Mark A Anastasio

Mark A Anastasio is a Donald Biggar Willett Professor of Bioengineering, Professor at the Siebel School of Computing and Data Science, and holds joint appointments in Electrical and Computer Engineering, Biomedical and Translational Sciences, and Clinical Sciences. He leads the Bioengineering department and is affiliated with the Coordinated Science Lab and Beckman Institute. His research focuses on advanced medical imaging technologies, including photoacoustic computed tomography, ultrasound computed tomography, and deep learning-driven image reconstruction methods. Anastasio has contributed to over 400 publications, including seminal works on improving imaging resolution and accuracy through computational techniques. He has been honored with prestigious fellowships from AIMBE, IEEE, and SPIE, and his work bridges engineering, biology, and clinical applications.

Key research areas include developing novel algorithms for image reconstruction, optimizing imaging systems using Bayesian methods, and integrating AI for medical diagnostics. His datasets, such as 2D acoustic breast phantoms and clinical imaging trials, are widely used in computational studies. Anastasio collaborates across disciplines to advance imaging for cancer detection, neuroimaging, and functional tissue analysis.

His awards reflect recognition for pioneering contributions to biomedical optics and computational imaging. Recent projects include optimizing MRI reconstruction with learned ideal observers and evaluating generative models for medical image statistics. Anastasio actively contributes to academic leadership roles and editorial boards, ensuring scientific rigor and innovation in imaging science.