Hello, I am

Amr M. Saber

Applied AI Research Scientist at the University of Toronto | Teaching Fellow at Queen's University

About Me

PhD Candidate at University of Toronto

My research integrates various AI methodologies, such as Machine Learning, Deep Learning, Reinforcement Learning, and Systems Control, to create AI systems that safeguard our critical infrastructure, including hospitals, transportation systems, and the electric grid, against cyber threats.

Teaching Fellow at Queen's University

I have extensive teaching experience covering a diverse range of subjects, including Probability, Statistics, Deep Learning, Control Systems, Engineering Design, Energy Systems, and Cybersecurity. Currently, I am the instructor for a senior course in Computer Vision at Queen's University.

Links

  •   amr.mohamedsab@gmail.com

My Expertise

AI
Artificial Intelligence (AI)

In my roles as a lifelong student, research scientist, and educator, I have developed a deep comprehension and practical expertise in various AI disciplines, including machine learning (ML), deep learning, reinforcement learning (RL), optimization, and systems control. Additionally, I have created AI solutions using a diverse range of ML frameworks, such as PyTorch, Scikit-learn, TensorFlow, StableBaselines, Flux, and more.

ICS Security

My research focuses on addressing the IT and OT security of Industrial Control Systems (ICS) to establish comprehensive security. I am well-versed in ICS security standards, such as ISA/IEC-62443, and familiar with cyber threat frameworks, including MITRE ATT&CK and the Cyber Kill Chain.

Energy Systems Engineering

My educational background is founded on a broad understanding of energy systems, encompassing power electronics, power system generation and distribution, power systems stability, protection, and control, as well as renewable energy systems. I have extensively investigated these principles in my research.

Autonomous Driving

I am deeply passionate about self-driving, While my research focus aligns seamlessly with the vision of enabling safe autonomous vehicles, I actively engage in learning and contributing to the field of autonomous driving. I am a former member of AUToronto, the renowned University of Toronto autonomous driving club, and currently, I instruct a design course on computer vision for autonomous vehicles.

My Resume

Education

PhD, Electrical and Computer Engineering

University of Toronto, Toronto, ON, Canada

Expected Graduation: June 2024

GPA: 4.0/4.0

Ontario Graduate Scholar. Alexander Graham Bell Graduate Scholar. Edward S. Rogers Sr. Research Fellow.

MASc, Electrical and Computer Engineering

University of Toronto, Toronto, ON, Canada

Graduation: June 2020

GPA: 4.0/4.0

Edward S. Rogers Sr. Research Fellow. Hatchery Entrepreneurial Fellow.

BASc, Engineering Science

University of Toronto, Toronto, ON, Canada

Graduation: June 2017

Major GPA: 3.97/4.0

Honours Graduate. Dean's List. Minor in Business.

Experience

Teaching Fellow

Queen's University & University of Toronto | Jan. 2019 - Present

I instructed a senior course on Control Systems during the Fall 2023 semester at Queen's University and am currently teaching a course on computer vision for autonomous vehicles.

Research Scientist

University of Toronto | Jan. 2019 - Present

I am enabling AI systems to facilitate safe decision-making for industrial control systems that enhances their cyber-resilience.

Electrical Engineering Intern (EIT)

Hatch Ltd. Consultancy | Jul. 2017 - Aug. 2018

I completed engineering design projects for some of the largest mines globally. Notably, I led the design, deployment, and troubleshooting for a process upgrade at the largest gold mine in the Americas, managing a team of 30+ technicians.

Data Analyst

Ontario's Electricity System Operator (IESO) | May 2015 - Jun. 2016

I developed 3 automated data analytics and visualization projects aimed at distilling electricity market data, identifying trends, and narrating developments to distill key insights.

My Skills

Programming Languages

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Machine Learning Frameworks

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Data Science and Visualization Libraries

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Technologies

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My Projects

d
Reinforcement Learning for Cyber Threat Modelling

In this research project, I leverage deep Reinforcement Learning to create agents that can model cyberattackers, replicating the strategies with which they can potentially harm our critical infrastructure.

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Reinforcement Learning for Combined Cyber Threats

In this research project, I leverage deep Reinforcement Learning to create agents that can replicate the coordination between multiple cyber threats attacking our critical infrastructure.

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Deep Learning for ICS Security

In this research project, I develop multiple deep learning algorithms, including Autoencoders, LSTM, and CNN networks, to enhance cyber threat detection and response in industrial control systems.

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d
Variational Autoencoders on MNIST

In this project, I use variational autoencoders to investigate the use of deep learning in generating images and reconstructing corrupt or incomplete images.

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d
Using Games and Animations in Education

In this teaching project, I develop new innovative Python-based labs to support learning in a new Signals and Systems course at Queen's University. The labs are based on the use of animations and games to engage students and improve their learning and recollection.

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d
Computer Vision

Zoaq was a computer vision project for which I was selected as a University of Toronto's Engineering's Hatchery entrepreneurial fellow. The project aimed to provide computer vision API for the fashion industry, and took on vision for men's hair-cutting as an initial design problem.

Go to Zoaq's webpage
d
Safe AI for Control

In this research project, I develop safe Reinforcement Learning Algorithms to enable physics-aware safe AI decision making in safety-critical systems.

Coming Soon