Embarking on a journey of scientific discovery and innovation, I am Mohammad Sarabian, a trailblazing Computational Fluid Dynamics (CFD) scientist and Artificial Intelligence (AI) expert dedicated to pushing the boundaries of what is possible in the realm of biomedical sciences and beyond. With an unwavering passion for leveraging cutting-edge technologies to solve complex problems, I have carved a unique path that has led me to my current role at W.L. Gore & Associates, where I spearhead the development of groundbreaking computational tools and deep learning models to optimize medical device design and performance.
My academic journey began with a solid foundation in mechanical engineering, earning both my bachelor’s and master’s degrees from the prestigious Shiraz University in Iran. Fueled by an insatiable curiosity and a drive to make a meaningful impact, I pursued my doctoral studies at Ohio University, where I delved into the intricacies of experimental investigations and direct numerical simulations of rigid particles in shear flows of Newtonian and complex fluids. Under the guidance of esteemed mentors, including Dr. Sarah Hormozi, Dr. Luca Brandt, and Dr. Bloen Metzger, I honed my skills in advanced experimental techniques, computational modeling, and high-performance computing, setting the stage for a transformative career at the intersection of CFD, AI, and biomedical sciences.
Prior to my current role, I had the privilege of serving as a postdoctoral research associate at the University of Arizona’s Department of Biomedical Engineering, where I made significant strides in elucidating the complex mechanisms underlying cerebrovascular diseases. By developing a novel deep learning framework, the “Area Surrogate Physics-Informed Neural Network” (AS-PINN), I achieved the remarkable feat of predicting cerebral blood flow hemodynamics with an unprecedented level of spatiotemporal resolution. This groundbreaking work, validated through comparisons with clinical 4D flow MRI data, not only advanced our understanding of cerebrovascular diseases but also laid the foundation for AI-driven diagnostic tools that have the potential to revolutionize patient care.
My expertise in AI further flourished during my tenure as an AI researcher at Origen.ai, where I developed state-of-the-art deep learning algorithms and reduced-order models for groundwater resource management. By pioneering a physics-informed neural network (PINN) algorithm, I created an innovative surrogate model capable of simulating complex subsurface flows with unparalleled speed and accuracy, marking a significant paradigm shift in the field of porous media.
Throughout my professional journey, I have consistently demonstrated a commitment to bridging the gap between computational simulations and real-world applications. My research has been featured in renowned scientific publications, such as IEEE Transactions on Medical Imaging, Acta Biomaterialia, and the Journal of Fluid Mechanics, showcasing the depth and breadth of my expertise.
As I continue to explore new frontiers in AI-driven CFD and biomedical engineering, I am fueled by an unwavering determination to develop transformative solutions that address the most pressing challenges faced by industries and communities worldwide. By combining my multidisciplinary background, technical prowess, and creative problem-solving skills, I am poised to make a lasting impact and inspire the next generation of innovators and researchers.
Join me on this exhilarating journey as we unlock the boundless potential of computational sciences and AI to shape a future where innovation knows no limits.