Note: I do not offer any teaching assistant or grading assistant jobs; please do not contact me for such purposes.

If you are interested in working with me, you are welcome to contact me (students in the Dept. of Mathematics get the priority), but please check my research interests before doing so.
I can suggest you some topics related to signal/image processing, or if you have a topic in mind, do not hesitate to share it with me.

Current Students:

PhD Students:

• Stephanie Young (SDSU-CSRC).
• Juan Sebastian Carillo Rodriguez (SDSU-CSRC)

Graduate Students:

• Shoshana Krishel (SDSU)
• Cameron Deschenes (SDSU)
• Matthew Wallace (SDSU)
• Samuel Persaud (SDSU)

Undergraduate Students:

Past Students:

PhD Students:

• Misha Kurtzman (SDSU-CSRC): signal/image processing in neuroscience.
• Yuan Huang (Visiting student from Beihang University, Beijing, China): Empirical wavelet texture segmentation and classification (2017/2018).
• Gian Tran (UCLA): 2D empirical wavelet transform (2012/2013).
• Travis Meyer (UCLA): electroencephalogram artefacts removal (2013).
• Yohann Tendero (ENS Cachan - France): mathematical theory of the Flutter-Shutter/ Infrared image processing (2012).
• Yu Mao (UCLA): non-rigid image stabilization - correction of atmospheric turbulence (2010).

Graduate/Master Students:

• Sam Rath (SDSU): Characterization of Meditative States by EEG Analysis (2024)
• Aliha Shareef (SDSU): Removal of redundancy kernels in Convolutional Neural Networks (2024).
• Humberto Pena (SDSU): On the mathematical modeling of Convolutional Neural Networks (2023).
• Richard Castro (SDSU): Empirical frames (2023).
• Tim Remiger (SDSU): Classification of potential binge drinkers via machine learning applied to multisource neuroimaging (2022).
• Stephanie Young (SDSU): Fourier based analysis of DNA sequences (2022).
• Tushar Jain (SDSU): Deep learning for atmospheric turbulence mitigation (2022).
• Jesus Perez-Cuarenta (SDSU): Image quality index based on local scales (2021).
• Madeline Lubien: Atmospheric turbulence simulation and deep learning restoration (2021).
• Basile Hurat (SDSU): Data-driven partitioning of the 2D Fourier domain (2020).
• Zariluz Alvarado (SDSU): Empirical wavelet based deblurring (2020).
• Ericka Negroni (SDSU): Tracking of moving targets through atmospheric turbulence (2020).
• Susan Deeb (SDSU): Analysis of Globus Pallidus Local Field Potentials and Electrocorticograms of Patients Diagnosed with Parkinson's Disease (2019).
• Kyle Woolsey (SDSU): Pseudo-spherical Fourier transform (2019).
• Nicholas Ferrante (SDSU): The inspection of moving objects in an optical flow field impacted by a turbulent media and global camera motion (2019).
• Jouie Aymes (SDSU): 2D filtering based on Voronoi partitioning (2018).
• Ludwig Siegert (SDSU): Super-resolution (2018).
• Francis Alvarez (SDSU): Multi-frame image fusion of turbulence degraded images (2017).
• Tony Silveti Falls (SDSU): Empirical Gabor frames (2017).
• Valentin De Bortoli (ENS Cachan - France): unsupervised texture segmentation and empirical wavelets (2014).
• Torin Gerhart (CSULB/UCLA): detection and tracking of gas plume in hyperspectral movies (2012).
• Sylvain Rousselle (ESIEE - France): texture segmentation by fractal embedding (2005).
• Laurent Pigois (ENSEA - France): Simulation of atmospheric turbulence effects by phase screens (2004).
• Melissa Pinel (University of Orsay - France): Local contrast adaptive control for high dynamic infrared images (2003).

Undergraduate students research projects:

• Brooke Tyler (SDSU): Evaluation of atmospheric turbulence mitigation algorithms (2021).
• Crystal Reina (SDSU): Forecasting multiphysics phenomena via machine learning (2021).
• Alex Guiterrez (SDSU): Analysis of Lorentz Transmission Electron Microscopy images 2 (2021).
• Benett Guillaume (SDSU): Analysis of Lorentz Transmission Electron Microscopy (LTEM) images (2020).
• Steven Cozine (SDSU): Image turbulence mitigation (2018).
• Zachary Comejo (SDSU): Early seizure detection (2017).
• Matthew Herman (SDSU): General Topology (2017).
• Victor Arjona (SDSU): Evaluation of super-resolution algorithms (2017).
• Jeremy Juybari (SDSU): Wavelet analysis of financial data (2017).
• Nicholas Ferrante (SDSU): Creation of an open source dataset for imaging through atmospheric turbulence (2016).
• Nicholas Ferrante, Margaret Fortman, Lena Tahir, Alex Tarter, Anneke von Seeger (SDSU - 2016 REU Summer projects): Image processing and restoration under atmospheric turbulence.
• Kathryn Heal (UCLA - Accepted in the graduate program at Harvard): empirical wavelet EEG analysis (2013/2014).
• Ziyu Wang (UCLA - Accepted in the graduate program at MIT): image denoising for electron microscopy (2013/2014).
• Kathryn Heal, Kaitlin Navarro, Margalit Wollner, Eddie Yan (UCLA - 2013 REU Summer projects): epilepsy classification, EEG Analysis, and EEG-fMRI fusion.
• Lauren Lieu, Justin Sunu, Torin Gerhart (UCLA - 2012 REU Summer projects): gas plume detection in hyperspectral movies.
• Jiahui Yu (UCLA - Accepted in the PhD program at University of Massachusetts Amherst): parameter analysis of the Fried deconvolution (2012).
• Lauren Lieu, Hannah Kastein, Will Ferenc, Ryan Wilson (UCLA - 2011 REU Summer projects): robots swarming through the internet.
• Carlo de Franchis (Ecole Polytechnique - France): blind image deconvolution (2008).
• Tristan Dagobert (Conservatoire des Arts et Metiers - France): restoration of infrared images degraded by atmospheric turbulence (2007).
• Anne Favede (ENSERG - France): correction of atmospheric turbulence effects in passive and active imaging (2006).
• Damien Jeandrau (IUT Cachan - France): texture classification by Support Vector Machines (2005).
• Nicolas Widynski (EPITA -France): Semi-automatic road network detection in aerial and satellite images (2005).
• Aurelien Zelty (EFREI - France): segmentation of textured images by Gabor filtering (2003).
• William Phommaly (University of Jussieu - France): non-uniformity noise correction for matrix based camera (2003).