Los Angeles, CA 319-***-**** acwrbs@r.postjobfree.com

https://github.com/mhfarahani https://www.linkedin.com/in/mehrdadhfarahani

No visa sponsorship required.

SUMMARY:

More than 10 years of programming experience for the engineering and data analysis applications.

Expertise in applying computational intelligence (e.g. artificial neural networks) and machine learning techniques (regression, classification, and clustering) to applications in science and engineering.

TECHNICAL SKILLS:

Programming Languages: Python, Fortran, C++, R, MATLAB/Octave

Libraries/Packages: Numpy, Matplotlib, Pandas, Scikit-Learn, Tensorflow, IPython/Jupyter notebook, Parallel Programming (MPI, PETSC)

Databases/Frameworks: SQL, Hadoop, Spark

Version Controls and Operating Systems: Git, Windows, LINUX

PROJECT EXPERIENCE:

Voice Clustering: July 2016 – Present

Developed a pipeline to compress formants of vowels using PCA and clustered them based on their voice qualities using K-Means method.

Identifying Claim Denials: May 2016 – Jun 2016

Applied RandomForest and OneClassSvm on a healthcare data set to predict claim denials and detect anomalies (99% confidence in predicting the desired class).

Artificial Intelligent Based Control: Sep 2005 – Feb 2009

Designed a fuzzy neural network-based controller to improve robustness of axial flow compressors against unseen aerodynamics conditions. The system uncertainties were predicted using an RBF neural network model.

Designed an adaptive neural network-based controller to control an underwater remotely controlled vehicle.

Neural Network Modeling of Aerodynamic Instabilities: Sep 2003 – Jul 2005

Developed and trained an artificial neural network model on experimental data to predict aero-dynamic instabilities in the axial flow compressors. The architecture of the neural network was optimized using a genetic algorithm.

WORK EXPERIENCE:

University of Iowa, Iowa City, IA

Postdoctoral Research Scholar, Department of Biomedical Engineering, Jun 2014 – Present

Computational aeroacoustics modeling of human phonation.

University of California Los Angeles (UCLA), Los Angeles, CA

Postdoctoral Research Scholar, Department of Head and Neck Surgery, December 2013 – Jun 2016

Developed and validated computational models of human phonation.

University of Iowa, Iowa City, IA

Graduate Research Assistant, Department of Biomedical Engineering, August 2009 –December 2013

Developed a massively parallel computational fluid dynamics solver and a high-order aeroacoustic solver.

Conducted fully resolved simulations of the airflow using more than 40 million computational grid points. The simulations were performed in parallel using 280 cores of Helium high-performance computing center at the University of Iowa.

Azad University of Damavand, Damavand

Lecturer, Department of Mechanical Engineering, February 2009 – Present

Taught a course on “Fundamentals of thermodynamics” and mentored associated laboratories.

University of Guilan, Rasht

Research Assistant in the Department of Mechanical Engineering, September 2003 – February 2009

Designed neural network based models and controllers for engineering applications.

Developed computational codes for fluid and structural mechanics simulations.

MACHINE LEARNING TECHNIQUES:

KNN, Logistic Regression, Naive Bayes, SVM, Decision Trees, Random Forest, AdaBoost, PCA, K-Means, Gaussian Mixture, One Class Svm, Elliptic Envelop, Neural Networks.

EDUCATION:

Ph.D. Biomedical Engineering, The University of Iowa, Iowa City, Iowa 2013

M.Sc. Mechanical Engineering, University of Guilan, Rasht 2008

B.Sc. Mechanical Engineering, University of Guilan, Rasht 2005

INDEPENDENT COURSE WORKES:

Coursera: Machine Learning (Instructor: Andrew Ng)

Udacity: Deep Learning, Machine Learning Engineer (NANODEGREE), Data Analyst (NANODEGREE)

LANGUAGES:

English (fluent), Farsi/Persian (fluent/native)

SELECTED PUBLICATIONS (6/28):

1.Farahani, M. H., Zhang, Z., 2016, “Experimental validation of a three-dimensional finite-amplitude nonlinear continuum model of phonation” The Journal of the Acoustical Society of America, 140 (2), EL172-EL177.

2.Farahani, M. H., Mousel, F. Vigmostad, S., 2014, “A High-Order Cartesian-Grid Finite-Volume Method for Aeroacoustics Simulations,” The Journal of the Acoustical Society of America, 136, 2224.

3.Farahani, M. H., Zhang, Z., 2014, “A computational study on the effect of intraglottal vortex-induced negative pressure on vocal fold vibration,” The Journal of the Acoustical Society of America, 136, EL369-EL375.

4.Farahani, M. H., Mousel, J., Alipour, F., and Vigmostad, S., 2013, "A Numerical and Experimental Investigation of the Effect of False Vocal Fold Geometry on Glottal Flow," Journal of Biomechanical Engineering, 135(12), pp. 121***-******.

5.Javadi Moghaddam, J., Farahani, M. H., and Amanifard, N., 2011, “A Neural Network-Based Sliding-Mode Control for Rotating Stall and Surge in Axial Compressors,” Applied Soft Computing, 11(1), pp. 1036-1043.

6.Amanifard, N., Nariman-Zadeh, N., Farahani, M. H., and Khalkhali, A., 2008, “Modelling of Multiple Short-Length-Scale Stall Cells in an Axial Compressor Using Evolved Gmdh Neural Networks,” Energy Conversion and Management, 49(10), pp. 2588-2594.

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