Is this you?
We are always looking for
smart people! Send us your resume and ideas of collaboration!
Is this you?
We are always looking for
smart people! Send us your resume and ideas of collaboration!
Alumni
Jose Antonio Padrón
My PhD thesis was about
developing a new family of anomaly change detection algorithms for remote sensing image
processing and geoscience time series analysis.
J. Emmanuel Johnson
My research at ISP involved feature
learning and dependence estimation using kernel methods and multivariate Gaussianization with
applications in Earth observation.
Daniel Heestermans Svendsen
I am working on machine
learning methods for remote sensing and earth observation data. My current focus is on
kernel methods, and the incorporation of physical knowledge in statistical methods.
Benyamin Kheradvar
I am working on convolutional
versions of linear + nonlinear models of visual neuroscience and using those in visual
prosthesis and image quality metrics.
Sal Catsis
I'm working on causal discovery from
observational data, and in particular to study climate-induced human migrations.
Marina Martínez-García
At IPL I've
been working on computational visual neuroscience, modelling the processes that take
place in the brain from the retinal images until we get information out of them.
Luca Martino
My primary research interests lie in
the area of Monte Carlo methods for Bayesian inference. My specialty is focused on the
random number generation problem and computational methods for stochastic quadrature,
such as rejection sampling, MCMC algorithms and importance sampling techniques.
Soulivanh Thao
My current research interests are
related to statistical methods for the detection and the attribution of climate change
and especially for the attribution of extreme weather events. Attribution methods
usually rely on the analysis of observations and climate model experiments.
Manuel Campos-Taberner
I'm with the UVERS group,
doing my PhD thesis on biophysical parameter retrieval for crop monitoring, in
particular in the FP7 ERMES project, and collaborating with ISP people on GP retrieval
algorithms.
Devis Tuia
In my postdoc at the ISP group, I
addressed a number of machine learning problems related to hyperspectral image
processing including graph adaptation, active learning, and advanced kernel methods.
Juan Gutiérrez
In my PhD I applied advanced
contrast perception models as regularization functionals to solve inverse problems such
as image restoration and motion estimation and studied their connection to image
statistics.
Irene Epifanio
My PhD work (best-thesis award in
Physics and Maths 2003) was focused on perceptual and statistical image representations
for image coding and texture classification.
Raul Santos-Rodríguez
My work at the ISP group
included the development of multiinformation and divergence measures using
Gaussianization transforms.
Gabriel Gómez
In my MSc work I applied accurate
contrast perception models to improve Support Vector Regression in subjective domains
for image coding.
Vicent Talens
In my MSc thesis I worked with a
Kernel generalization of the SSIM image quality index well suited to be applied to
hyperspectral images.
Sandra Jiménez
In my PhD years (best-MSc thesis
award in Computer Science 2013) I analyzed the complexity of spatio-spectral signals for
illumination invariant Bayesian reflectance estimation and hyperspectral image coding.
Marcelo Armengot
During my stay at ISP I used with
Kernel Ridge Regression for image denoising assuming smoothness in the spatial domain.
Yolanda Navarro
In my MSc thesis I applied
nonlinear models of chromatic contrast perception in wavelet domains to improve
JPEG2000.
Jose Rovira
During my MSc work I contributed to
develop nonlinear local-to-global Independent Component Analysis.
Francesca Bovolo
My work at the ISP group included
the analysis of multi-temporal remote sensing image changes, and the definition of
advanced one-class classifiers.
Mattia Marconcini
My work at the ISP group included
the development of semi-supervised one-class classifiers for remote sensing data
classification.
Luca Capobianco
My work at the ISP group included
the development of target detection algorithms for remote sensing data analysis.
Helena Burriel
At ISP I built virtual worlds of
controlled spatial arrangement to study the effects of occlusion, perspective and view
point in 2D shape statistics.
Amparo Gil
in my MSc Thesis I developed in cortical
image representations that are simultaneously robust to neural noise and energy
efficient.
Koray Çiftçi
In my stay at IPL I addressed the
problem of decoding the visual signals from simulated and real neural responses.
Emma Izquierdo
My PhD work included kernel-based
nonlinear generalization of classical (linear) feature extraction techniques to improve
classification results in remote sensing.
Fatih Nar
During my a year visit to IPL, I focused
on processing optical images using kernel methods and variational methods, large scale
anomaly change detection methods and digital terrain model (DTM) extraction. It was a
joy to live in Valencia and life-time experience to work with productive and cheerful
researchers in the IPL.
Irene Martin
My research interests include machine
learning and signal processing, especially deep neural networks and transfer learning.
Currently I am working on applying physical constraints to ML models for better
generalization, consistency and extrapolation capabilities.
Borja Galán
My research was tied to study feature representations that are sparse, interpretable and causal. At ISP I have been working in the Causal inference in the human-biosphere coupled system (SCALE) project funded by BBVA and the EC H2020 DeepCube project developing modules for interpretability and explainability in ML models.
Mara DíezWhile I was at ISP, I was conducting fMRI recordings of the visual brain using synthetic and natural images. I was director of the
Optometry
Clinic of the Universitat de Valencia, which has a range of experimental tools for vision research.
Qiang Li
I worked on computational neuroscience
via combined fMRI and image processing techniques to better understand the mechanism of
the human vision system, which efficiently processes and extracts the information from
the natural world.