Heilym Camila Ramirez Rico | Computer Vision | Young Scientist Award

Prof. Dr. Heilym Camila Ramirez Rico | Computer Vision | Young Scientist Award

Federico Santa María Technical University | Chile

Prof. Dr. Heilym Camila Ramirez Rico is a researcher affiliated with Pontificia Universidad Católica de Valparaíso, Chile, whose work lies at the intersection of computer vision, human posture analysis, and intelligent transportation systems. Her research focuses on the application of vision-based sensing and data-driven methods to analyze human movement and behavior in real-world urban environments, with particular emphasis on public transportation safety and accessibility. She has authored 7 peer-reviewed publications, which have collectively received 208 citations, reflecting a strong scholarly impact relative to publication volume, with an h-index of 4. Her work demonstrates interdisciplinary collaboration, involving co-authors across engineering, applied sciences, and urban studies. Notably, her recent open-access study on passenger posture detection during bus boarding and alighting contributes to data-informed urban mobility planning. The societal relevance of her research is evident in its potential to improve public transport design, passenger safety, and inclusive urban infrastructure through applied computer vision solutions.

Citation Metrics (Scopus)

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Top 5 Featured Publications

Yanping Mo | Image Restoration Algorithms | Best Researcher Award

Ms. Yanping Mo | Image Restoration Algorithms | Best Researcher Award

Postgraduate Student | Xi’an University of Science and Technology | China

Ms. Yanping Mo is a researcher affiliated with the School of Communication and Information Engineering at Xi’an University of Science and Technology, China, and associated with the China Education and Research Network in Beijing. Her research primarily focuses on the intersection of computational imaging, signal processing, and optimization algorithms for image restoration and enhancement. In particular, her recent work titled “Research on plug-and-play image restoration algorithm based on dual weighted ADMM,” published in Optics & Laser Technology (December 2025), demonstrates her expertise in developing advanced optimization frameworks for image reconstruction. The study explores a dual weighted Alternating Direction Method of Multipliers (ADMM) approach that integrates plug-and-play priors to enhance the flexibility and accuracy of image restoration tasks. This approach effectively addresses common challenges in image denoising, deblurring, and super-resolution by adaptively balancing data fidelity and regularization terms. Her contribution lies in improving the convergence stability and computational efficiency of traditional ADMM-based algorithms while maintaining high-quality visual outputs. Through her collaborative work with researchers such as Wei Chen, Zhaohui Li, and Bin Fan, Mo advances the application of mathematical modeling and artificial intelligence techniques in optical and laser imaging technologies. Her research supports the broader goal of enhancing image processing methodologies for scientific imaging, remote sensing, medical imaging, and industrial inspection applications. Overall, Yanping Mo’s research reflects a strong commitment to the development of robust and intelligent algorithms that bridge theory and application in the field of computational optics and image restoration.

Profile: ORCID

Featured Publications

1. Chen, W., Mo, Y., Li, Z., & Fan, B. (2025, December). Research on plug-and-play image restoration algorithm based on dual weighted ADMM. Optics & Laser Technology, 113997.