Esteban Denecken | Engineering | Best Researcher Award

Dr. Esteban Denecken | Engineering | Best Researcher Award

Researcher from University of Los Andes, Chile

Esteban Jorge Denecken Campaña is a dedicated researcher and electrical engineer specializing in medical image processing and advanced magnetic resonance imaging (MRI) techniques. With a strong background in electrical engineering and ongoing doctoral studies, he has established a clear trajectory in biomedical imaging and computational analysis. His work centers on the development of novel methods for the simultaneous acquisition of water, fat, and velocity imaging using phase-contrast MRI. He has contributed to multiple peer-reviewed journals and has presented at prestigious international conferences including ISMRM. Esteban has collaborated with prominent institutions such as the University of Wisconsin–Madison, where he worked with the Quantitative Body MRI team. His expertise lies at the intersection of image processing, signal acquisition, and algorithmic development for clinical and biological applications. Esteban has also contributed to innovation in image analysis of biological materials and has actively supported undergraduate research and academic mentorship. His professional journey reflects both academic excellence and practical innovation. With solid experience in both academia and industry, he combines technical precision with a creative approach to engineering challenges, particularly in healthcare technologies. His participation in innovation programs and cross-disciplinary research showcases his commitment to translating scientific discovery into practical, impactful solutions.

Professional Profile

Education

Esteban Jorge Denecken Campaña holds a robust academic foundation in electrical engineering and biomedical image processing. He earned both his Bachelor’s and Professional Degree in Civil Electrical Engineering from Universidad de Los Andes in 2015. Currently, he is pursuing a Doctorate in Engineering Sciences with a specialization in Electrical Engineering at Pontificia Universidad Católica de Chile, where his doctoral research focuses on the development of advanced MRI techniques for simultaneous imaging of water, fat, and flow velocity. He has also enhanced his expertise through specialized training, including a Biomedical Imaging course at Northeastern University and practical EEG-fMRI training conducted at Clínica Las Condes. Additionally, Esteban completed the Innovation Academy program at Universidad de Los Andes, where he acquired valuable knowledge in innovation management, intellectual property protection, and science communication. His academic path demonstrates a balanced integration of theoretical knowledge and applied research in electrical engineering, with an increasing focus on medical and biological imaging. His academic excellence is complemented by a commitment to continual learning, evidenced by language training at the University of California, Davis, and participation in multiple research-related technical courses. His educational background positions him as a capable and well-rounded researcher in biomedical engineering.

Professional Experience

Esteban Denecken’s professional experience spans research engineering, doctoral research, and technical innovation within academia and industry. He is currently working as a Research Engineer at the School of Engineering, Universidad de Los Andes, where he develops image processing algorithms for analyzing biological samples, including paletted rich fibrin and microglial cells. As part of his doctoral research at Pontificia Universidad Católica de Chile, he has developed advanced techniques for MRI data acquisition, contributing significantly to the field of simultaneous imaging of biological structures and functions. He also completed a prestigious research internship at the University of Wisconsin–Madison, where he collaborated with leading experts in quantitative MRI. Earlier in his career, Esteban served as an Assistant Scientist at the Advanced Center of Electrical and Electronic Engineering (AC3E), where he enhanced algorithms for displaying HDR content on standard screens. His experience also includes working as a Frontend Developer for Falabella Financiero, where he contributed to the development of digital platforms for credit services in Latin America. Esteban has held roles supporting undergraduate education and research and has served as a teacher assistant for various engineering subjects. His broad professional experience reflects a dynamic balance between academic research, software development, and technical mentorship.

Research Interests

Esteban Denecken’s research interests lie at the intersection of electrical engineering, medical imaging, and computational analysis. His primary focus is the development of novel MRI techniques, specifically aimed at the simultaneous acquisition of water, fat, and velocity imaging. This work enhances the diagnostic capabilities of MRI in clinical settings, particularly in cardiovascular and metabolic imaging. He is also deeply engaged in image processing techniques for analyzing the structural and functional properties of biological tissues. His research addresses challenges in respiratory gating, porosity analysis, and segmentation of microglial cells—topics that are critical in both clinical diagnostics and biomedical research. Esteban is particularly interested in leveraging signal processing, machine learning, and computational modeling to improve the accuracy and efficiency of image-based diagnostics. His interdisciplinary approach involves collaboration with experts in radiology, biomedical engineering, and computer vision. Through his research, Esteban seeks to bridge the gap between engineering innovation and healthcare application, contributing to advances in personalized medicine and non-invasive diagnostics. He continues to explore how computational tools can enhance imaging resolution, data interpretation, and automation in clinical workflows, highlighting his commitment to impactful, translational research in biomedical technology.

Research Skills

Esteban Denecken possesses a wide range of research skills, particularly in medical imaging, signal processing, and algorithm development. His technical proficiency includes the design and implementation of MRI-based techniques for simultaneous imaging of multiple parameters such as water, fat, and blood velocity. He has extensive experience with 4D flow MRI and respiratory gating, which are essential for capturing dynamic physiological processes. Esteban is skilled in biomedical image processing, including tissue segmentation, porosity analysis, and quantitative imaging. He is adept at developing custom algorithms for analyzing both structural and functional aspects of biological materials, using tools such as MATLAB and Python. His research contributions extend to high-impact journal publications and presentations at top-tier international conferences. Additionally, Esteban is experienced in interdisciplinary collaboration, having worked alongside radiologists, physicists, and engineers during his internship at the University of Wisconsin–Madison. He has also mentored undergraduate students, providing guidance in thesis work related to computer vision and image analysis. His ability to communicate complex technical concepts, combined with practical software development experience, further enhances his research effectiveness. Overall, Esteban demonstrates a rare combination of scientific rigor, software engineering capabilities, and collaborative agility.

Awards and Honors

While Esteban Denecken’s formal awards and honors are not explicitly listed, his academic and professional trajectory includes multiple indicators of distinction and recognition. His selection for a competitive internship at the University of Wisconsin–Madison, under the mentorship of renowned radiology expert Dr. Diego Hernando, reflects a high level of international recognition. Participation in leading international conferences such as ISMRM, where he has consistently presented his work since 2021, also underscores the academic community’s acknowledgment of his contributions. His doctoral research at Pontificia Universidad Católica de Chile, one of the most prestigious institutions in Latin America, further attests to his scholarly capabilities and potential. Additionally, Esteban’s role as a mentor to undergraduate thesis students and as a research engineer at Universidad de Los Andes shows that he is entrusted with responsibilities that reflect institutional confidence in his expertise and leadership. Through these roles and invitations to high-level collaborative projects, Esteban has positioned himself as a rising figure in the field of biomedical engineering. His consistent involvement in innovative academic initiatives, such as the Innovation Academy at UANDES, reinforces his proactive engagement in research and innovation ecosystems.

Conclusion

Esteban Jorge Denecken Campaña is a highly promising researcher with a focused expertise in medical image processing and electrical engineering. His academic foundation, hands-on research in advanced MRI techniques, and collaboration with leading international institutions demonstrate a strong alignment with the criteria of a Best Researcher Award. He has contributed to multiple peer-reviewed publications and regularly participates in global scientific forums, reflecting both scholarly productivity and engagement with the research community. His skills in biomedical imaging, algorithm development, and interdisciplinary collaboration are significant strengths that enhance the impact of his work. While he could further benefit from more visible international awards or patents to supplement his growing publication record, his current achievements clearly position him as a valuable asset to the research and academic community. Esteban’s innovative mindset, academic dedication, and technical expertise make him a strong contender for recognition as a best researcher. His work not only advances scientific understanding but also holds practical value in clinical diagnostics and health technologies. Therefore, he is well-suited for consideration for the Best Researcher Award and has the potential to make significant contributions to his field in the coming years.

Publications Top Notes

1. Simultaneous Acquisition of Water, Fat, and Velocity Images Using a Phase‐Contrast T2‐IDEAL Method*

  • Authors: Esteban Denecken, Cristóbal Arrieta, Julio Sotelo, Hernán Mella, Sergio Uribe

  • Year: 2025

2. Simultaneous Acquisition of Water, Fat, and Velocity Images Using a Phase‐Contrast 3p‐Dixon Method

  • Authors: Esteban Denecken, Cristóbal Arrieta, Diego Hernando, Julio Sotelo, Hernán Mella, Sergio Uribe

  • Year: 2025​

3. Impact of Respiratory Gating on Hemodynamic Parameters from 4D Flow MRI

  • Authors: Esteban Denecken, Julio Sotelo, Cristobal Arrieta, Marcelo E. Andia, Sergio Uribe

  • Year: 2022

Zhe Tian | Ocean Engineering | Best Researcher Award

Assoc. Prof. Dr. Zhe Tian | Ocean Engineering | Best Researcher Award

Head of the Department at Ocean University of China, China

Ph.D. Zhe Tian is an accomplished researcher and associate professor at the College of Engineering, Ocean University of China. His extensive academic career spans multiple years, where he has made significant contributions to marine and offshore engineering, focusing on dynamic analysis, modal parameter estimation, and structural health monitoring. With a strong foundation in both education and hands-on professional experience, his research has been published in numerous respected journals. His work often explores innovative methodologies for improving the safety, performance, and reliability of offshore structures, particularly in the context of offshore wind turbines and floating structures. As a result, Ph.D. Tian has earned recognition within the scientific community and beyond.

Professional Profile

Education

Ph.D. Zhe Tian completed his Ph.D. in Marine Engineering from Wuhan University of Technology between 2011 and 2016. Prior to his Ph.D., he earned his Bachelor’s degree in Structural Engineering from the same institution, where he laid the groundwork for his academic pursuit in the fields of marine structures and engineering. His strong educational background, particularly in marine engineering and structural engineering, has provided him with the expertise to tackle complex challenges in offshore structural dynamics, modeling, and health monitoring systems.

Professional Experience

Ph.D. Zhe Tian has a distinguished professional career, highlighted by his role as an Associate Professor at the College of Engineering, Ocean University of China. His tenure at the university began in 2021, following his time as a lecturer at the same institution from 2017 to 2020. Additionally, he had the opportunity to broaden his academic exposure as a Visiting Scholar at the University of Southampton in the UK, where he contributed to research on ocean engineering from 2014 to 2015. His experience at renowned institutions and his progression in academia have enabled him to develop a deep understanding of offshore engineering and related fields.

Research Interests

Ph.D. Zhe Tian’s research interests are centered around the dynamic analysis of offshore structures, modal parameter estimation, model updating, and structural health monitoring systems. His research aims to advance the understanding of offshore structures’ behavior under various conditions, providing solutions for improved design, safety, and durability. He has a particular focus on offshore wind turbines, floating structures, and offshore jacket platforms. Tian’s work also emphasizes the development of innovative methods, such as ensemble deep learning models, variational mode decomposition, and Grey Wolf Optimizer algorithms, for better performance assessment and maintenance of offshore systems.

Research Skills

Ph.D. Tian possesses a diverse set of research skills in the fields of dynamic structural analysis, computational modeling, and artificial intelligence. His expertise includes applying advanced mathematical techniques to assess the dynamic performance of offshore structures, including offshore wind turbines. He is proficient in using optimization algorithms, such as Grey Wolf Optimizer, and signal processing methods, such as variational mode decomposition, to solve complex structural degradation problems. Additionally, Tian is skilled in utilizing machine learning for structural health monitoring, specifically in the context of offshore platforms and marine vessels, showcasing his versatility in both traditional and cutting-edge research methods.

Awards and Honors

Throughout his academic career, Ph.D. Zhe Tian has received recognition for his impactful research contributions to offshore engineering. His work on dynamic performance assessment and structural health monitoring has earned him several prestigious academic honors. While specific awards and honors are not mentioned in the provided profile, his extensive publication record in reputable journals, including Ocean Engineering, and his role as an associate professor attest to his influence and standing in the academic community. These achievements underline his reputation as a leading researcher in the field of marine and offshore engineering.

Conclusion

Ph.D. Zhe Tian is a prominent figure in marine and offshore engineering, demonstrating remarkable expertise in dynamic analysis, structural health monitoring, and the advancement of innovative technologies for offshore structures. His educational background, professional experience, and extensive research output reflect a strong foundation in the field. Tian’s ability to integrate advanced computational methods, machine learning, and optimization algorithms into his work has set him apart as a leading researcher. He continues to make valuable contributions to the scientific community, with significant implications for offshore engineering, particularly in the areas of renewable energy and structural safety. Moving forward, his potential for further innovation and impact in both academic and industry applications remains high.

Publication Top Notes

  • Computer vision-based non-contact structural vibration measurement: Methods, challenges and opportunities
    • Authors: Cheng, Y., Tian, Z., Ning, D., Chauhan, S., Vashishtha, G.
    • Year: 2025
    • Journal: Measurement: Journal of the International Measurement Confederation
  • Global response expansion for dynamic structures based on the evolutionary orthogonal basis
    • Authors: Liu, F., Guo, J., Tian, Z.
    • Year: 2025
    • Journal: Mechanical Systems and Signal Processing
  • Dynamic performance assessment of offshore wind structures based on root morphology model
    • Authors: Tian, Z., Liu, L., Ji, X., Song, H., Chang, S.
    • Year: 2025
    • Journal: Ocean Engineering
  • Structural health monitoring on offshore jacket platforms using a novel ensemble deep learning model
    • Authors: Wang, M., Incecik, A., Tian, Z., Krolczyk, G., Li, Z.
    • Year: 2024
    • Journal: Ocean Engineering
    • Citations: 4
  • FULL-FIELD STRAIN ESTIMATION FROM MEASURED ACCELERATIONS OF OFFSHORE WIND TURBINE SUPPORT STRUCTURES
    • Authors: Guo, J., Li, Y., Wu, X., Tian, Z., Liu, F.
    • Year: 2024
    • Conference: Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering – OMAE
    • Citations: 1
  • Research on collision identification between ships and offshore wind turbines based on neural network
    • Authors: Guo, Z., Tian, Z., Wang, B., Han, L.
    • Year: 2023
    • Conference: 7th IEEE International Conference on Transportation Information and Safety, ICTIS 2023
  • Structural performance degradation identification of offshore wind turbines based on variational mode decomposition with a Grey Wolf Optimizer algorithm
    • Authors: Ji, X., Tian, Z., Song, H., Liu, F.
    • Year: 2022
    • Journal: Ocean Engineering
    • Citations: 14
  • Fatigue life analysis of monopile foundation offshore wind turbine under coupled multiple loadings
    • Authors: Wang, B., Sun, Z., Xu, C., Tian, Z.
    • Year: 2022
    • Conference: Proceedings of the International Offshore and Polar Engineering Conference
  • Numerical simulation of nanofluid convective heat transfer in an oblique cavity with conductive edges equipped with a constant temperature heat source: Entropy production analysis
    • Authors: Tian, Z., Shahsavar, A., Al-Rashed, A.A.A.A., Rostami, S.
    • Year: 2021
    • Journal: Computers and Mathematics with Applications
    • Citations: 11
  • A Laplace-domain method for motion response estimation of floating structures based on a combination of generalised transfer function and partial fraction
    • Authors: Liu, F., Fu, Q., Tian, Z.
    • Year: 2020
    • Journal: Ships and Offshore Structures
    • Citations: 14