NAHID BABAZADEH KHAMENEH

Montréal, Québec, Canada / +1-514-***-**** / adhzbm@r.postjobfree.com Education

****-****: Ph.D. Student, Department of Computer Engineering and Information Technology (IT), École de Technologie supérieure, Montréal, Québec, Canada. 2007-2011: M.Sc. Department of Engineering, Science and Research branch of Islamic Azad University, Tehran, Iran. Student in Artificial Intelligence. 2003-2005: B.Sc. Department of Engineering, Islamic Azad University, Zanjan, Iran. Student in Computer Engineering (Software).

1996-1999: Associated Diploma, Dr. Shariaty Technical Faculty, Tehran, Iran. Student in Applied Computer.

Professional Skills

Computer Vision: 3D model reconstruction, 3D pose and scale estimation, Statistique computer vision, Motion tracking, Image registration, Image segmentation, Image classification, Pattern recognition, Face recognition, Multi-object detection.

Deep Learning: Convolutional neural network (CNN), Deep neural network (DNN), Adapted nero fuzzy Inference system (ANFIS).

Machine Learning: SVM, MLP, PCA, Random forests, Agent-based learning, Advance artificial intelligence algorithms, Genetic Algorithm, Ant colony algorithm. Data Mining: Big data

Natural Language Processing: Text mining and classification. Programming Languages & Software: Python, C, C++, Visual Studio.net, Asp.net, Bash, Git, Matlab, R, SPSS.

Libraries: TensorFlow (gpu-version), Keras, PyTorch, Jupyter Notebook, Spyder, Scikit-Learn, NLTK, Numpy, Pandas, Pillow, OpenCV

Database Package: SQL, SQL server, Oracle.

Computer Operating System: Linux, Unix.

Application Software: LaTex.

Work Experience

Research engineer in computer vision and deep learning @ Orthopedics and Imaging Laboratory (LIO); ISO 13485:2016, Research Center of Montréal University Hospital

(CRCHUM), École de technologie supérieure (ÉTS), Montréal, Québec, Canada Jan. 2016 - Now

Fully automatic patient-specific 3D bone pose and scale estimation from 2D bi-planar radiographs using deep convolutional neural network (CNN)-based registration framework.

Fully automatic patient-specific 3D model reconstruction (shape and scaling) of the bone structures using training multi-layer CNNs.

Fully automatic multi-view patient-specific 3D model reconstruction of the bone structures from 2D multi-acquisitions.

Research engineer in computer vision and deep learning @ Sarem Cell Research Center (SCRC), Sarem Women's hospital, Tehran, Iran, Jan 2008-Sep 2013

Microscopic images acquisitions of normal and abnormal red blood cells using CCD-Camera, Medical Image Processing, Feature extraction, Detection, Segmentation and classification of normal and abnormal samples using deep neural networks and adaptive neuro-fuzzy inference system, Computer-aid diagnostics.

Software engineer & database administrator (DBA) @ Computer & Information Technology

(IT) Center of Azad University, Tehran, Iran, Sep 2005 – Jun 2014

Analyze operator requirements, design and develop software programs to provide an official application to manage and process students and staffs’ information with C++, VB. Net, Asp.net

Build, tune, and maintain SQL server databases’ structure, manage the database’s performance, manage users and security.

Software engineer intern @ Department of informatics of IRIB organization, Tehran, Iran, Sep 2004 – Sep 2005

Web programming with VB.Net, Web designing with PHP, System analysis with UML software.

IT support technician @ Computer & Information Technology (IT) Center of Azad University, Tehran, Iran, Feb 1999 – Sep 2004

Member of IT operations team, maintain, resolve and supervise the use of LANS, maintain the internet, intranets, and extranets of the university, analyze and design SQL server databases. Publications

N. Babazadeh Khameneh, H. Arabalibeik, S. Setayeshi, “Detection of hypochoromic anemia in blood sample microscopic images using adaptive network-based fuzzy inference system,” Journal of Computational Methods in Science and Engineering, vol. 14, pp. 385-394, 2014.

N. Babazadeh Khameneh, H. Arabalibeik, P. Salehian, S. Setayeshi, “Abnormal red blood cells detection using adaptive neuro-fuzzy system,” Journal of Studies in Health Technology and Informatics, vol. 173, pp. 30-34, 2012. PMID: 22356952 (PubMed-indexed for MEDLINE)

Nahid Babazadeh Khameneh, Carlos Vazquez, Thierry Cresson, Frédéric Lavoie, Jacques de Guise, “Highly accurate automated patient-specific 3D bone pose and scale estimation using bi-planar pose-invariant patches in a CNN-based 3D/2D registration framework,” Submitted In: IEEE-ISBI, 2021.

Conferences

Nahid Babazadeh Khameneh, Thierry Cresson, Christine Bakhous, Carlos Vazquez, Jacques de Guise. Automatic 3D pose estimation via co-trained CNN models, 39th SICOT Orthopaedic World Congress, Montréal, Québec, Canada, October 2018.

Nahid Babazadeh Khameneh, Thierry Cresson, Christine Bakhous, Carlos Vazquez, Jacques de Guise. Multi-trained ensemble CNN regression model for 3D pose estimation, 38e Journée de la Recherche du POES et de la Division d'Orthopédie de l'Université de Montréal, L’Hôpital Sainte-Justine, Montréal, Québec, Canada, May 2018.

Teaching Experience

TA for Engineering Math. & Differentiation (Fall 2019), Artificial Intelligence & Genetic Algorithm

(Winter 2013), Computer Programming C++ (Fall 2012), Data Structure & Algorithms (Summer 2012) Language

English: Fluent, Certificate of Proficiency in English-Language and Culture, McGill University, Montréal, Québec, Canada, Dec. 2015.

French: Fluent, Certificate of TCFTP, TCFQ.

Turkish (Azari): Mother tongue.

Persian: Native Speaker.

MEMBERSHIP AND VOLUNTEERING EXPERIENCES

Volunteer for SICOT 2018.

Student member of association in engineering, computing and technology (IEEE), 2011-Now.

Student member of RBIQ, Oct 2017 - Now.

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