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)

7393
6000
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Citations

7,393

Documents

182

h-index

43

Citations

Documents

h-index

View Scopus Profile View ORCID Profile View Google Scholar Profile

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)

 

Solomon Legesse | Computer Science | Editorial Board Member

Assoc Prof Dr. Solomon Legesse | Computer Science | Editorial Board Member

Postgraduate Coordinator | Bahir Dar University | Ethiopia

Dr. Solomon Addisu is a leading researcher in climate change, environmental systems, soil science, and sustainable land-use management, with a strong focus on Ethiopia and the broader East African region. His extensive body of work advances understanding of how climate variability, land degradation, agricultural systems, and natural resource pressures intersect to shape environmental sustainability and community resilience. Through more than a decade of scientific contributions, he has established himself as a significant voice in climate adaptation research, soil enhancement technologies, and watershed management.A central pillar of his research explores biochar technology, soil amendments, and nutrient cycling. His studies on water hyacinth-based biochar, phosphorus biofertilizers from animal bone, and the physicochemical transformations of biomass during pyrolysis offer pioneering insights into regenerative agriculture and soil rehabilitation. These works demonstrate the potential of low-cost, sustainable inputs to improve soil fertility, reduce acidification, enhance nutrient retention, and boost crop productivity—especially in degraded highland agroecosystems.Dr. Addisu is also widely recognized for his contributions to climate modeling, hydrological forecasting, and drought analysis. His research using CMIP6 scenarios, rainfall trend evaluations, and meteorological drought assessments provides vital actionable guidance for climate adaptation planning in vulnerable regions. He applies advanced geospatial tools, remote sensing, and machine learning to analyze land-use dynamics, watershed degradation, flood risks, and invasive species monitoring—most notably in the Lake Tana basin.Another core area of his work addresses environmental pollution, urban heat island effects, charcoal production impacts, and sustainable waste management solutions. His studies integrate socioeconomic, ecological, and policy perspectives, offering comprehensive frameworks for environmental governance, community-based adaptation, and nature-based solutions.Additionally, Dr. Addisu’s extensive research on climate change perceptions, rural livelihood vulnerabilities, agricultural resilience, and livestock diversification is widely cited in the fields of sustainable development and rural poverty reduction. His work equips policymakers and communities with evidence-based strategies to build resilience in the face of increasing climate stressors.Overall, Dr. Solomon Addisu’s research portfolio bridges environmental science, climate adaptation, soil restoration, and sustainable natural resource management. His contributions significantly strengthen scientific understanding and provide practical pathways toward ecological stability, food security, and climate-resilient development across Ethiopia and East Africa.

Profiles: ORCID

Featured Publications

  1. Kohira, Y., Fentie, D., Lewoyehu, M., Wutisirirattanachai, T., Gezahegn, A., Ahmed, M., Akizuki, S., Addisu, S., & Sato, S. (2025). The sustainable management of nitrogen fertilizers for environmental impact mitigation by biochar applications to soils: A review from the past decade. Environments.

  2. Fentie, D., Mihretie, F. A., Kohira, Y., Addisu Legesse, S., Lewoyehu, M., Wutisirirattanachai, T., & Sato, S. (2025). Optimizing cropping systems using biochar for wheat production across contrasting seasons in Ethiopian highland agroecology. Agronomy.

  3. Gezahegn, A., Selassie, Y. G., Agegnehu, G., Addisu, S., Mihretie, F. A., Kohira, Y., & Sato, S. (2025). Pyrolysis temperature changes the physicochemical characteristics of water hyacinth-based biochar as a potential soil amendment. Biomass Conversion and Biorefinery.

  4. Mekonnen, G. T., Berlie, A. B., Wubie, M. A., Legesse, S. A., & Cameselle, C. (2025). Surface urban heat island intensity and urban utility consumption: Impact analysis and projections. The Scientific World Journal.

  5. Addisu, S., Aniley, E., Gashaw, T., Kelemu, S., & Demessie, S. F. (2024). Evaluating the performances of gridded satellite products in simulating the rainfall characteristics of Abay Basin, Ethiopia. Sustainable Environment.

The nominee’s contributions in computer science advance intelligent systems that enhance automation, analytics, and digital decision-making across industries. Their innovative research accelerates global technological transformation, strengthens digital infrastructures, and drives smarter, more efficient solutions for society, businesses, and future technological innovation.

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).