Munish Kumar | Computer Science | Research Excellence Award

Dr. Munish Kumar | Computer Science | Research Excellence Award

Associate Professor | Maharaja Ranjit Singh Punjab Technical University | India

Dr. Munish Kumar is a distinguished researcher in artificial intelligence, machine learning, deep learning, and computer vision, with a strong focus on real-world applications in forensic document analysis, speech and language processing, intelligent transportation systems, multimedia analytics, and smart surveillance. His research interests include handwriting and writer identification, document forgery detection, facial emotion recognition, human activity and gait analysis, speech recognition, and transfer learning–based lightweight AI models. He possesses advanced research skills in CNNs, hybrid CNN-BLSTM architectures, support vector machines, feature extraction, pattern recognition, data analytics, and AI-driven image and signal processing. His impactful contributions have earned him academic recognition through high citation impact and consistent publication in reputed international journals and conferences, reflecting significant awards and honors through scholarly influence. According to Scopus, Dr. Kumar has published 182 documents, received 7,393 citations, and achieved an h-index of 43, underscoring his sustained research excellence, global visibility, and leadership in advancing intelligent and forensic AI systems across interdisciplinary domains.

 

Citation Metrics (Scopus)

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6000
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Citations

7,393

Documents

182

h-index

43

Citations

Documents

h-index

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Featured Publications


A survey of deep learning and its applications: A new paradigm to machine learning


– Archives of Computational Methods in Engineering, 2020 (Citations: 1530)


Face detection techniques: a review


– Artificial Intelligence Review, 2019 (Citations: 587)


Transfer learning for image classification using VGG19: Caltech-101 image data set


– Journal of Ambient Intelligence and Humanized Computing, 2023 (Citations: 457)


A healthcare monitoring system using random forest and internet of things (IoT)


– Multimedia Tools and Applications, 2019 (Citations: 389)

 

Maliki Moustapha | Computer Science | Best Researcher Award

Dr. Maliki Moustapha | Computer Science | Best Researcher Award

PhD | Erciyes University | Turkey

Dr. Maliki Moustapha, an accomplished researcher from Erciyes University, is recognized for his expertise in Artificial Intelligence (AI), Deep Transfer Learning, and Data Engineering, with a strong focus on the integration of intelligent algorithms and data-driven models to address real-world computational challenges. His academic background is rooted in computer science and engineering, where he developed advanced skills in machine learning, neural networks, data mining, and smart systems design. Professionally, Dr. Moustapha has been actively engaged in both research and academic mentorship, contributing to the development of innovative solutions in AI-powered automation, pattern recognition, and intelligent monitoring systems. His major research interests encompass computer vision, deep learning model optimization, spatiotemporal data analysis, and Internet of Things (IoT)-based smart healthcare systems. Among his most cited contributions is the publication titled “A Novel YOLOv5 Deep Learning Model for Handwriting Detection and Recognition” in the International Journal on Artificial Intelligence Tools (2023), which demonstrates superior accuracy and efficiency in image recognition. He has also published influential works on spatial and spatiotemporal clustering algorithms and IoT-based patient monitoring, bridging the gap between data intelligence and applied computing. His research skills span across Python programming, neural network modeling, big data analytics, data preprocessing, and model training for intelligent systems. Though early in his academic journey, Dr. Moustapha has earned recognition for his impactful work, showing promising potential in advancing AI technologies. According to Scopus and Google Scholar, he has achieved 9 citations, an h-index of 1, and several published documents reflecting growing international recognition. Dr. Moustapha’s research continues to contribute meaningfully to the fields of artificial intelligence and computational intelligence. In conclusion, his innovative approach, interdisciplinary mindset, and technological vision position him as a forward-thinking researcher committed to shaping the next generation of intelligent data systems and AI-driven innovations.

Profiles: ORCID | Google Scholar

Featured Publications

1. Moustapha, M., Taşyürek, M., & Öztürk, C. (2023). A novel YOLOv5 deep learning model for handwriting detection and recognition. International Journal on Artificial Intelligence Tools, 32(04), 2350016.

2. Moustapha, M. (2024). Spatial and spatiotemporal clustering algorithms in data mining. In Proceedings of the 3rd International Conference on Data and Electronics and Computing (ICDEC).

3. Moustapha, M. (2019). Alternative approach of patient monitoring system based on Internet of Things. In Proceedings of the II. International Science and Academic Congress (INSAC).