Maziar Yaesoubi, PhD

Data Scientist and Machine learning engineer at FICO®

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ABOUT ME

As of May 2018, I work as a Data Scientist and Machine learning engineer at FICO®.

I am currently a postdoctoral fellow at the Mind Research Network and my mentor is Dr. Vince D. Calhoun.

My research interests include statistical signal processing as well as machine learning.

My main field of research as a PhD student was analysis of functional aspect of human brain by looking at the brain as a dynamic system during resting as well as various cognitive states. Most of the data that I worked with were fMRI scans of various groups of subjects (Healthy and Diseased) as well as EEG/MEG data. Beside my main research, during the course of my PhD and my internships I had great opportunity of being involved in various other projects such as processing of Infrared images of humans skin for early detection of cancer and high dynamic range (HDR) imaging of dynamic scenes which were all in the line of my main interests of signal/image processing and data analysis.


Please download my Curriculum Vitae here (PDF).


MY EDUCATION

2009 - 2016

University of New Mexico, Albuquerque, NM

Ph.D. in Electrical and Computer Engineering


2007 - 2009

Linköping University, Linköping, Sweden

Master of Science in Computer Science


2001 - 2006

Sharif University of Technology, Tehran, Iran

Bachelor of Science in Computer Engineering


My Google Scholar

Journals

[J8]

A window-less approach for capturing time-varying connectivity in f MRI data reveals the presence of states with variable rates of change

Yaesoubi, M., Adali, T. and Calhoun, V.D.

Human Brain Mapping, vol. 39, no. 4, 2018


[J7]

A joint time-frequency analysis of resting-state functional connectivity reveals novel patterns of connectivity shared between or unique to schizophrenia patients and healthy controls

Yaesoubi, M., Miller, R.L., Bustillo, J., Lim, K.O., Vaidya, J. and Calhoun, V.D.

Neuroimage: clinical, vol. 15, 2017


[J6]

Time-varying Spectral Power of Resting-state fMRI Netwroks Reveals Cross-frequency Dependence in Dynamic Connectivity

Yaesoubi, M., Miller, R.L., and Calhoun, D.

PLoS ONE, 12, no. 2, 2017


[J5]

Cross-Frequency rs-fMRI Network Connectivity Patterns Manifest Differently for Schizophrenia Patients and Healthy Controls

Miller, R.L., Yaesoubi, M., and Calhoun, D.

IEEE Signal Processing Letters, 2016


[J4]

Higher Dimensional Meta-State Analysis Reveals Reduced Resting fMRI Connectivity Dynamism in Schizophrenia Patients

Miller, R.L., Yaesoubi, M., Turner, J., Mathalon, D., Preda, A., Pearlson, G., Adali, T., and Calhoun, D.

PLoS ONE, 11, no. 3, 2016


[J3]

Dynamic coherence analysis of resting fMRI data to jointly capture state-based phase, frequency, and time-domain information

Yaesoubi, M., Allen, E.A., Miller, R.L. and Calhoun, V.D

Neuroimage, vol. 120, 2015

(Winner of the second best journal paper in the "First Annual Student Paper Competition" at ECE department of UNM")


[J2]

Mutually Temporally Independent Connectivity Patterns: A New Framework to Study Resting State Brain Dynamics with Application to Explain Group Difference Based on Gender

Yaesoubi, M., Miller, R.L. and Calhoun V.D.

Neuroimage, vol. 107, 2015


[J1]

Robust Patch-Based HDR Reconstruction of Dynamic Scenes

Sen, P. , Khademi Kalantari, N. , Yaesoubi, M., Darabi, S. , Goldman, D. and Shechtman, E. *

ACM Transactions on Graphics, Vol. 31, No. 6, November 2012, (Proceedings of ACM SIGGRAPH Asia 2012)

*Ordering of the authors for this specific publication does not reflect the actual intellectual contributions of each individual author. Please inquire for details on authors' contributions.

Peer-Reviewed Conference Publications

[C6]

Time-Varying Frequency modes of resting fMRI brain networks reveal significant gender differences

Yaesoubi, M., Miller, R.L., Adali, T. and Calhoun, V.D.

IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Shanghai 2016


[C5]

Meta-State Analysis Reveals Reduced Resting fMRI Connectivity Dynamism in Schizophrenia Across Multiple Multivariate Analytic Techniques

Miller, R.L., Yaesoubi, M. and Calhoun V.D.

Brain Connectivity, Fourth Biennial Resting State Conference, Boston 2014


[C4]

Higher Dimensional Analysis Shows Reduced Dynamism of Time-Varying Network Connectivity in Schizophrenia Patients

Miller, R.L., Yaesoubi, M. and Calhoun V.D.

Workshop on Pattern Recognition in Neuroimaging (PRNI), Tuebingen, Germany 2014


[C3]

Higher Dimensional fMRI Connectivity Dynamics Show Reduced Dynamism in Schizophrenia Patients

Miller, R.L., Yaesoubi, M. and Calhoun V.D.

Engineering in Medicine and Biology Society (EMBC), IEEE 36th Annual International Conference, Chicago, IL 2014


[C2]

Characterization of Connectivity Dynamics in Intrinsic Brain Networks

Calhoun V., Yaesoubi, M., Rashid, B. and Miller, R.L.

IEEE Global Conference on Signal and Information Processing (GlobalSIP), Dallas, TX 2013


[C1]

Applying Finite State Morphology to Conversion Between Roman and Perso-Arabic Writing Systems

Maleki, J., Yaesoubi, M. and Ahrenberg, L.

Frontiers in Artificial Intelligence and Applications; Vol. 191, pp. 215-223. Post-proceedings of the 7th International Workshop FSMNLP 2008


MY SKILLS

My practical skills and knowledge

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Designer

Adobe Illustrator
8 out of 10
After Effects
7 out of 10
Photoshop
9 out of 10
Design skills
10 out of 10

Programer

PHP
9 out of 10
Python
8 out of 10
HTML
10 out of 10
CSS
9 out of 10

MY PORTFOLIO

See my latest work

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