Darío Fernando Yépez Ponce | Robotics and Automation | Editorial Board Member

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Prof. Darío Fernando Yépez Ponce | Robotics and Automation | Editorial Board Member

Docente Investigador | Instituto Superior Universitario Central Técnico | Ecuador

Darío Fernando Yépez Ponce is a mechatronics and automation engineer and academic from Ecuador, currently working as a faculty member in electronics at Instituto Superior Universitario Central Técnico in Quito (since October 2024). His background includes an engineering degree in mechatronics (2016) from Universidad Técnica del Norte, plus ongoing postgraduate studies (Master’s in Electronics and Automation) at Universidad Politécnica Salesiana. Over the years he has served as a lecturer in various institutions across Ecuador teaching mechatronics, electronics, and automation engineering.Professor Yépez’s research interest concentrates on robotics, control systems (notably PID control), autonomous systems (including unmanned ground vehicles), microgrids and power electronics, IoT-based automation, and applications of mechatronics in agriculture and automation systems. His work shows a recurrent focus on optimization algorithms, control strategies, mobile robotics, and intelligent systems for automation and smart farming. Notable recent outputs include a 2025 journal article titled “Route Optimization for UGVs: A Systematic Analysis of Applications, Algorithms and Challenges,” which analyses algorithms for path planning in autonomous ground vehicles. In terms of research productivity and impact: according to his publicly visible profile, he has a Google Scholar citation count of about 113 citations.Publications span journal articles, conference papers, and book chapters. For example, his 2025 UGV-optimization article is indexed in major journals. The breadth of his work — from control system tuning (e.g., PID controllers via hybrid optimization strategies) to IoT-based systems and robotics — reflects a versatile research skill set in automation, control, robotics, power electronics, and applied mechatronics.Although I could not find a definitive public value for his Scopus h-index or total Scopus-document count (his Scopus Author ID is 57220807265), the combination of his journal-indexed articles, book chapters and recent contributions suggests a growing research profile, particularly in robotics, automation, and sustainable/renewable-power applications.In conclusion, Darío Fernando Yépez Ponce represents a dynamic and interdisciplinary researcher bridging mechatronics, control systems, automation, and robotics — with an orientation toward real-world applications such as autonomous vehicles and smart farming. His emerging publication record and international-indexed works position him as an active contributor in automation and mechatronics research circles.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

  1. Yépez-Ponce, D. F., Salcedo, J. V., Rosero-Montalvo, P. D., & Sanchis, J. (2023). Mobile robotics in smart farming: Current trends and applications. Frontiers in Artificial Intelligence, 6, 1213330.
    Citations: 99

  2. Ponce, H. M. Y., & Yépez-Ponce, D. F. (2020). Control de modo deslizante para microrredes: Una revisión. Investigación Tecnológica IST Central Técnico, 2(1), 14–14.
    Citations: 5

  3. Yépez Ponce, D. F., & Montalvo López, W. M. (2021). Development of a hybrid optimization strategy based on a bacterial foraging algorithm (BFA) and a particle swarming algorithm (PSO) to tune the PID controller of a ball and plate system. In XV Multidisciplinary International Congress on Science and Technology (pp. 15–29).
    Citations: 3

  4. Yépez-Ponce, D. F., Montalvo, W., Guamán-Gavilanes, X. A., & Echeverría-Cadena, M. D. (2025). Route optimization for UGVs: A systematic analysis of applications, algorithms and challenges. Applied Sciences, 15(12), 6477.
    Citations: 2

  5. Yépez Ponce, H. M., Yépez Ponce, D. F., Proaño Lapuerta, E. A., Mosquera Bone, C. E., & Alarcón Angulo, M. L. (2022). Open-source platform for development of taximeters: Adjustment software. In International Conference on Applied Technologies (pp. 532–544).
    Citations: 1

 

Solomon Legesse | Computer Science | Editorial Board Member

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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.

Amna Ikram | Artificial Intelligence | Best Researcher Award

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Dr. Amna Ikram | Artificial Intelligence | Best Researcher Award

Senior Lecturer | Government Sadiq College Women University | Pakistan

Dr. Amna Ikram is an accomplished researcher recognized for her pioneering contributions in machine learning, image processing, Internet of Things (IoT), obstacle detection, and smart agriculture. Her work emphasizes the integration of artificial intelligence and data-driven technologies to develop intelligent, efficient, and socially impactful systems. With a citation count exceeding 170, an h-index of 7, and an i10-index of 5, Dr. Ikram’s scholarly record highlights her commitment to addressing modern challenges in automation, healthcare, and sustainable agriculture.Her research focuses on creating AI-enabled frameworks and hybrid computational models that enhance decision-making and predictive accuracy in real-world applications. In agriculture, her widely cited paper, “Crop Yield Maximization Using an IoT-Based Smart Decision System” (Journal of Sensors, 2022), presents a robust model for optimizing crop productivity using sensor data, environmental parameters, and predictive algorithms. This work has significantly influenced the development of precision agriculture and IoT-driven farming systems.Expanding her expertise into healthcare and assistive technologies, Dr. Ikram has contributed to several innovative studies such as “Forensic Radiology: A Robust Approach to Biological Profile Estimation from Bone Image Analysis Using Deep Learning” and “Transformer-Based ECG Classification for Early Detection of Cardiac Arrhythmias.” These contributions showcase her ability to blend AI with biomedical imaging for diagnostic advancements and patient support.Her recent publications, including “A DETR-Based Approach for Enhancing Object Detection in Assistive Technology for the Visually Impaired” and “AI-Enabled Vision Transformer for Automated Weed Detection,” highlight her continuous drive to apply machine learning and computer vision to enhance accessibility and agricultural efficiency. Furthermore, her exploration of fuzzy-optimized hybrid neural networks and IoT sensor integration has resulted in innovative frameworks for yield prediction, crop disease detection, and obstacle recognition.Dr. Ikram’s interdisciplinary approach bridges technology and sustainability. By merging deep learning, IoT infrastructure, and intelligent vision systems, her work supports the creation of smarter, adaptive environments that empower both humans and industries. Her research continues to advance the frontiers of AI-driven automation, smart agriculture, and assistive IoT technologies, contributing profoundly to sustainable innovation and societal betterment.

Profiles: ORCID | Google Scholar

Featured Publications

  1. Ikram, A., Aslam, W., Aziz, R. H. H., Noor, F., Mallah, G. A., Ikram, S., & Ahmad, M. S. (2022). Crop yield maximization using an IoT-based smart decision system. Journal of Sensors, 2022(1), 2022923.
    Citations: 71

  2. Batool, S. N., Yang, J., Gilanie, G., Latif, A., & Ikram, A. (2025). Forensic radiology: A robust approach to biological profile estimation from bone image analysis using deep learning. Biomedical Signal Processing and Control, 105.
    Citations: 19

  3. Malik, M., Ikram, A., Batool, S. N., & Aslam, W. (2018). A performance assessment of rose plant classification using machine learning. In Proceedings of the International Conference on Intelligent Technologies and Applications (pp. 745–756).
    Citations: 15

  4. Hassan, J. U., Missen, M. M. S., Firdous, A., Maham, A., & Ikram, A. (2023). An adaptive M-learning usability model for facilitating M-learning for slow learners. International Journal of Interactive Mobile Technologies, 17(19).
    Citations: 14

  5. Naveed, S., Husnain, M., Alsubaie, N., Samad, A., Ikram, A., Afreen, H., & Gilanie, G. (2024). Drug efficacy recommendation system of glioblastoma (GBM) using deep learning. IEEE Access.
    Citations: 13

Dr. Amna Ikram’s research bridges artificial intelligence, IoT, and data-driven innovation to create intelligent solutions that enhance agriculture, healthcare, and assistive technologies. Her pioneering work advances sustainable development, automation, and societal well-being through smart, human-centered innovations that connect science with real-world impact.