Surjit Bhai | Computational Chemistry | Innovative Research Award

Published-on by Indian Scientist

Innovative Research Award

Surjit Bhai
Assam down town University

Surjit Bhai
Affiliation Assam down town University
Country India
Scholar ID 74fJslYAAAAJ
Documents 18
Citations 126
h-index 6
Subject Area Computational Chemistry
Event Indian Scientist Awards

Surjit Bhai is an academic researcher affiliated with Assam down town University, India. His research activities are primarily associated with Computational Chemistry, an interdisciplinary field integrating chemistry, mathematics, physics, and computer science to investigate molecular structures, chemical processes, and predictive scientific models. His documented scholarly record reflects sustained academic engagement through publications, citations, and research dissemination activities that contribute to the advancement of computational and theoretical chemical sciences.[1]

Abstract

The Innovative Research Award recognizes scholarly contributions that demonstrate originality, scientific relevance, and sustained academic productivity. Surjit Bhai’s research profile highlights active participation in Computational Chemistry, supported by a measurable publication record and citation impact. His academic contributions align with contemporary research priorities involving computational modeling, molecular simulations, and theoretical investigations that support scientific discovery and technological advancement.[1][2]

Keywords

Computational Chemistry; Molecular Modeling; Chemical Informatics; Quantum Chemistry; Scientific Computing; Innovative Research; Theoretical Chemistry; Research Excellence; Chemical Simulations; Academic Scholarship.

Introduction

Computational Chemistry has emerged as a critical scientific discipline that enables researchers to investigate molecular behavior and chemical interactions through computational methods. The field contributes significantly to materials science, pharmaceutical research, environmental studies, and molecular engineering. Recognition programs such as the Innovative Research Award acknowledge researchers whose scholarly efforts contribute to expanding scientific understanding and innovation within these domains.[2]

Research Profile

According to available scholarly metrics, Surjit Bhai has produced eighteen documented research publications and accumulated one hundred twenty-six citations, with an h-index of six. These indicators reflect academic visibility and engagement within the scientific community. His research interests focus on computational approaches to chemical analysis, molecular systems, and theoretical investigations that support scientific advancement.[1]

  • Research specialization in Computational Chemistry.
  • Experience in molecular modeling and computational analysis.
  • Contribution to peer-reviewed scientific literature.
  • Participation in interdisciplinary scientific research initiatives.

Research Contributions

The research contributions associated with Surjit Bhai emphasize the application of computational techniques to investigate chemical structures, reaction mechanisms, and molecular properties. Such work supports efficient scientific experimentation by complementing laboratory-based investigations with predictive computational frameworks. Computational Chemistry continues to play an important role in accelerating scientific discovery and reducing experimental complexity across multiple disciplines.[2][3]

  • Computational investigation of molecular systems.
  • Development and application of theoretical chemical models.
  • Support for data-driven scientific analysis.
  • Contribution to interdisciplinary computational research.

Publications

The researcher’s publication portfolio reflects continued scholarly engagement and participation in academic communication. Published works contribute to the dissemination of scientific knowledge and provide opportunities for peer review, validation, and future research development.[1]

  1. Peer-reviewed journal articles in Computational Chemistry.
  2. Research papers involving molecular simulations and theoretical studies.
  3. Conference publications and scientific communications.
  4. Collaborative interdisciplinary research outputs.

Research Impact

Citation-based indicators provide one perspective on scholarly influence and visibility. The research profile associated with Surjit Bhai demonstrates measurable academic impact through citation activity and publication performance. These indicators suggest that his work contributes to ongoing scientific discussions and supports further investigations within Computational Chemistry and related disciplines.[1]

Award Suitability

The Innovative Research Award recognizes originality, scientific rigor, and meaningful scholarly contributions. Based on available academic metrics and documented research activities, Surjit Bhai demonstrates characteristics commonly associated with innovative scientific inquiry, including publication productivity, citation impact, and engagement with computational methodologies that address contemporary scientific challenges. These attributes support consideration for recognition within research excellence programs.[1][4]

Conclusion

Surjit Bhai’s academic profile reflects continued contributions to Computational Chemistry through scholarly publication, citation impact, and research engagement. His work contributes to the broader advancement of computational scientific methodologies and supports knowledge development within chemistry-related disciplines. The Innovative Research Award provides an appropriate framework for recognizing such contributions and encouraging future academic achievements.[1]

References

  1. Google Scholar. (n.d.). Scholar profile: Surjit Bhai, Scholar ID 74fJslYAAAAJ. https://scholar.google.com/citations?user=74fJslYAAAAJ&hl=en
  2. Recyclable Functionalized Material for Sensitive Detection and Exceptional Sorption of Hexavalent Chromium and Permanganate Ions with Biosensing ApplicationsClick to copy article link. https://pubs.acs.org/doi/abs/10.1021/acsabm.1c00609
  3. Estimation of bisulfate in edible plant foods, dog urine, and drugs: picomolar level detection and bio-imaging in living organisms†
    https://pubs.rsc.org/en/content/articlelanding/2017/vz/c9an01078e/unauth
  4. Probing the Interaction of Nucleobases and Fluorophore-Tagged Nucleobases with Graphene Surface: Adsorption and Fluorescence Studies.
    https://chemistry-europe.onlinelibrary.wiley.com/doi/abs/10.1002/slct.201904442

Kumar Rahul | Artificial Intelligence | Innovative Research Award

Published-on by Indian Scientist

Dr. Kumar Rahul | Artificial Intelligence | Innovative Research Award

NIFTEM | India

Dr. Kumar Rahul is an Assistant Professor in the Department of Interdisciplinary Sciences at the National Institute of Food Technology Entrepreneurship and Management (NIFTEM), Sonepat, combining his expertise in software engineering, big-data analytics and food-technology research. With a Ph.D. in Computer Science and Engineering focused on enhanced data cleaning and outlier-detection using hybrid meta-heuristics, and earlier degrees in software engineering (M.E.) and computer applications (BCA/MCA), his career spans roles in both academia and engineering. He has authored numerous peer-reviewed articles (including systematic reviews on big-data/AI, applications of AI and ML in food-industry and healthcare, hybrid meta-heuristic models, data-cleaning frameworks) and holds patents in sensor-network water-quality monitoring and deep–learning corner-detection algorithms. His Google Scholar h-index stands at 10 with over 500 citations, reflecting his growing research impact. His research interests include artificial intelligence and machine learning for food processing, big-data analytics and industrial systems, IoT/Edge–Fog–Cloud applications, and optimization/meta-heuristic techniques for outlier or anomaly detection. He has also contributed to applied projects such as mobile-app development for fruit-freshness checking and served as Co-PI on a funded initiative in the food-technology domain. His work has been recognised through awards including UGC-NET (LS) and strong GATE performance, and he actively participates in faculty development programs and serves as a resource-person on topics such as IoT in industries and agri-startups. In summary, Dr. Rahul brings a multidisciplinary blend of computer-science rigor and domain-specific application in food-technology, making him a valuable contributor to research and education in smart food systems and analytics.

Profile: Scopus

Featured Publications

Rahul, K., & Banyal, R. K. (Erratum). Retraction Note: Firefly algorithm: an optimization solution in big data processing for the healthcare and engineering sector [Retraction note]. International Journal of Speech Technology, 24(3), 581–592. https://doi.org/10.1007/s10772-020-09783-y

Rahul, K., Arora, N., & Arora, S. (2025). Effectiveness of blockchain and IoT in horticulture crop supply chain. In B. Sharma, D.-T. Do, S. N. Sur, & C.-M. Liu (Eds.), Advances in Communication, Devices and Networking. Springer Nature.

Major Singh Goraya | Computer Science | Best Researcher Award

Published-on by Indian Scientist

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.