I am doing my PhD studies under the supervision of Matthias Bethge. I am working on statistical modeling of natural images and unsupervised representation learning. One goal is to develop new image models and to compare their coding performance to that of existing models. Another goal is to develop new unsupervised learning methods for time-dependent and invariant image representations.

Current Projects:

Multi-Information estimation of natural images:

In this project we are trying to provide good bounds on redundancy of natural images. We use conditional likelihood for providing meaningful bounds on redundancy of natural images.

Elliptically contoured distributions:

Elliptically contoured distributions are generalization of the Gaussian distribution that recently successfully applied for statistical modeling of natural images. In this project I am trying to derive Maximum likelihood estimation for Elliptically Gamma distribution , etc.

Previous Projects:

Hierarchical and Mixture models for natural images:

In this project we applied Hierarchical ICA (a variation of projection pursuit) and mixture of elliptically contoured distributions for modeling natural image patches (Note that it outperformed the state-of-the-art methods for density modeling of natural image patches)
Our Scientific Advisory Report:
Mixture Models and Hierarchical Models of Natural Images
A talk that I gave about it:
Statistical modeling of natural images
Bernstein Conference Abstract :
Hierachical Models of Natural Images

Unbiased Shear Estimation in Weak Gravitational Lensing:

This is the prize-winning method for shear estimation in weak gravitational lensing
Publication:
Spectral Stacking: Unbiased Shear Estimation for Weak Gravitational Lensing
Code:
Implemented algorithm in Matlab

Compression Algorithm:

We derived an effective lossy image compression algorithm. A patent is pending about our proposed algorithm.
Some details:
Method and Device for Image Compression

Complex Wavelet Transform:

This is the work that I did during my Master studies. In my Master thesis, I successfully applied this wavelet for activity detection of fMRI images.
Paper:
Almost Perfect Reconstruction Filter Bank for Non-redundant, Approximately Shift-Invariant, Complex Wavelet Transforms
Code:
A code for applying wavelet transform and inverse wavelet transform for 1D, 2D or 3D signals
Presentaion:
A 45 minute talk about the proposed method

Future Projects:

Causal Learning:

I have become interested in causal inference, especially since it is related to the quantitative aspect of time and its relation to action and causality. I think, I will focus on this question for my next career, provided that I continue working on modern science questions.

Hierarchical Models for Natural Images:

I will use projection pursuit statistical models (An example would be deep networks) for quantitative modeling of natural images. In mathematical science, natural images are considered as two-dimensional array of numbers measured by a device exp. sensor of a ccd camera.

Fractional Shift-Invariant and Steerable Wavelet Transform:

I think, I will be able to extend the result of my paper to fractional and steerable wavelets.

Directional Discrete Cosine Transform:

A meaningful definition for fast directional discrete cosine transform.

Image processing applications:

The image model can be used for different applications like denoising, segmentation, etc.

Video Compression:

Extension of patent for video compression

Lossless Image Compression:

How to use natural image models for lossless compression and how to have a scalable lossless compression

Entropy Coding for Image Compression:

Designing meaningful combination of quantized coefficients as letters for entropy coding of image compression algorithm.

Wavelet for fMRI Data Activity Detection:

It is a second part of my Master thesis that I did not have time to publish it.

Fingerprint Image Enhancement:

It is my Bachelor work that I did not have time to publish an improved version of it

Weak Gravitational Lensing :

I have some ideas to extend proposed shear estimation method for weak lensing power spectrum estimation.

Education:

PhD Student

• Max-Planck-Institute, Tübingen, Germany (July. 07 - ? )

Master of Science degree in Biomedical Engineering

• AmirKabir University, Tehran, Iran (Sept. 04 - Feb. 07)
• Thesis: Statistical Analysis of fMRI images using wavelet transform
• Major GPA: 17.59/20.

Bachelor of Science degree in Electrical Engineering

• University of Tehran, Tehran, Iran (Sept. 00 - Sept. 04)
• Thesis: an effective Algorithm for Fingerprint Enhancement based on Wavelet Transform
• Major GPA: 16.12/20.

Publication:

Journal

1. 1. Hosseini, R. and M. Vafadust: Almost Perfect Reconstruction Filter Bank for Non-redundant, Approximately Shift-Invariant, Complex Wavelet Transforms. Journal of Wavelet Theory and Applications 2(1), 1-14 (11 2008)

Technical Report

1. Hosseini, R. and M. Bethge: Spectral Stacking: Unbiased Shear Estimation for Weak Gravitational Lensing. (186) (10 2009)

Patent

1. Bethge, M. and R. Hosseini: Method and Device for Image Compression. (2009/146933) (submitted) (07 2008)

Computer Skills:

• C/C++/VC++, Matlab
• MSWord/Excel/Powerpoint, LaTeX

AWARDS:

• Reshad Hosseini, Matthias Bethge: prize winning method for the highest performance in the main challenge of GREAT08 PASCAL competition (Gravitational Lensing and Accuracy Testing 2008).
• Award from Ministry of Education, for succeeding in the national scientific Olympiad in Mathematics, Physics, Chemistry
• Award from Ministry of Education, for advancing into the highest stage of the prestigious Kharazmi scientific Olympiad
• Award from Ministry of Education, for obtaining the first spot in the annual scientific contest in Kurdistan province

Foreign Languages:

• English: Proficient
• German: Proficient
• French: Some knowledge
• Arabic: Some knowledge