Award

SRM Institute of Science and Technology india, India

Dr. S.S. Subashka Ramesh is an accomplished academic and researcher in Computer Science and Engineering with a strong foundation in advanced computing and data-driven technologies. Holding doctoral and postgraduate qualifications, she has extensive teaching and research experience, mentoring scholars and contributing to impactful innovations. Her research interests include machine learning, artificial intelligence, edge computing, and medical imaging. With notable publications, patents, and academic leadership, she has earned professional recognition and continues to advance knowledge through research, collaboration, and technology-driven solutions for real-world challenges.

Citation Metrics (Google Scholar)

700
500
20
10
0

Citations
641

h-index
11

i10index
13

Citations

h-index

i10-index

Featured Publications

Jeba Sonia J | Artificial Intelligence | Chemistry | Best Academic Researcher Award

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Dr. Jeba Sonia J | Artificial Intelligence | Chemistry | Best Academic Researcher Award

SRM Institute of Science and Technology, India

Dr. Jeba Sonia J is an accomplished academician and researcher in Computer Science and Engineering with extensive experience in teaching, mentoring, and curriculum development across undergraduate, postgraduate, and professional programs. Her academic background includes doctoral and postgraduate training in computer science. Her research interests span artificial intelligence, machine learning, deep learning, data science, computer networks, and wireless communications, with notable contributions through high-impact publications and patents. She has received prestigious fellowships, best paper recognition, and faculty excellence awards, demonstrating sustained excellence in research, teaching, and academic leadership.

Citation Metrics (Google Scholar)

220
160
10
5
0

Citations
209

h-index
8

i10index
7

Total Citations

h-index

i10-index

Featured Publications


Authentication of biometric system using fingerprint recognition with euclidean distance and neural network classifier


– International Journal of Innovative Technology and Exploring Engineering · Cited by 35


K-means clustering and SVM for plant leaf disease detection and classification


– International Conference on Recent Advances in Energy-efficient Technologies · Cited by 29


Green buildings and sustainable engineering


– Springer Transactions in Civil and Environmental Engineering · Cited by 15

Deepti Deshwal | Artificial Intelligence | Women Researcher Award

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Dr. Deepti Deshwal | Artificial Intelligence | Women Researcher Award

Maharaja Surajmal Institute of Technology New Delhi | India

Dr. Deepti Deshwal is an accomplished Assistant Professor in Electronics & Communication Engineering with extensive teaching experience and expertise in Artificial Intelligence, Machine Learning, speech processing, biomedical image analysis, and computer vision. She holds a Ph.D. in AI and has contributed significantly through SCI/SCIE publications, editorial roles, and funded research projects. Recognized with multiple research awards, she actively mentors Ph.D. students and fosters innovation through IPR initiatives, conferences, and technical workshops. Her work bridges academic excellence with practical AI applications, driving technology-driven societal impact.

Citation Metrics (Scopus)

350
300
20
10
0

Citations
306

h-index
9

Documents
22

Citations

h-index

Documents

Featured Publications


Economic analysis of lithium ion battery recycling in India


– Wireless Personal Communications · 64 citations · 2022


Feature extraction methods in language identification: a survey


– Wireless Personal Communications · 59 citations · 2019


Isolated word language identification system with hybrid features from a deep belief network


– International Journal of Communication Systems · 34 citations · 2023
Citation counts may vary across databases; links redirect to publisher pages or Google Scholar search results for accessibility.

Subhodeep Moitra | Artificial Intelligence | Young Researcher Award

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Mr. Subhodeep Moitra | Artificial Intelligence | Young Researcher Award

Techno College Hooghly | India

Subhodeep Moitra is a computer science researcher focused on advancing artificial intelligence through the fusion of human-like visual perception and cognition. His academic foundation spans computer applications at both undergraduate and postgraduate levels, where he built strong expertise in machine learning, deep learning, computer vision, neural networks, adversarial robustness, and cognitive modeling. His research explores self-supervised reconstruction, adversarial recovery, AGI-oriented theoretical computing, medical prediction systems, and environmental forecasting, with publications in journals, conferences, preprint platforms, and book chapters. He has contributed to projects ranging from temperature forecasting and brain-stroke detection to adversarially robust autoencoders and AGI theory. His professional experience includes serving as a visiting faculty member, teaching programming, mentoring research projects, and engaging in active collaborative work. His technical skills extend across Python, deep learning frameworks, MERN stack development, and cloud-based AI tools, supported by multiple certifications from NASA, NVIDIA, CERN, IBM, Oracle, and Coursera. He has presented papers at international conferences and earned best paper presentation awards for his contributions in machine learning–driven forecasting and adversarial perception. His long-term research interest lies in building unified AI systems capable of perceiving, reasoning, and adapting with human-inspired intelligence, aiming to push the boundaries of next-generation cognitive AI.

Profile: Google Scholar

Featured Publications

Moitra, S., & Banerjee, D. (n.d.). Robustness as Latent Symmetry: A Theoretical Framework for Semantic Recovery in Deep Learning. OSF.

Moitra, S., & Banerjee, D. (n.d.). Are We Even on the Right Track? A Theoretical Framework for AGI Beyond Classical Computation. Authorea Preprints.

Moitra, S., & Banerjee, D. (n.d.). Skip the Chaos: A Self-Supervised Learning-Powered Autoencoder for Adversarial Recovery. OSF.

Pintu, P., Subhodeep, M., & Deblina, B. (n.d.). The mystery of Neural Network: Linked with quantum mechanics and universe. ResearchGate.

Pal, P., Moitra, S., & Banerjee, D. (n.d.). The mystery of Neural Network: Linked with quantum mechanics and universe.

Runu Banerjee Roy | Artificial Intelligence | Best Researcher Award

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Dr. Runu Banerjee Roy | Artificial Intelligence | Best Researcher Award

Jadavpur University| India

Dr. Runu Banerjee Roy is a Professor in Instrumentation and Electronics Engineering at Jadavpur University, widely recognized for her contributions to electronic olfaction, taste sensing, molecular imprinting, sensor development, and artificial intelligence–based instrumentation. She has an extensive research profile with 1213 citations, an h-index of 17, and an i10-index of 25, reflecting her strong scholarly impact and research productivity. Her publication record includes more than 50 peer-reviewed journal papers, around 40 conference papers, multiple book chapters, and several patents that are granted, published, or filed. She has successfully guided doctoral and postgraduate research scholars and completed multiple sponsored research projects funded by major scientific agencies, focusing on portable sensing devices, electronic nose and tongue systems, and electrochemical detection technologies for applications in food quality and safety. In academics, she has served in leadership roles such as Head of Department, NBA accreditation coordinator, and curriculum committee member, contributing to program development and quality enhancement. Her work has earned recognition through competitive research awards, scientific prizes, and support for international research presentations. With strong expertise spanning instrumentation, intelligent sensing systems, and applied electronics, she continues to advance innovative research, academic excellence, and technology-driven solutions in modern sensor engineering.

Profile: Google Scholar | Scopus

Featured Publications

Roy, R. B., Tudu, B., Shaw, L., Jana, A., Bhattacharyya, N., & Bandyopadhyay, R. (2012). Instrumental testing of tea by combining the responses of electronic nose and tongue. Journal of Food Engineering, 110(3), 356–363.

Banerjee, M. B., Roy, R. B., Tudu, B., Bandyopadhyay, R., & Bhattacharyya, N. (2019). Black tea classification employing feature fusion of E-Nose and E-Tongue responses. Journal of Food Engineering, 244, 55–63.

Banerjee, R., Tudu, B., Bandyopadhyay, R., & Bhattacharyya, N. (2016). A review on combined odor and taste sensor systems. Journal of Food Engineering, 190, 10–21.

Roy, R. B., Chattopadhyay, P., Tudu, B., Bhattacharyya, N., & Bandyopadhyay, R. (2014). Artificial flavor perception of black tea using fusion of electronic nose and tongue response: A Bayesian statistical approach. Journal of Food Engineering, 142, 87–93.

Nag, S., Pradhan, S., Naskar, H., Roy, R. B., Tudu, B., Pramanik, P., … et al. (2021). A simple nano cerium oxide modified graphite electrode for electrochemical detection of formaldehyde in mushroom. IEEE Sensors Journal, 21(10), 12019–12026.

Shanmugam S | Machine Learning | Best Researcher Award

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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).

Major Singh Goraya | Computer Science | Best Researcher Award

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Prof. Major Singh Goraya | Computer Science | Best Researcher Award

Sant Longowal Institute of Engineering and Technology | India

Dr. Major Singh Goraya is a Professor in the Department of Computer Science and Engineering at Sant Longowal Institute of Engineering and Technology (SLIET), Longowal. He holds a Ph.D. from Punjabi University, complemented by strong academic foundations in computer engineering. His primary research areas include cloud computing, resource management, green computing, fault tolerance, and load balancing. With 27 Scopus-indexed publications, 460 citations across 399 documents, and an h-index of 10, Dr. Goraya has made consistent scholarly contributions to high-performance and sustainable computing. His studies have explored dynamic resource allocation, energy-efficient scheduling frameworks, and deep learning-based optimization techniques. He has supervised several Ph.D. and M.Tech. research scholars and continues to guide emerging researchers in cloud resource efficiency and intelligent computation. His international exposure through conferences in the UK, Canada, and Malaysia reflects his active engagement in global research forums. In addition, he has successfully organized numerous academic workshops, conferences, and training programs. Dr. Goraya’s innovative contributions strengthen the integration of artificial intelligence and cloud technology, promoting scalable and eco-efficient computational solutions that advance modern computer engineering research.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Goyal, N., Singh, T., & Goraya, M. S. (2025). Deep convolutional neural networks vs. vision transformers for video-based human activity recognition. In Proceedings of Lecture Notes in Computer Science (pp. xx–xx). Springer.

Singh, J., & Goraya, M. S. (2023). An autonomous multi-agent framework using quality of service to prevent service level agreement violations in cloud environment. International Journal of Advanced Computer Science and Applications, 14(3).

Goyal, N., Goraya, M. S., & Singh, T. (2023). An axiomatic analysis for object detection and recognition using deep learning. In Smart Innovation, Systems and Technologies (pp. xx–xx). Springer.

Thakur, A., & Goraya, M. S. (2022). A workload and machine categorization-based resource allocation framework for load balancing and balanced resource utilization in the cloud. International Journal of Grid and High Performance Computing, 14(2).

Hasan, M., Goraya, M. S., & Garg, T. (2022). E-FFTF: An extended framework for flexible fault tolerance in cloud. In Lecture Notes in Networks and Systems (pp. xx–xx). Springer.

Vaijayanthimala Jayavel | Artificial Intelligence | Best Researcher Award

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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.

Debashis Chatterjee | Artificial Intelligence | Young Researcher Award

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Assist. Prof. Dr. Debashis Chatterjee | Artificial Intelligence | Young Researcher Award

Visva Bharati University | India

Dr. Debashis Chatterjee is an Assistant Professor in the Department of Statistics at Visva-Bharati University, Santiniketan. He holds advanced degrees in Statistics from the Indian Statistical Institute and has contributed significantly to interdisciplinary applications of statistics in STEM disciplines. His work bridges statistical theory with practical applications in astronomy, biology, geology, and medical sciences. He has authored and supervised research focusing on Bayesian statistics, machine learning, and computational methods. With a strong academic background, teaching experience, and an active research profile, he continues to make meaningful contributions to the field of statistics and its applications across diverse domains.

Professional Profile

Google Scholar

Education

Dr. Debashis Chatterjee completed his Bachelor’s, Master’s, and Doctoral degrees in Statistics from the Indian Statistical Institute, one of the most prestigious institutions in the field. His studies were concentrated in the areas of mathematical statistics, probability, and interdisciplinary applications of statistical methods. His doctoral research focused on advanced statistical methodologies, combining theory with applications in areas like astronomy, earth sciences, and medical sciences. The rigorous training at ISI provided him with a strong foundation in both theoretical and applied statistics. This academic journey equipped him with the expertise to bridge statistical principles with complex real-world scientific challenges.

Professional Experience

Dr. Debashis Chatterjee serves as an Assistant Professor at Visva-Bharati University, where he has been actively engaged in teaching and research. He teaches a wide range of courses at undergraduate and postgraduate levels, covering topics in regression, statistical inference, real analysis, and linear algebra. Alongside classroom teaching, he supervises dissertation projects at both undergraduate and postgraduate levels, guiding students in applying advanced statistical techniques. His professional journey also includes mentoring PhD scholars and collaborating with researchers from diverse disciplines. With prior teaching and research involvement at the Indian Statistical Institute, he has developed a robust academic and professional portfolio.

Awards and Recognition

Dr. Debashis Chatterjee has been recognized for both his academic and teaching contributions. He has received awards for paper presentations at national academic forums and has been featured in leading newspapers for his impactful research on subjects like bird migration and earthquake prediction using statistical approaches. His excellence in teaching has also been acknowledged through honors based on student feedback. Earlier in his academic career, he achieved recognition in national-level Olympiads in mathematics and astronomy. These accolades reflect his ability to integrate statistical theory with practical challenges and his commitment to advancing both research and pedagogy in statistics.

Research Skills

Dr. Debashis Chatterjee possesses expertise in interdisciplinary statistical theory and its applications across astronomy, geology, biology, and medical sciences. His research interests include Bayesian statistics, machine learning, stochastic processes, and computational methods. He focuses on novel statistical methodologies applied to complex real-world scientific problems, including spatio-temporal modeling, geostatistics, astrostatistics, and bioinformatics. His work also explores artificial intelligence, probabilistic robotics, and applications of big data in genetics and astronomy. Skilled in both theoretical development and practical implementation, he integrates statistical learning with applied sciences, offering innovative solutions to pressing scientific and technological challenges. He also mentors research scholars in these areas.

Notable Publications

Whisperers of whales wander: A directional statistical investigation of whales’ migration influenced by geomagnetic, ocean current, and celestial cues
Author: D Chatterjee, P Ghosh
Journal: Journal for Nature Conservation, 127011
Year: 2025

On the directional nature of the fall of celestial objects on the surface of Venus
Author: D Chatterjee, P Ghosh
Journal: Planetary and Space Science, 106167
Year: 2025

A novel Bayesian approach based on wing geometric morphometry to discriminate Culicoides species (Diptera: Ceratopogonidae)
Author: N Banerjee, S Maitra Mazumdar, A Pal, D Chatterjee, A Mazumdar
Journal: Journal of Medical Entomology, tjaf082
Year: 2025

Circular insights for rhythmic health: A Bayesian approach with stochastic diffusion for characterizing human physiological rhythms with applications to arrhythmia detection
Author: D Chatterjee, S Saha, P Ghosh
Journal: PLOS ONE 20 (6), e0324741
Year: 2025

Bayesian hierarchical modeling of mucosal immune responses and growth efficiency in young animals: Demonstrating the superiority of data-dependent empirical priors
Author: D Chatterjee, P Ghosh
Journal: PLOS ONE 20 (6), e0326273
Year: 2025

Conclusion

Dr. Debashis Chatterjee’s career reflects a blend of strong academic training, impactful research, and dedicated teaching. His ability to link statistical theory with diverse scientific applications has positioned him as a versatile academic contributing across STEM disciplines. Through his teaching, he nurtures young statisticians, while his research advances the role of statistics in solving complex problems in natural and applied sciences. Recognized for his innovative contributions, he continues to expand the frontiers of interdisciplinary statistics. His achievements highlight his commitment to advancing both scholarship and pedagogy, reinforcing his role as a researcher, mentor, and educator in the statistical sciences.

Milind Cherukuri | Artificial Intelligence | Young Researcher Award

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Mr. Milind Cherukuri | Artificial Intelligence | Young Researcher Award

University of North Texas, India

Author Profile

ORCID

GOOGLE SCHOLAR

🎓 EARLY ACADEMIC PURSUITS

Milind Cherukuri’s academic journey began with a Bachelor’s in Computer Science from SRM University, Chennai (2015–2019), where he built a strong foundation in software engineering and algorithmic problem-solving. His pursuit of advanced knowledge led him to the University of North Texas, Dallas, where he completed his Master’s in Computer Science (2021–2022) with a focus on artificial intelligence, machine learning, and data systems.

🏢 PROFESSIONAL ENDEAVORS

Milind’s professional trajectory spans a blend of engineering rigor, AI research, and enterprise system design:

  • Caris Life Sciences (2025–Present)
    Role: Salesforce Business Analyst & Administrator
    Spearheading automation and optimization of clinical and research workflows, Milind integrates complex data systems and aligns AI tools with healthcare outcomes.

  • Amazon (2022–2024)
    Role: Software Engineer
    Engineered scalable microservices, improved customer personalization using AI, and contributed to global backend infrastructure, earning accolades for reliability and innovation.

  • Infor (2019–2021)
    Role: Software Engineer
    Led backend automation initiatives and research into NLP applications, with early contributions in recommendation systems and sentiment analysis pipelines.

📚 CONTRIBUTIONS AND RESEARCH FOCUS ON ARTIFICIAL INTELLIGENCE

Milind’s AI research is grounded in both theoretical depth and applied innovation. His key research themes include:

  • Sentiment Analysis & Emotion Modeling

  • Safe and Responsible Development of Large Language Models (LLMs)

  • Image Segmentation and Validation Tools for Web Structures

  • Prompt Engineering for LLM Optimization

He has published five peer-reviewed research papers, presented at premier conferences such as IEEE AI Summit and EEET 2024, and contributed tools like WebChecker, which enhances web development quality control.

🏅 ACADEMIC CITES, ACCOLADES AND RECOGNITION

  • Elevated to Senior Member of IEEE (2025)

  • Peer reviewer for leading journals, including JOBARI

  • Citations across platforms including IEEE Xplore, ResearchGate, and arXiv

  • Recognized internally by Amazon and Caris Life Sciences for exemplary technical contributions

  • Invited speaker at international AI research forums

🌍 IMPACT AND INFLUENCE

Milind’s work bridges AI with healthcare, e-commerce, and cloud ecosystems, showing measurable improvements:

  • 30% efficiency gain in Salesforce workflows at Caris Life Sciences

  • Millions of fault-tolerant requests/day enabled by backend systems at Amazon

  • Influenced global discussions on AI safety through groundbreaking presentations

He continues to influence both industry and academia through tool development, peer-review contributions, and community engagement.

🧭 LEGACY AND FUTURE CONTRIBUTIONS

Milind aims to build a safer, smarter, and ethically grounded AI ecosystem. His future research plans focus on:

  • Explainable AI in healthcare diagnostics

  • Open-source tools for LLM safety benchmarking

  • Sustainable AI development aligning with ESG goals

He envisions fostering innovation at the crossroads of healthcare, AI, and policy, mentoring the next generation of AI practitioners and building intelligent systems that serve humanity.

 ✅CONCLUSION

Mr. Milind Cherukuri stands out as a technologist, researcher, and thought leader, bridging cutting-edge AI with practical impact. With a track record of academic brilliance, engineering excellence, and ethical AI advocacy, he continues to leave a mark on research, innovation, and global digital transformation.

 🔬NOTABLE PUBLICATION:

Title: Comparing Image Segmentation Algorithms

Author: M. Cherukuri
Journal/Conference: 2024 IEEE 4th International Conference on Data Science and Computer Applications (ICDSCA)
Year: 2024

Title: Cost, Complexity, and Efficacy of Prompt Engineering Techniques for Large Language Models

Author: M. Cherukuri
Journal/Conference: International Journal on Science and Technology
Year: 2025

Title: WebChecker: A Versatile EVL Plugin for Validating HTML Pages with Bootstrap Frameworks

Author: M. Cherukuri
Journal/Conference: arXiv preprint arXiv:2502.07479
Year: 2025

Title: Advancing AI Safely: Frameworks and Strategies for the Development of GPT-5 and Beyond

Author: M. Cherukuri
Journal/Conference: ResearchGate Preprint
Year: 2025

Title: Exploring Multi-Dimensional Sentiment Analysis: A Study on Emotion Representation Structures and Prediction Models

Author: M. Cherukuri
Journal/Conference: REST Journal on Data Analytics and Artificial Intelligence
Volume: 3, Pages 55–76
Year: 2024