Siamak Yousefi, PhD

Postdoctoral Fellow, UCLA

Department  Department of Radiological Science
Laboratory           Neural Signal Processing (NSP) Laboratory
University

University of California at Los Angeles

Email               s.yousefi *at* ucla.edu

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About Siamak Yousefi

Siamak Yousefi is a postdoctoral fellow at Radiological Science Department of University of California at Los Angeles. He is a member of NSP lab where he is working on the neural signal processing and computer brain interface areas. He was graduated from Erik Jonsson School of Engineering and Computer Science of the University of Texas at Dallas at 2011. During his PhD at UTD, he has collaborated with the Neuroimaging Research Laboratory in Radiology department working on image registration and segmentation from 2008 to 2009 and with Live Cell Imaging Research Laboratory in Cell Biology department of the University of Texas Southwestern Medical Center working on pattern classification from 2009 to 2011. He has been a member of Digital Media Lab (DML), Sharif University of Technology, from 2006 to 2008. He is an active reviewer for several journals including IEEE Transactions on Image Processing, IEEE Transactions on Medical Imaging, International Journal of Machine Learning and Cybernetics and Journal of Systems and Softwares. Yousefi is a member of IEEE and has co-authored more than 25 peer-reviewed articles.

 

Research Overview

My research interests lie in the broad area of signal/image processing, pattern recognition and machine learning with emphasis on medical and biomedical applications. I have conducted research on anatomic magnetic resonance imaging (MRI), atlas-based segmentation, brain's subcortical structure segmentation and second harmonic generation (SHG) image analysis. At the SIP I was mainly working on stochastic lattice (image) modeling based on Markov Random Fields (MRFs) with the application to image segmentation, restoration and texture analysis. At NSP lab in UCLA, I am working on human brain interface and neural signal processing applications to prosthetic devices.