Providence Habumuremyi | Civil Engineering | Best Researcher Award

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Dr. Providence Habumuremyi | Civil Engineering | Best Researcher Award

Postdoctoral Fellow, Fuzhou University, China.

Dr. Providence Habumuremyi, born on January 1, 1988, in Rwanda, is a distinguished civil engineer specializing in tunnel stability and geotechnical engineering. Currently a postdoctoral fellow at Fuzhou University, China, he earned his Doctor of Engineering from Beijing Jiaotong University, focusing on three-dimensional analytical methods for tunnel face stability in undrained clay grounds. His academic journey includes a Master’s degree in Civil Engineering from the same university and a Bachelor’s degree from the University of Rwanda. Dr. Habumuremyi’s professional experience spans roles such as Civil Engineer at Beijing Jinghangan Airport Engineering Co., Ltd., contributing to international airport projects in the Maldives and Zambia. His multilingual abilities and cross-cultural experiences enhance his collaborative research endeavors. Recognized for his analytical skills and innovative approaches, Dr. Habumuremyi continues to impact the field through research, publications, and contributions to major engineering projects.

Profile

Orcid

🎓 Education

  • Doctor of Engineering in Civil Engineering
    Beijing Jiaotong University, China (09/2019 – 06/2024)
    Dissertation: Three-Dimensional Analytical Continuous Upper Bound Limit Analyses for Face Stability of Shallow Shield Tunneling in Undrained Clay Ground
    Supervisor: Prof. Yan-Yong Xiang

  • Master of Engineering in Civil Engineering
    Beijing Jiaotong University, China (09/2015 – 06/2017)
    Thesis: Friction Pendulum Systems for Seismic Isolation of Structures in Near-Fault Regions
    Supervisor: Prof. Lin LiuResearcher Discovery+1AGRIS+1

  • Bachelor of Science in Civil Engineering
    University of Rwanda (01/2011 – 08/2014)
    Supervisor: Prof. Park Ildong

🏗️ Experience

  • Postdoctoral Researcher
    Fuzhou University, China (11/2024 – Present)
    Research Focus: Tunnel stability, ground and structural dynamics, geotechnical engineering.

  • Inspector
    Beijing Jianyetong Engineering Testing Technology Co., Ltd. (07/2024 – 11/2024)
    Responsibilities: Preparation of construction drawings, on-site surveying, attending technical meetings.

  • Civil Engineer
    Beijing Jinghangan Airport Engineering Co., Ltd. (07/2017 – 09/2019)
    Projects: Expansion of Maldives Velana International Airport; Construction of Ndola Simon Mwansa Kapwepwe International Airport, Zambia.
    Responsibilities: Preparation of construction drawings, site supervision, technical meetings, translation of technical documents (Chinese to English).

  • Director of Studies
    Collegio Santo Antonio Maria Zaccaria (01/2015 – 09/2015)
    Responsibilities: Supervision of teachers, curriculum implementation follow-up, teaching Mathematics, Physics, Technical Drawing, Scaffolding.

🔬 Research Focus 

Dr. Habumuremyi’s research centers on the stability analysis of tunnel faces, particularly in undrained clay conditions. He employs analytical and computational methods, including three-dimensional upper bound limit analyses, to assess and enhance the safety of shallow shield tunneling operations. His work extends to geotechnical engineering, focusing on soil-structure interaction, and the dynamics of structures under seismic loading. By integrating tools like MATLAB, SAP2000, ABAQUS, and OPTUM G2 & G3, he develops models that predict structural responses to various geotechnical challenges. His interdisciplinary approach aims to improve construction practices and inform the design of resilient infrastructure.

đź“š Publication Top Notes

1. A 3-D Analytical Continuous Upper Bound Limit Analysis for Face Stability of Shallow Shield Tunneling in Undrained Clays

Journal: Computers and Geotechnics, December 2023
DOI: 10.1016/j.compgeo.2023.105779
Authors: Providence Habumuremyi, Yanyong Xiang

Summary:
This paper introduces a three-dimensional (3D) analytical upper bound limit method to evaluate face stability in shallow shield tunneling through undrained clay. Unlike previous two-dimensional models, the authors developed a 3D continuous velocity field based on a logarithmic spiral failure mechanism, offering more accurate predictions. The method considers various tunnel depths, diameters, and face pressures.

Key Contributions:

  • Developed a new continuous 3D velocity field using upper bound limit analysis.

  • Applied to shield tunneling in undrained clay (e.g., soft cohesive soil in urban areas).

  • Validated against numerical simulations (ABAQUS), showing good agreement.

  • Provided design charts for practicing engineers.

Relevance:
This model improves the safety and efficiency of tunnel construction in soft ground by offering realistic estimations of the support pressure required to prevent face collapse.

2. Determining Trigger Factors of Soil Mass Failure in a Hollow: A Study Based in the Sichuan Province, China

Journal: CATENA, September 2022
DOI: 10.1016/j.catena.2022.106368
Authors: Jules Maurice Habumugisha, Ningsheng Chen, Mahfuzur Rahman, Providence Habumuremyi, Etienne Tuyishimire, et al.

Summary:
This study investigates the main triggering factors of soil mass failure (landslides) in a specific hollow area of Sichuan Province, China. It uses field data, geostatistics, and geotechnical analysis to assess slope failure causes. Key parameters include slope angle, rainfall, vegetation cover, and soil composition.

Key Contributions:

  • Combined field sampling, laboratory testing, and remote sensing.

  • Identified critical depth and shear strength thresholds for failure.

  • Proposed mitigation techniques, including improved land management and vegetative cover.

Relevance:
Essential for improving slope stability prediction and disaster risk reduction in landslide-prone mountainous regions.

3. Friction Pendulum Systems for Seismic Isolation of Structures in Near-Fault Regions

Type: Master’s Thesis
Date: May 20, 2017
DOI: 10.13140/RG.2.2.19943.15527
Author: Providence Habumuremyi

Summary:
This thesis evaluates the performance of Friction Pendulum Systems (FPS) for seismic isolation in buildings located in near-fault zones. Near-fault ground motions can be intense and impulsive, posing challenges to conventional structural designs. The study uses numerical simulations in SAP2000 to demonstrate how FPS can effectively decouple structures from strong ground motions.

Key Contributions:

  • Designed FPS models for medium-rise buildings.

  • Compared base-isolated structures with fixed-base ones under near-fault motion.

  • Showed significant reduction in base shear and inter-story drift with FPS.

Relevance:
Supports the use of FPS isolation technology in earthquake engineering, particularly for civil infrastructure near seismic faults.

4. Mitigation Measures for Wind Erosion and Sand Deposition in Desert Railways: A Geospatial Analysis of Sand Accumulation Risk

  • Journal: Sustainability, April 29, 2025

  • DOI: 10.3390/su17094016

  • Authors: Mahamat Nour Issa Abdallah, Tan Qulin, Mohamed Ramadan, Providence Habumuremyi

Summary:

This study presents a comprehensive geospatial analysis aimed at identifying and mitigating the risks associated with wind erosion and sand deposition along desert railway corridors. Utilizing advanced GIS tools and remote sensing data, the research identifies high-risk zones where sand accumulation poses significant threats to railway infrastructure. The authors evaluate various mitigation strategies, including the implementation of sand fences, vegetation barriers, and optimized track alignments, to reduce the impact of aeolian processes on railway operations.

Key Contributions:

  • Development of a geospatial risk assessment model for sand accumulation along railway lines.

  • Identification of critical zones susceptible to wind-induced sand deposition.

  • Evaluation of mitigation measures and their effectiveness in different environmental contexts.

  • Recommendations for integrating geospatial analysis into railway planning and maintenance strategies.

Relevance:

The findings offer valuable insights for railway engineers and planners working in arid regions, providing tools and strategies to enhance the resilience of railway infrastructure against wind erosion and sand deposition.

5. Atom Search Optimization: A Systematic Review of Current Variants and Applications

  • Journal: Knowledge and Information Systems, April 12, 2025

  • DOI: 10.1007/s10115-025-02389-3

  • Authors: Sylvère Mugemanyi, Zhaoyang Qu, François Xavier Rugema, Yunchang Dong, Lei Wang, FĂ©licitĂ© Pacifique Mutuyimana, Emmanuel Mutabazi, Providence Habumuremyi, Rita ClĂ©mence Mutabazi, et al.

Summary:

This comprehensive review delves into the Atom Search Optimization (ASO) algorithm, a nature-inspired metaheuristic optimization technique. The paper systematically categorizes existing variants of ASO, analyzing their structural modifications, performance enhancements, and application domains. It also highlights the algorithm’s adaptability in solving complex optimization problems across various fields, including engineering design, machine learning, and operational research.

Key Contributions:

  • Classification and analysis of existing ASO variants and their respective enhancements.

  • Evaluation of ASO’s performance in comparison to other optimization algorithms.

  • Identification of application areas where ASO has been effectively employed.

  • Discussion on the challenges and future research directions in the development of ASO algorithms.

Relevance:

For researchers and practitioners in optimization and computational intelligence, this review serves as a valuable resource, offering a consolidated understanding of ASO’s capabilities and guiding future developments in the field.

Conclusion

Dr. Providence Habumuremyi presents a compelling case as a highly promising and accomplished early-career researcher in civil and geotechnical engineering. His strong academic foundation, international research contributions, publication record, and multilingual competence support his suitability for the Best Researcher Award. While there is room to grow in terms of independent research leadership and impact-driven dissemination, his trajectory indicates a strong upward path in academic and engineering research.

Dr Lili Zhao | Biomedical Engineering |

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Dr Lili Zhao | Biomedical Engineering | Women Researcher Award

Department of Computer Science, Nantong University, China

Dr. Lili Zhao, born in Xinxiang, China, is a distinguished researcher specializing in Artificial Intelligence, Computer Vision, and Biomedical Image Processing. Currently serving in the Department of Computer Science at Nantong University, she has built a career dedicated to innovative research and teaching. She earned her Doctor of Engineering from the National University of Defense Technology and completed her postdoctoral research at Shanghai Jiao Tong University. With an international research stint at the University of Leicester, UK, Dr. Zhao has strengthened global academic ties. Her work has led to impactful publications in SCI-indexed journals and international conferences. Known for her contributions to medical imaging—particularly in fetal ultrasound and cervical cancer diagnostics—she integrates deep learning and algorithmic optimization in her projects. Beyond research, she passionately teaches courses in machine learning, C++, and digital image processing, fostering the next generation of computer scientists.

🎓 Education

Dr. Lili Zhao’s academic journey reflects a strong foundation in Computer Science and Artificial Intelligence. She earned her Bachelor of Engineering (2007) from Xinyang Normal University, followed by a Master of Engineering (2011) from Henan Normal University, majoring in Computer Application Technology. Her thirst for advanced research led her to pursue a Doctor of Engineering (2017) in Computer Science at the National University of Defense Technology, one of China’s top institutions. From 2018 to 2024, she conducted postdoctoral research in Artificial Intelligence at Shanghai Jiao Tong University, focusing on medical image processing. She also spent 2022–2023 as an academic visitor at the University of Leicester, UK, further enriching her international perspective in AI research. Her consistent academic excellence and cross-disciplinary training uniquely position her to address challenges at the intersection of computing and biomedical engineering.

đź’Ľ Experience

Dr. Zhao currently serves in the Department of Computer Science at Nantong University, where she is involved in both teaching and research within the School of Artificial Intelligence and Computer Science. Over the years, she has held various academic positions, with hands-on experience in research laboratories focused on biomedical image processing, deep learning, and AI-powered healthcare diagnostics. During her postdoctoral work at Shanghai Jiao Tong University, she developed advanced frameworks for fetal ultrasound image assessment and cervical cancer detection. She also collaborated internationally during her academic visit to the University of Leicester, contributing to joint projects in algorithmic optimization and uncertainty quantification. Her teaching record includes courses such as Machine Learning, C++ Programming, and Digital Image Processing, emphasizing her balanced engagement in both scientific innovation and student mentorship.

🔬 Research Focus

Dr. Lili Zhao’s research is centered on the development of AI-driven solutions for biomedical image analysis, particularly in fetal imaging and cervical cell diagnostics. Her work combines image processing, computer vision, and algorithm optimization to enable early and accurate diagnosis of medical conditions. She employs deep learning techniques to address challenges such as image quality assessment, segmentation, and classification under uncertainty or label shift. Her projects integrate multi-phase detection, extreme learning machines, and MRF-based segmentation for cytological images, contributing significantly to early cancer detection and maternal health monitoring. These solutions have the potential to be integrated into smart diagnostic systems and telemedicine platforms. Dr. Zhao’s research not only improves diagnostic efficiency but also ensures cost-effective healthcare delivery, particularly in under-resourced settings.

đź“„ Publication Top Notes