I am the director of the Vision and Image Processing (VIP) Laboratory. Along with my colleagues, we investigate how to improve early diagnostic methods and find new imaging biomarkers of ocular and neurological diseases in adults (e.g. age-related macular degeneration, diabetic retinopathy, Glaucoma, Alzheimer) and children (e.g. retinopathy or prematurity). We also develop automatic artificial intelligence machine learning and deep learning algorithms to detect/segment/quantify anatomical/pathological structures seen on medical images.
On another front, we study efficient signal processing based methods to overcome the theoretical and practical limitations that constrain the achievable resolution of any imaging device. Our approach, which is based on adaptive extraction and robust fusion of relevant information from the expensive and sophisticated as well as simple and cheap sensors, has found wide applications in improving the quality of imaging systems such as ophthalmic SD-OCT, digital X-ray mammography, electronic and optical microscopes, and commercial digital camcorders. We are also interested in pursuing statistical signal processing based projects, including super-resolution, demosaicing, deblurring, denoising, motion estimation, compressive sensing/adaptive sampling, and sensor fusion.
Education and Training
- University of California at Los Angeles, Research Assistant, Electrical Engineering
- University of California at Los Angeles, Postdoctoral Scholar, Electrical Engineering
Selected Grants and Awards
- Quantitative assessment of glaucomatous conventional outflow dynamics
- The BCI (Brain Computer Interface) Glaucoma Study: Objective Home-Based Detection of Progressive Visual Function Loss in Glaucoma
- Compressive aperture super-resolution in vivo microscopy
- Advanced a/LCI systems for improved clinical utility
- Advanced a/LCI systems for improved clinical utility
- Portable motion-stabilized optical coherence tomography for eye care in acute care settings
- Handheld Portable Adaptive Optics Optical Coherence Tomography for Imaging Young Children
- Novel Experimental Model for Pseudoexfolliation Syndrome
- Novel Experimental Model for Pseudoexfolliation Syndrome
- Training in Medical Imaging
- Psychophysics-Guided Signal Processing for Retinal Prosthetics
- Analyzing retinal microanatomy in retinopathy of prematurity to improve care
- Coherent light scattering for early detection of Alzheimer's disease
- Whole Eye Optical Coherence Tomography to Improve Refractive Surgery and Eye Care
- Handheld Portable Adaptive Optics Scanning Laser Ophthalmoscope for Imaging Young Children
- NCS-FO:Real-time optical readout and control of population neural activity with cellular resolution
- RPB: 2014 Nelson Trust Award
- Automated Software for Analysis of Adaptive Optics Scanning Laser Ophthalmoscopy Images
- Flavoprotein Autofluorescence Imaging in AMD
- Computer Aided Classification of Diabetic Macular Edema
- Temporal dynamics of retinal ganglion cell neurodegeneration in glaucoma
- Intraoperative OCT Guidance of Intraocular Surgery
- OCT measurement of TM/SC stiffness in living mice
- Smartphone Ophthalmoscope Lens Vascularity
- UPenn - NEI Follow-up Study: Comparison of AMD Treatment Trials (CATT) YR3
- Knight's Template OCT in Normal Children
- Field Deployable Optical Coherence Tomography for Triage of Ocular Trauma
- Smartphone ophthalmoscope image analysis of lens capsule vascularity to estimate preterm gestational age
- Novel Retinal Biomarkers for Early Detection of Alzheimer's Disease
- Coherent light scattering for early detection of retinal disease
- Coordinating Center for the Comparison of AMD Treatments Trials
- Portable Motion Compensated SDOCT System for Imaging Young Children
- Real Time Intraoperative SDOCT for Vitreoretinal Surgery