Zhifeng Chen | Biomedical Engineering | Excellence in Innovation Award

Dr. Zhifeng Chen | Biomedical Engineering | Excellence in Innovation Award 

Neusoft Medical Systems Co. Ltd | Australia

Zhifeng Chen, Ph.D., is an accomplished biomedical imaging scientist whose multidisciplinary career spans advanced MRI physics, deep learning–driven neuroimaging, quantitative MRI, and accelerated data acquisition methodologies. With a strong academic foundation from Zhejiang University and extensive postdoctoral training at premier institutions including Harvard Medical School, Massachusetts General Hospital, the University of Southern California, and Monash University he has developed a robust research portfolio focused on rapid, motion-resistant, and high-fidelity MRI techniques. Dr. Chen has made notable contributions to non-Cartesian reconstruction, ASL angiography, fMRI, susceptibility mapping, and liver DCE-MRI, integrating compressed sensing, low-rank subspace modeling, diffusion models, contrastive learning, and untrained neural networks. His expertise extends to pulse sequence programming on Siemens 3T and 7T platforms, advanced signal processing, and deep learning–based image reconstruction. A productive researcher with 26 documents, 214 citations, and an h-index of 9, he has demonstrated sustained scholarly impact across biomedical engineering, radiology, and computational imaging. His work has been recognized through competitive fellowships and prestigious awards, including multiple ISMRM Merit Awards, the International Postdoctoral Exchange Fellowship, and the Shandong Provincial Science and Technology Progress Prize. Dr. Chen has secured numerous grants as Principal Investigator, leading innovations in physics-informed deep learning, motion-corrected dynamic imaging, and quantitative MRI. His professional service includes reviewing for leading journals, coordinating special issues, and evaluating national and international research grants. With extensive experience mentoring students and collaborating across academia and industry, Dr. Chen continues to advance next-generation MRI technologies that enhance imaging speed, robustness, and clinical diagnostic value.

Profile: Scopus | Orcid

Featured Publications 

Chen, Z. (2025). Accelerating multi-directional diffusion MRI through patch-based joint reconstruction. NeuroImage.

Ekanayake, M., Pawar, K., Chen, Z., Egan, G., & Chen, Z. (2025). PixCUE: Joint uncertainty estimation and image reconstruction in MRI using deep pixel classification. Journal of Imaging Informatics in Medicine.

Pouria Mazinani | Biomechanics | Young Scientist Award

Dr. Pouria Mazinani | Biomechanics | Young Scientist Award 

University of Catania | Iran

Dr. Pouria Mazinani is a highly skilled Project Manager and researcher with a multidisciplinary background in Mechanical and Civil Engineering. He holds multiple advanced degrees, including a Ph.D. in Civil Engineering from the University of Catania and dual MSc degrees in Civil and Mechanical Engineering. His research and technical expertise span biomechanics, structural analysis, computational modeling, and fluid mechanics, with a particular focus on the simulation of corneal Young’s modulus using ABAQUS, Python, and Elastography. Dr. Mazinani has demonstrated strong analytical and leadership abilities through his roles at IDRA Quality Inspection Company and IQI Group, where he managed engineering projects, conducted mechanical equipment inspections, and ensured compliance with international quality standards. His academic contributions include five research documents, accumulating 13 citations and an h-index of 2, reflecting his growing impact in the engineering research community. Proficient in a wide range of software tools such as ANSYS, COMSOL, MATLAB, and AutoCAD, he also holds numerous professional certifications in quality management systems, data science, gas turbines, and project management. Dr. Mazinani’s combination of technical expertise, project management acumen, and research excellence underscores his commitment to advancing innovative engineering solutions.

Profile: Scopus 

Featured Publications 

Mazinani, P. (2025). Evaluating corneal biomechanics using intraocular pressure methods and finite element modeling: Parameters study and parametric optimization. Zeitschrift für Angewandte Mathematik und Physik.