Rajesh D | Artificial Intelligence | Best Academic Researcher Award

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Dr. Rajesh D | Artificial Intelligence | Best Academic Researcher Award

National Council of Educational Research and Training | India

Dr. Rajesh D is an Associate Professor and senior academic leader with extensive experience in ICT, information security, and educational technology. His academic background spans computer science and information technology, complemented by professional certifications in data science, Python, and AI for education. With significant teaching and research experience, his work focuses on knowledge discovery, data analytics, AI-driven learning systems, and ICT for inclusive education. His research contributions, patents, publications, and national-level recognitions highlight his impact on technology-enabled education and cyber security leadership.

Research Profile : Orcid

Featured Publications

Doss, R. (2024). Quasi oppositional Jaya algorithm with computer vision based deep learning model for emotion recognition on autonomous vehicle drivers. Journal of Intelligent Systems and Internet of Things. https://doi.org/10.54216/jisiot.140111

Doss, R. (2024). A study on the implications of ensemble learning for education in India. International Journal of All Research Education & Scientific Methods.

Doss, R. (2023). A study of distance education to enhance employability of students in higher education. International Journal of Research Publication and Reviews.

Doss, R. (2023, July 26). Classification and characterization of internet worms for automatic containment. In Multi-Disciplinary Research and Practice (Conference proceedings).

Raja, S., Manikandasaran, S. S., & Doss, R. (2022). Threat modeling and IoT attack surfaces. In Innovations in Communication and Computing. Springer. https://doi.org/10.1007/978-3-030-66607-1_11

Sivakamasundari | Computer Science | Best Researcher Award

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Ms. Sivakamasundari | Computer Science | Best Researcher Award

SRM Institute of Science and Technology | India

Ms. P. Sivakamasundari is a dedicated academic and researcher in Computer Science and Engineering, recognized for her contributions to deep learning-based medical image analysis. With qualifications spanning Diploma, Bachelor’s, and Master’s degrees in Computer Science and Engineering, she is currently pursuing her Ph.D. at SRM Institute of Science and Technology. She has extensive teaching experience as an Assistant Professor for more than a decade, during which she has guided students in core computing subjects including algorithms, computation theory, compiler design, and image classification. Her research focuses on advanced deep learning frameworks for healthcare applications, particularly diabetic retinopathy and diabetic foot ulcer detection, resulting in book chapters, conference publications, and journal manuscripts under review. She has published and filed patents related to medical imaging and automated disease detection systems, demonstrating her innovation-driven approach. Her scholarly presence includes 1 citation, 1 h-index, and 0 i10-index, indicating emerging research visibility. She has completed multiple professional certifications and participated in workshops, FDPs, and internships in machine learning, biometrics, accelerated computing, and high-performance healthcare analytics. Her work reflects strong commitment toward applying AI for societal benefit, and she continues to advance her expertise through active research and academic contributions.

Profile: Google Scholar

Featured Publications

Sivakamasundari, P., Anandhi, S., Kumaran, A. A., Vijayakumar, K., Birnica, Y. J., & others. (2024). Early detection of glaucoma utilizing retinal nerve fiber layer (RNFL) investigation. International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems.

Sivakamasundari, P., & Niranjana, G. (2025). An automatic detection and classification of diabetic foot ulcers using Chebyshev chaotic ladybug beetle optimized extended Swin Transformer–InceptionV3 model. Biomedical Signal Processing and Control, 110, 108268.

Gomathi, G., Sumathy, V., Sivakamasundari, P., & Deepa, R. (2024). A various approaches of machine learning algorithms for kidney disease prediction. International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems.

Sivakamasundari, P., & Niranjana, G. (2024). Diabetic foot ulcer classification using deep learning approach. International Conference on Computer, Communication and Signal Processing (ICCCSP).

Sivakamasundari, P., & Niranjana, G. (2023). A critique on deep learning methodologies employed for the identification of diabetic retinopathy using fundus images. Intelligent Computing and Control for Engineering and Business Systems (ICCEBS).

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.

Bappa Mukherjee | Artificial Intelligence | Best Researcher Award

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Dr. Bappa Mukherjee | Artificial Intelligence | Best Researcher Award

Wadia Institute of Himalayan Geology, Dehradun | India

Prof. Motireddy Srinivasulu Reddy is a distinguished academician and researcher recognized for his impactful work in toxicology. He has contributed significantly to advancing knowledge in the field through teaching, research, and scholarly publications. With a strong commitment to academic excellence, he has guided numerous students and inspired them toward scientific inquiry. His professional journey reflects dedication, innovation, and leadership in research. Prof. Reddy has earned respect in the academic community for his integrity and contributions to science, making him a role model for aspiring researchers. His work continues to benefit both academia and society at large.

Professional Profiles

Scopus | Orcid

Education

Prof. Motireddy Srinivasulu Reddy pursued higher education in the field of science and specialized in toxicology. His academic journey provided him with strong theoretical foundations and practical expertise in analyzing chemical substances and their impact on living organisms. Through rigorous academic training, he developed an in-depth understanding of toxicological processes and advanced laboratory techniques. His education laid the groundwork for his research career, where he applied scientific methodologies to address real-world problems. He has continuously expanded his knowledge base through academic research, publications, and collaborations, reflecting his dedication to lifelong learning and excellence in scientific advancement.

Professional Experience

Prof. Motireddy Srinivasulu Reddy has gained extensive professional experience as a researcher, educator, and mentor. He has been actively engaged in teaching, guiding students in toxicology, and contributing to curriculum development in the field of science. His research has focused on analyzing toxic substances, studying their environmental and health impacts, and proposing innovative solutions. Alongside academic roles, he has contributed to scientific forums, conferences, and collaborative research initiatives. His professional experience demonstrates a balance between teaching, research, and service, making him an integral contributor to academic institutions and scientific communities committed to advancing toxicological studies.

Awards and Recognition

Prof. Motireddy Srinivasulu Reddy has received awards and recognition for his valuable contributions in toxicology and scientific research. His achievements highlight his dedication to innovation and knowledge dissemination within the academic and research community. He has been honored for his outstanding performance in research, publications, and scholarly impact. Such recognitions reflect the high regard his peers hold for his expertise and commitment to excellence. These awards not only validate his academic and research efforts but also encourage him to continue contributing toward solving scientific challenges. His recognition demonstrates the significance of his role in advancing toxicology.

Research Skills

Prof. Motireddy Srinivasulu Reddy possesses strong research skills in toxicology, focusing on the analysis of chemical effects, biological interactions, and environmental implications. His expertise includes conducting laboratory experiments, applying advanced methodologies, and interpreting scientific data to derive meaningful outcomes. He is proficient in designing research frameworks, identifying innovative solutions, and contributing to evidence-based scientific knowledge. His ability to integrate theoretical principles with practical approaches has enabled him to publish impactful work. Additionally, his skills extend to mentoring students and guiding them in developing their research potential, thereby strengthening the academic and scientific research community.

Notable Publications

Earthquake prediction using machine learning perspectives in Himalayan seismic belt and its surroundings
Author: Bappa Mukherjee, Ritesh Lal Shaw, Mukat Lal Sharma, Kalachand Sain
Journal: Journal of Asian Earth Sciences
Year: 2025

3D U-Net assisted fault probability prediction from seismic volume in Dibrugarh oil field, upper Assam shelf, NE India
Author: Bappa Mukherjee, Soumitra Kar, Kalachand Sain
Journal: Physics and Chemistry of the Earth, Parts A/B/C
Year: 2025

Machine learning assisted crustal velocity proxy: A case study over the Tibetan Plateau and its surroundings
Author: Bappa Mukherjee, P.K. Gautam, Kalachand Sain
Journal: Journal of Asian Earth Sciences
Year: 2024

Machine learning assisted gas hydrate saturation proxy: A case study from KG basin, India
Author: S. Konar, Bappa Mukherjee, Kalachand Sain
Journal: Himalayan Geology
Year: 2024

Conclusion

Prof. Motireddy Srinivasulu Reddy has established himself as a respected figure in academia and research through his dedication to toxicology and scientific excellence. His educational background, professional experience, awards, and research skills demonstrate his commitment to advancing the frontiers of knowledge. By contributing to teaching, research, and mentoring, he has played an essential role in shaping the future of students and researchers. His work serves as an inspiration for the academic community, reflecting values of hard work, integrity, and innovation. Prof. Reddy continues to be a driving force in advancing scientific inquiry and societal development.

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.

Pritam BIKRAM | Artificial Intelligence | Best Researcher Award

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Mr. Pritam BIKRAM | Artificial Intelligence | Best Researcher Award

Indian Institute of Engineering Science and Technology, Shibpur, India

Author Profile

SCOPUS

ORCID

GOOGLE SCHOLAR

🎓 EARLY ACADEMIC PURSUITS

Mr. Pritam Bikram began his academic journey with a B.Tech in Information Technology from the Government College of Engineering and Leather Technology, graduating in 2020. With a strong foundation in computational systems and programming, he advanced his studies by pursuing an M.Tech in Information Technology at the prestigious Indian Institute of Engineering Science and Technology (IIEST). His dedication and academic excellence earned him a GATE scholarship during this period. Currently, he is pursuing his Ph.D. at IIEST, where his research is focused on advanced applications of Artificial Intelligence (AI) in real-world domains.

🏢 PROFESSIONAL ENDEAVORS

Throughout his academic tenure, Mr. Bikram has remained consistently involved in cutting-edge research and collaborative scientific inquiry. Working under a result-oriented and interdisciplinary professional environment, he has contributed to the development of novel AI-based solutions in Intelligent Transportation Systems (ITS), remote sensing, environmental monitoring, and precision agriculture. His analytical mindset and logical problem-solving approach have enabled him to tackle multifaceted challenges across domains.

📚 CONTRIBUTIONS AND RESEARCH FOCUS IN ARTIFICIAL INTELLIGENCE

Mr. Bikram’s core research lies in the realm of Artificial Intelligence, with specific focus areas including:

  • Trajectory prediction using graph neural networks

  • Missing spatio-temporal data imputation

  • Deep learning applications for traffic forecasting

  • AI-driven spectral analysis for crop disease monitoring

His work is characterized by graph-based encoder-decoder learning frameworks, attentive graph structure learning, and dynamic attention mechanisms, reflecting a deep command over neural architectures and real-world data-driven applications.

🏅 ACADEMIC CITATIONS, ACCOLADES AND RECOGNITION

Mr. Bikram is the first author of multiple high-impact peer-reviewed journal articles, including:

  • Expert Systems with Applications (Elsevier, 2025)

  • Neurocomputing (Elsevier, 2024)

  • Applied Intelligence (Springer, 2024)

  • Remote Sensing Applications: Society and Environment (Elsevier, 2025)

His research has begun gaining strong academic traction and citations, contributing to the broader scientific discourse in AI and its applications. He has also received:

  • 🎓 GATE Scholarship (2020)

  • 🧠 Ph.D. Institute Scholarship (2022)

🌍 IMPACT AND INFLUENCE

Mr. Bikram’s contributions have significant implications for smart city development, environmental sustainability, and agritech innovations. His models have demonstrated real-world applicability in enhancing urban mobility, early disease detection in agriculture, and data imputation for intelligent decision-making systems. By addressing societal challenges with AI, he continues to drive forward impactful and sustainable technological solutions.

🧭 LEGACY AND FUTURE CONTRIBUTIONS

Looking ahead, Mr. Bikram envisions integrating interdisciplinary AI methodologies with climate science, transportation modeling, and remote sensing technologies. His role as a reviewer for esteemed journals like Knowledge-Based Systems, Neurocomputing, Applied Intelligence, and IEEE Transactions on Intelligent Vehicles marks him as a thought leader shaping future research directions.

He is also preparing to become an IEEE Member (December 2025), aligning with a global network of innovators.

 ✅CONCLUSION

With a powerful combination of technical expertise, research depth, and real-world problem-solving focus, Mr. Pritam Bikram stands as an emerging scholar in the Artificial Intelligence community. His contributions are expected to influence diverse fields from urban mobility to climate-resilient agriculture, leaving a lasting legacy.

🔬NOTABLE PUBLICATION:

Effective message-passing scheme and aggregation technique embedded in graph-based encoder-decoder learning framework for trajectory prediction
Author(s): Pritam Bikram, Shubhajyoti Das, Arindam Biswas
Journal: Expert Systems with Applications
Year: 2025

Multilayer optimized deep learning model to analyze spectral indices for predicting the condition of rice blast disease
Author(s): Shubhajyoti Das, Pritam Bikram, Arindam Biswas, Vimalkumar C., Parimal Sinha
Journal: Remote Sensing Applications: Society and Environment
Year: 2025

Dynamic attention aggregated missing spatial–temporal data imputation for traffic speed prediction
Author(s): Pritam Bikram, Shubhajyoti Das, Arindam Biswas
Journal: Neurocomputing
Year: 2024

Attentive graph structure learning embedded in deep spatial-temporal graph neural network for traffic forecasting
Author(s): Pritam Bikram, Shubhajyoti Das, Arindam Biswas
Journal: Applied Intelligence
Year: 2024