Electrical Engineering Information Technology

Mohammad Niknazar

Contact: ********.********@*******.*** +1-951-***-****

Residence: New York - Permanent Resident of the United States (Green Card Holder) Areas of Interest:

• Signal Processing, Statistical Signal Processing, Biomedical Signal Processing, EEG and ECG Processing

• Machine Learning, Statistics, Predictive Models, Pattern Recognition, Feature Extraction, Classification

• Computational Neuroscience, Cross-Frequency Analysis

• Bioinformatics, DNA Sequencing Data Analysis, Big Data Analysis Skills:

• Programming: Python, MATLAB, R, SQL, C, LaTeX

• Language: Farsi (native), English (fluent), French (fluent), Spanish (basic), Arabic (basic) Experience:

• Data Scientist at Phosphorus, May 2016 – December 2017. o Hands on Team Lead, two data scientists and two bioinformatics associates o Developed machine learning single-based and ensemble predictive models to estimate the probability of In Vitro Fertilization success (using Python machine learning packages such as scikit-learn and scipy, and R packages) o Performed regression and parametric and nonparametric statistical significance testing on different types of data including continuous, counts and contingency tables (using Python and R) o Built SMN, MLPA and Sanger data analysis and visualization pipelines for genetic data analysis (using Python) o Contributed to normal and tumor Next-Generation Sequencing CNV pipelines

• Postdoctoral Researcher at University of California, Riverside, February 2014 – February 2016. o Developed a machine learning system for automatic detection/classification of rapid eye movements during sleep o Analyzed the effect of sleep spindle oscillations on memory consolidation using signal processing methods

• Electronics Engineer at Varna Control Industry, June 2007 – May 2008. o C/Assembly AVR microcontroller programming

o Circuit design

Education:

• Ph.D. in Electrical Engineering - Signal, Image and Speech Processing, and Telecommunications, Joseph Fourier University Grenoble I, Grenoble, France, 2013.

o Thesis: Extraction and Denoising of Fetal ECG Signals [Link]

• M.Sc. in Electrical Engineering - Biomedical Engineering, Sharif University of Technology, Tehran, Iran, 2010. o Thesis: Analysis of Epileptic Rats' EEG and Detection and Prediction of Epileptic Seizures

• B.Sc. in Electrical Engineering - Electronics, University of Semnan, Iran, 2007. o Thesis: Graphical Interface Software/Hardware Design for AVR Microcontroller Selected Publications:

• B. D. Yetton, M. Niknazar, K. A. Duggan, E. A. McDevitt, L. N. Whitehurst, N. Sattari, and S. C. Mednick,

“Automatic Detection of Rapid Eye Movements (REMs): A Machine Learning Approach,” Journal of Neuroscience Methods, Elsevier, vol. 259, pp. 72-82, 2016. [Link]

• M. Niknazar, H. Becker, B. Rivet, C. Jutten, and P. Comon, “Blind Source Separation of Underdetermined Mixtures of Event-Related Sources,” Signal Processing, Elsevier, vol. 101, pp. 52-64, 2014. [Link]

• M. Niknazar, B. Rivet, and C. Jutten, “Fetal ECG Extraction by Extended State Kalman Filtering based on Single- Channel Recordings,” Biomedical Engineering, IEEE Transactions on, vol. 60, no. 5, pp. 1345-1352, 2013. [Link]

• M. Niknazar, S. R. Mousavi, B. Vosoughi Vahdat, and M. Sayyah, “A New Framework Based on Recurrence Quantification Analysis for Epileptic Seizure Detection,” Biomedical and Health Informatics, IEEE Journal of

(Information Technology in Biomedicine, IEEE Transactions on), vol. 17, no. 3, pp. 572-578, 2013. [Link]

• Other Publications Available at Google Scholar – Over 300 Citations. [Link]

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