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Dr. Fazli is a Computer Scientist who got his Ph.D. under the supervision of Dr. Shannon Quinn in the Computer Science Department of The University of Georgia. His Ph.D. dissertation title is “SUBMiT: Scalable and Unsupervised Biomedical Tracking” in which he developed various novel pipelines for tracking the cells and clustering the motion phenotypes in both 2D and 3D Microscopy videos. He also developed deep computational architectures that incorporate unsupervised object detection and probabilistic object tracking.

Previously, He also got his Doctorate in Business Administration from the University of Montesquieu Bordeaux IV under the supervision of Prof. Jean Fabrice Lebraty. Moreover, formerly, he got his master’s in Artificial Intelligent and Robotics in Iran.

His Computer Science Ph.D. research was focused on developing novel computational tools for segmentation, tracking, and modeling biological systems to examine multiscale spatiotemporal dynamics of those systems under different conditions. His dissertation is mainly focused on how these spatiotemporal changes can be quantified and modeled to predict how the system under observation will respond to certain stimuli (drugs, pathogens, toxins).

His expertise includes computer vision, machine learning, big data, and deep learning applications in biomedical image analysis and motion modeling.