Nitin Goyal | Computer Science | Best Researcher Award

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Dr. Nitin Goyal | Computer Science | Best Researcher Award

Assistant Professor | Central University of Haryana | India

Dr. Nitin Goyal is a distinguished academic and researcher in the field of Computer Science and Engineering, recognized for his extensive contributions to advanced computing technologies, underwater wireless sensor networks (UWSN), and intelligent communication systems. With a robust academic foundation and over sixteen years of professional experience, he has established a prolific research profile encompassing artificial intelligence, machine learning, deep learning, Internet of Things (IoT), and wireless sensor networks (WSN). Dr. Nitin Goyal has authored more than 175 research papers, including 90 SCI-indexed, 15 Scopus-indexed, 15 book chapters, and numerous conference proceedings, reflecting his commitment to high-impact scientific dissemination. His innovative work has led to the filing of 30 patents, with 20 already granted, demonstrating his drive for technological advancement and innovation. As an editor and contributor to multiple international books published by CRC Press, IGI Global, and Cambridge Scholars, he plays a vital role in bridging research and industry applications. His active engagement as a reviewer, editorial board member, and guest editor for renowned SCI journals such as Scientific Reports (Nature) and CMC – Computers, Materials & Continua further emphasizes his scholarly leadership. Dr. Nitin Goyal research excellence has been recognized globally through awards such as the Best Researcher Award and his inclusion in the list of the world’s top 2% scientists by Elsevier. His recent works on AI-driven pest classification, privacy-preserving frameworks, and intelligent anti-phishing models underscore his continuous pursuit of innovation for sustainable and secure technological ecosystems. 3,747 Citations by 2,904 documents, 128 Documents, 35 h-index.

Profiles: Scopus | Orcid | Google Scholar | Researchgate | LinkedIn 

Featured Publications

Trivedi, N. K., Gautam, V., Anand, A., Aljahdali, H. M., Villar, S. G., Anand, D., … (2021). Early detection and classification of tomato leaf disease using high-performance deep neural network. Sensors, 21(23), 7987.

Kumar, A., Sharma, S., Goyal, N., Singh, A., Cheng, X., & Singh, P. (2021). Secure and energy-efficient smart building architecture with emerging technology IoT. Computer Communications, 176, 207–217.

Lilhore, U. K., Imoize, A. L., Li, C. T., Simaiya, S., Pani, S. K., Goyal, N., Kumar, A., … (2022). Design and implementation of an ML and IoT based adaptive traffic-management system for smart cities. Sensors, 22(8), 2908.

Chaudhary, M., Goyal, N., Benslimane, A., Awasthi, L. K., Alwadain, A., & Singh, A. (2022). Underwater wireless sensor networks: Enabling technologies for node deployment and data collection challenges. IEEE Internet of Things Journal, 1.

Goyal, N., Dave, M., & Verma, A. K. (2020). SAPDA: Secure authentication with protected data aggregation scheme for improving QoS in scalable and survivable UWSNs. Wireless Personal Communications, 113(1), 1–15.

Fayaz Ali Dharejo | Computer Vision | Best Researcher Award

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Dr. Fayaz Ali Dharejo | Computer Vision | Best Researcher Award

University of Wurzburg | Germany

Dr. Fayaz Ali Dharejo is a postdoctoral researcher specializing in computer vision, medical image analysis, image reconstruction, and super-resolution. With research spanning remote sensing, underwater imaging, and AI-powered medical applications, he has contributed extensively to advancing intelligent image processing systems. His academic journey and professional expertise span multiple countries, including China, Germany, and the UAE. He has authored numerous high-impact journal and conference papers, delivered international talks, and mentored graduate students globally. As a senior IEEE member and ACM member, Dr. Dharejo is committed to pushing technological frontiers while fostering collaborations between academia and industry.

Professional Profile

Scopus

Orcid

Google Scholar

Education

Dr. Fayaz Ali Dharejo earned his Ph.D. in Computer Applied Technology from the University of Chinese Academy of Sciences, focusing on remote sensing image dehazing and super-resolution using traditional and deep learning algorithms. He holds a Master’s in Software Engineering from the University of Electronic Science and Technology of China, where he researched human action recognition in videos. His academic foundation began with a Bachelor’s in Electronics Engineering from Quaid-E-Awam University of Engineering, Sciences and Technology, working on real-time face recognition using MATLAB. This multidisciplinary education built his expertise in computer vision, machine learning, and advanced image analysis.

Experience

Dr. Dharejo has held postdoctoral research positions at Julius Maximilian University of Würzburg, Germany, and Khalifa University, Abu Dhabi, specializing in computer vision and AI-driven image reconstruction. His earlier roles include Graduate Researcher and Teaching Assistant at the Chinese Academy of Sciences, Beijing, and Lecturer in Electrical Engineering at Indus University, Karachi. He has taught courses in computer vision, image processing, deep learning, and signal processing across undergraduate and postgraduate levels. Dr. Dharejo has also supervised master’s and doctoral research projects in areas such as semantic segmentation, anomaly detection, and AI-powered agriculture, contributing to interdisciplinary advancements.

Research Interests

Dr. Dharejo’s research interests center on computer vision, medical image analysis, remote sensing, image dehazing, and super-resolution techniques. He works extensively with deep learning, transformer architectures, and wavelet transforms to solve image reconstruction challenges in complex environments, including underwater and medical imaging scenarios. His work also extends to activity recognition, federated learning, and AI applications in the metaverse. Dr. Dharejo aims to develop efficient, lightweight, and scalable models for real-time deployment on edge devices, with a strong emphasis on interdisciplinary applications bridging healthcare, environmental monitoring, and autonomous systems.

Awards

Dr. Dharejo has received numerous honors, including the International Excellent Graduate Award from the University of Chinese Academy of Sciences, CSC Outstanding International Award from the Ministry of Education of China, and multiple academic excellence awards from Chinese and Pakistani institutions. He earned prestigious fellowships such as the CAS-TWAS President Fellowship for his Ph.D. and the Chinese Government Scholarship for his Master’s degree. His achievements also include recognition in research excellence, travel grants for presenting at IEEE conferences, and competitive international research funding. These accolades underscore his contributions to advancing AI-driven imaging technologies globally.

Top Noted Publications

Title: AI and 6G into the metaverse: Fundamentals, challenges and future research trends
Year: 2024
Cited by: 140

Title: LBPH based improved face recognition at low resolution
Year: 2018
Cited by: 119

Title: LBPH-based enhanced real-time face recognition
Year: 2019
Cited by: 118

Title: Wavelet-based enhanced medical image super resolution
Year: 2020
Cited by: 53

Title: Two-dimensional displacement optical fiber sensor based on macro-bending effect
Year: 2019
Cited by: 44

Conclusion

Dr. Fayaz Ali Dharejo’s prolific publication record, international collaborations, academic leadership, and contributions to high-impact research position him as a highly suitable candidate for the Best Researcher Award. His consistent excellence in advancing computer vision and AI research, coupled with his community service and mentoring, make him a strong contender whose recognition would inspire both emerging and established scientists in the field.

Moumita Ghosh | Computer Science | Best Researcher Award

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Dr. Moumita Ghosh | Computer Science | Best Researcher Award

Assistant Professor, Heritage Institute of Technology, India

Dr. Moumita Ghosh (PhD, Engg.) is a passionate researcher from Kolkata, India 🇮🇳, currently working as an Assistant Professor in the Department of Computer Science and Engineering at the Heritage Institute of Technology. Her core research interests lie at the intersection of Data Science and Computational Biodiversity. With a deep commitment to innovation and academia, she integrates machine learning and data mining techniques to address biodiversity conservation and complex ecological data analysis. 👩‍🏫🌿📊

Profile

Orcid

Education 🎓

Dr. Ghosh holds a Ph.D. in Engineering (2019–2024) from Jadavpur University, Kolkata, with her thesis focusing on “Algorithms for Data Mining: Applications in Biodiversity” 🧠🌱. She earned her M.E. in Multimedia Development from the same university (2011–2013) and completed her B.Tech. in Info Technology from WBUT in 2011. She also achieved outstanding academic performance in both her higher secondary and secondary education at Ichapur Girls’ High School. 🎓

Experience 💼

With over a decade of academic experience, Dr. Ghosh has served in key teaching roles at several premier institutions. She currently teaches Data Structures at Heritage Institute of Technology (2024–Present). Previously, she worked at Narula Institute of Technology (2022–2024), Jadavpur University (as a guest faculty and later PI for a DST-funded project), and held Assistant Professor roles at Institute of Engineering and Management (2015–2017) and Bengal College of Engineering and Technology (2013–2015). 💻📚

Research Interest 🔍

Dr. Ghosh’s research bridges Data Science and Ecology through Computational Biodiversity 🌍🧬. Her work includes pattern mining, remote sensing data, complex networks, and biodiversity modeling using advanced machine learning algorithms. She explores how AI and statistical methods can help mitigate biodiversity loss, emphasizing ecological data interpretation and predictive modeling. Her interests extend to deep learning, natural language processing, and ecological network analysis. 📈🌐

Awards 🏆

Dr. Ghosh is a UGC NET qualifier (2017 & 2018) and was awarded the prestigious DST Women Scientists Fellowship (2019–2022), where she led a ₹22 lakh project on biodiversity data mining. She collaborates internationally with Universitas Islam Indonesia and has served as a reviewer and TPC member for various global conferences. She is a proud member of the Computer Society of India (CSI) since 2021. 🏅🌟

Publications 📄

📖 Ghosh et al. (2023). “An Irregular CLA-based Novel Frequent Pattern Mining Approach.” International Journal of Data Mining, Modelling and Management. DOI

📖 Ghosh et al. (2022). “Recognition of Coexistence Pattern of Salt Marshes and Mangroves.” Ecological Informatics. DOI

📖 Ghosh et al. (2022). “Frequent itemset mining using FP-tree.” Innovations in Systems and Software Engineering.

📖 Ghosh et al. (2021). “Knowledge Discovery of Sundarban Mangrove Species.” SN Computer Science. DOI

📖 Ghosh et al. (2021). “Prediction of Interaction between SARS-CoV-2 and Human Protein.” Journal of The Institution of Engineers (India): Series B. DOI

📖 Mondal, Ghosh et al. (2022). “Suffix forest for mining tri-clusters from time-series data.” Innovations in Systems and Software Engineering.

📖 Ghosh & Parekh (2013). “Fish shape recognition using multiple shape descriptors.” International Journal of Computer Applications.

Conclusion

Dr. Moumita Ghosh is a highly suitable candidate for the Best Researcher Award. Her innovative integration of machine learning and biodiversity studies, coupled with a solid record of publications, a granted patent, and a DST fellowship, reflects both depth and societal relevance in her research. With continued international exposure and independent research leadership, she is poised to make significant contributions to science and sustainability.