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

Published-on by Indian Scientist

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

Padmini Sankaramurthy | Energy | Research Excellence Award

Published-on by Indian Scientist

Dr. Padmini Sankaramurthy | Energy | Research Excellence Award

SRM Institute of Science and Technology | India

Dr. S. Padmini is an accomplished academic and researcher with a strong foundation in Electrical and Electronics Engineering, advanced training in Power Systems Engineering, and doctoral work centered on intelligent algorithms for hydrothermal scheduling, further strengthened by an ongoing postdoctoral fellowship in multidisciplinary AI applications. With extensive teaching and research experience in a premier institution, she has contributed significantly to curriculum development, research supervision, academic leadership, and large-scale institutional activities. Her scholarly output includes publications indexed in major databases, patents, major project proposals, international collaborations, and diverse technical contributions across intelligent systems, power systems optimization, energy economics, and AI-driven engineering solutions. She has delivered numerous courses, created substantial digital learning resources, and guided students at multiple academic levels. Her research has earned citations totalling 341, along with an h-index of 10 and an i10-index of 10, demonstrating meaningful global impact. She is recognized for excellence through multiple awards, including distinguished scientific honours, innovation-driven recognitions, and accolades for academic contributions. Her ongoing collaborations across global universities reflect her commitment to advancing multidisciplinary research. Dr. Padmini’s work continues to integrate engineering intelligence, sustainable energy solutions, and advanced computational methods to support emerging technological needs and societal progress.

Profiles: Google Scholar | Orcid | Scopus

Featured Publication

Jeevadason, A. W., Padmini, S., Bharatiraja, C., & Kabeel, A. E. (2022). A review on diverse combinations and Energy-Exergy-Economics (3E) of hybrid solar still desalination. Desalination, 527, 115587.

Rebecca, B., Kumar, K. P. M., Padmini, S., Srivastava, B. K., Halder, S., & Boopathi, S. (2024). Convergence of Data Science-AI-Green Chemistry-Affordable Medicine: Transforming Drug Discovery. In Handbook of Research on AI and ML for Intelligent Machines and Systems (pp. 348–373).

Venkatesh, B., Sankaramurthy, P., Chokkalingam, B., & Mihet-Popa, L. (2022). Managing the demand in a micro grid based on load shifting with controllable devices using hybrid WFS2ACSO technique. Energies, 15(3), 790.

Lakshmi, K., Amaran, S., Subbulakshmi, G., Padmini, S., Joshi, G. P., & Cho, W. (2025). Explainable artificial intelligence with UNet based segmentation and Bayesian machine learning for classification of brain tumors using MRI images. Scientific Reports, 15(1), 690.

Sankaramurthy, P., Chokkalingam, B., Padmanaban, S., Leonowicz, Z., … Padmini, S. (2019). Rescheduling of generators with pumped hydro storage units to relieve congestion incorporating flower pollination optimization. Energies, 12(8), 1477.

Subhodeep Moitra | Artificial Intelligence | Young Researcher Award

Published-on by Indian Scientist

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.

Milind Cherukuri | Artificial Intelligence | Young Researcher Award

Published-on by Indian Scientist

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