Available Open to ML Research & Engineer roles — Ph.D. — Electrical Engineering

Hi, I'm Pegah Mansourian

Driven AI and cybersecurity researcher with a deep focus on designing resilient, intelligent systems for real-world applications. Passionate about applying advanced machine learning techniques to solve complex security challenges in connected and autonomous environments.

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Personal Details

Email: pegah@mansourian.me

LinkedIn: linkedin.com/in/pegah-mansourian

Location: Canada/Toronto

I Am a Machine Learning Researcher and PhD in AI Security

I am a PhD researcher at the University of Windsor specializing in adversarial ML and intrusion detection for vehicular networks. My work bridges deep learning theory and real-world security challenges in intelligent transportation systems.

What I Do

I am a cybersecurity-focused AI researcher specializing in machine learning, deep learning, and anomaly detection for Connected Autonomous Vehicles. My work explores transformer-based intrusion detection and adversarial robustness, with publications in leading IEEE journals and Springer conferences.

Core Expertise

Machine Learning
Deep Learning
Artificial Intelligence (AI)
Anomaly Detection
Intrusion Detection Systems (IDS)
Adversarial Machine Learning
Reinforcement Learning
Transformer-based Architectures
Generative AI
Generative Adversarial Imitation Learning
AI-Driven Behavioral Analysis

AI & Security in Autonomous Systems

Cybersecurity for Intelligent Transportation Systems (ITS)
Secure AI for Autonomous Mobility
Vehicular Network Security (V2X, V2V, V2I)
Applied AI in Cyber-Physical Systems (CPS)
Adversarial Robustness Testing
Security Policies
Communication Protocols
Information Security

Tools & Programming

Python
C++
Linux
SQL
Microsoft SQL Server
TensorFlow
PyTorch
Scikit-learn
NumPy
LaTeX

Data & Modeling

Statistical Data Analysis
Feature Engineering
Predictive Modeling
Data Classification
Data Visualization
Optimization Models
Data Analytics
Data Modeling
Engineering Statistics

Platforms & Technologies

Azure
Edge AI / On-Device AI
Git/GitHub
VS Code / Jupyter Notebook

Academic, Teaching & Collaboration

Research Design & Methodology
Curriculum Development
Graduate-Level Teaching
Scientific Writing & Publication
Interdisciplinary Collaboration
Presentation & Communication Skills
Leadership & Mentorship

Academic Background

My research spans AI-based intrusion detection, adversarial robustness, and anomaly detection in connected autonomous vehicles. I have published 6 peer-reviewed papers in IEEE journals and Springer conferences.

Ph.D. — Electrical Engineering

University of Windsor

Advisor: Dr. Ning Zhang

Dissertation: "Connected Autonomous Vehicles Cybersecurity: Anomaly Detection and Adversarial Robustness"

Sep 2021 – Nov 2025

Conducting advanced research on AI-based intrusion detection for Connected Autonomous Vehicles, focusing on anomaly detection and adversarial robustness.
Designed and evaluated deep learning models (LSTM, MLP) for CAN and VANET intrusion detection with >99.9% accuracy on intra-vehicle attacks.
Designed and implemented adversarial training pipelines to evaluate and enhance model robustness across multiple attack types.
Developing a transformer-based IDS using the Informer architecture to capture spatiotemporal patterns in VANET data.
Exploring Explainable AI and Low-Rank Adaptation (LoRA) as future work for scalable and trustworthy AI security models.
Published 5 peer-reviewed papers in top IEEE journals and Springer conferences.

MSc. Researcher

Amirkabir University of Technology

Advisor: Dr. Mehdi Dehghan

Thesis: "Anomaly Detection in Internet of Things: Fog and Cloud Hierarchical Approach"

Sep 2017 – Feb 2020

Conducted research on spatiotemporal correlation detection in IoT data using machine learning techniques.
Implemented a distributed machine learning model on edge nodes with Convolutional LSTM to enhance anomaly detection, reducing response time and privacy risks.

Industry Experience

Before and during my PhD, I gained hands-on engineering experience in network solutions and security, which informs my applied research perspective.

Transmission Solution Manager

Huawei Technologies Services Sep 2020 – Aug 2021

Designing technical optical transmission network solutions and strategies.
Working closely with project management, service delivery, and other solution teams on technical deliverables.
Developing opportunity, lead, proposal, bidding and contract for the sales projects.

Senior Network and Security Engineer

Hamrah-e-Aval 2018 - 2021

Designing test plans, procedures, scenarios, and scripts according to customer requirements and company policies.
Identifying, analyzing and creating detailed records of problems that appear during testing.
Creating detailed, step‐by‐step documentation of test procedures.

Interests

My interests lie at the intersection of artificial intelligence and cybersecurity, with a focus on making autonomous systems smarter, safer, and more trustworthy.

Research Interests

Adversarial Machine Learning & AI Security

In-depth research on adversarial robustness, focusing on the development of secure AI systems, especially for autonomous vehicles and critical systems.

AI for Autonomous Vehicles & Security

Advanced work on AI-driven intrusion detection and anomaly detection in vehicular networks, emphasizing vehicle-to-everything (V2X) security protocols.

Explainable AI (XAI) & Robustness Testing

Researching methods for making AI systems more transparent and understandable, especially in high-risk environments like autonomous driving and healthcare.

Edge AI & IoT Security

Research on enhancing AI models for edge computing and IoT security, developing solutions for real-time anomaly detection and privacy preservation at the edge.

Generative AI for Cybersecurity

Exploring the use of Generative AI models, such as GANs, for creating synthetic data and simulation-based testing for security threat models and intrusion detection.

Blockchain & Machine Learning in IoV

Research on the integration of blockchain with machine learning to secure data integrity in Internet of Vehicles (IoV) and autonomous systems.

Professional Interests

AI Security & Adversarial Robustness

Designing secure AI systems capable of mitigating adversarial attacks and ensuring robustness in production environments, including autonomous and smart systems.

Generative AI & Data Augmentation

Exploring applications of Generative AI in cybersecurity, from synthetic data generation for model training to adversarial attack prevention and defense simulations.

Edge AI & Real-Time Anomaly Detection

Focusing on edge AI for IoT devices, implementing real-time anomaly detection and predictive models for edge computing environments in autonomous vehicles and industrial systems.

Scalable AI Solutions & Cloud Integration

Designing cloud-based AI solutions that are scalable, reliable, and optimized for real-time security operations across distributed environments, including AWS, GCP, and Azure.

AI-Powered Threat Detection Systems

Building AI-powered threat detection systems to identify vulnerabilities and provide predictive insights for cybersecurity defense in connected, autonomous environments.

Publications

I believe research is a way to shape the future — each publication reflects not only a solution, but a step toward safer, smarter, and more secure intelligent systems.