Amir Jamali

I have over 10 years of experience as a Computer Vision and Data Science researcher and developer, with a strong focus on applied deep learning. My work spans a variety of tasks including classification, object detection, segmentation, and 3D reconstruction for real-world applications developed in C++ and Pythonsuch as fire and smoke detection, face recognition, fall detection, intrusion detection, abandoned object detection, network anomaly detection, and pavement defect analysis

• Concordia University Sep 2020 - May 2023
M.Sc. in Cybersecurity Montreal, Canada
◦ GPA: 3.77/4.00
◦ Thesis: Pavement Defect Classification and Localization Using Hybrid Weakly Supervised and Supervised Deep Learning and
GIS
◦ Proposed a two-stage framework combining Class Activation Mapping (CAM) and supervised segmentation
(U-Net/Mask R-CNN) for efficient road defect detection, trained with GIS-based datasets and achieving up to 97%
precision on crack types.
• Amir Kabir University of Technology (Tehran Polytechnic) Sep 2012 - Apr 2015
M.Sc. in Cumputer Science Tehran, Iran
◦ Grade: 17.07/20
◦ Thesis: Sparse and Dense 3D Face Modelling based on 2.5D AAM Approach from a Single Image
◦ Proposed a modified 2.5D AAM-based framework to estimate 3D face pose and reconstruct dense 3D face models
from a single image, using camera calibration for pose recovery and enhancing recognition with 3DLBP features.
• K. N. Toosi University of Technology Sep 2001 - May 2006
B.Sc. in Electronics Tehran, Iran
◦ Grade: 16.03/20
◦ Thesis: Three Phase Three Level Matrix and Diode Clamp DC/AC Inverter