Research
Statistical signal and image processing, inverse problems, and computational imaging
Research Interests
Statistical Signal & Image Processing
Bayesian estimation, hierarchical models, MCMC methods, and variational inference for signal and image analysis.
Inverse Problems
Regularization techniques, proximal algorithms, ADMM, and optimization-based approaches for ill-posed problems.
Computational Imaging
Model-based deep learning, unrolling, plug-and-play priors, diffusion models, and generative approaches.
Enhanced & Robust Sensing
Single-photon imaging, LiDAR, hyperspectral imaging, altimetry, and multi-modal sensor fusion.
Tools & Methods
Research Areas
Single-Photon Data
Robust 3D imaging, sensor fusion, underwater imaging
Hyperspectral Imagery
Spectral unmixing, endmember variability
Wind Turbine Inspection
Defect detection, drone imaging
Materials Science
EDX data, multiscale modeling
Medical Imaging
fMRI, BOLD signal, image segmentation
Altimetry
Coastal altimetry, delay/Doppler, parameter estimation
Research Group
Current Members
Shu Pan
PhD Student, co-supervised with Y. Petillot
Pallabjyoti Deka
PhD Student, co-supervised with J. Leach & S. McLaughlin
Sabrina Henry
PhD Student, co-supervised with J. Leach
Dr. Sandor Plosz
Post-Doc, co-supervised with J. Leach
Former Members
Dr. Imad Gohar
PhD, co-supervised with S. John
Dr. Alice Ruget
Post-Doc & PhD
Dr. Amir Belmekki
PhD, co-supervised with S. McLaughlin
Dr. Jakeoung Koo
Post-Doc
Dr. Sandor Plosz
Post-Doc
Dr. Songmao Chen
PhD
Dr. Hamza Cherkaoui
PhD, co-supervised with P. Ciuciu