yasin.dehfouli

Professional and research background

I am a cybersecurity engineer with experience in detection engineering, endpoint and identity security, vulnerability management, and incident response. My operational work has included establishing controls in a startup environment, improving telemetry coverage, validating detections, and supporting investigations.

My research and engineering work extends into digital forensics and AI methods for security analysis. I build Python tooling and reproducible pipelines for Volatility-based investigations and have co-authored peer-reviewed work on applied machine learning for malicious-process detection, keeping evidence, evaluation, and analyst interpretation central.

Experience

Security Engineering Associate - Detection & Secure Delivery

Hadeth

Building the security capability that lets a startup deliver with stronger operational confidence and customer-ready assurance.

Hybrid security foundation

Bringing network, identity, endpoint, backup, and privileged-access controls into a defensible operating baseline.

Detection that can be trusted

Developing ATT&CK-informed Wazuh detection and triage routines around testing, context, and repeatable response.

Security in delivery

Embedding code, dependency, container, and application checks into releases with clear ownership of findings.

Product assurance

Shaping web, API, and machine-learning release decisions through early threat modeling and practical controls.

Cybersecurity & AI Researcher

Behaviour-Centric Cybersecurity Center, York University

Built the research systems, forensic tooling, and explainable models that carried volatile-memory evidence from controlled collection into analyst-facing investigation and peer-reviewed results.

Forensic automation

Architected and released VolMemLyzer as a resilient Volatility 3 framework for orchestrating plugins and turning raw output into structured investigation evidence.

Reproducible evidence pipeline

Built controlled malware-execution and memory-capture workflows across QEMU, Python, Bash, and PowerShell with synchronized host and network telemetry.

Analyst-centered triage

Developed MemTriage to move large memory captures through scalable analysis, ATT&CK-correlated findings, model overlays, cached review, and reporting.

Explainable malware detection

Published VADViT, combining VAD-derived representations with transformer attention to classify malicious processes while preserving region-level explanations.

Teaching Assistant

York University

  • Software Tools
    Fall 2023 / Winter 2024
    • Guided practical work in Linux navigation, permissions, and system fundamentals.
    • Supported Bash scripting and C programming labs, feedback, and assessment.
  • Introduction to Artificial Intelligence and Logic Programming
    Fall 2024
    • Explained core artificial-intelligence and machine-learning concepts through practical exercises.
    • Supported logic programming, inference, and structured problem-solving coursework.
  • Introduction to Security
    Winter 2025 / Winter 2026
    • Taught cryptography foundations including RSA, hashing, and secure communication.
    • Guided labs on network security, malware, and defensive analysis.
  • Systems Programming
    Fall 2025
    • Supported systems-level programming in C and assembly.
    • Connected Bash workflows with compilation, debugging, and low-level execution.

AI Software Engineer

noICT

Connected intelligent software with real devices, turning voice interaction into dependable smart-home behavior.

Voice-to-action systems

Developed speech and intent workflows that translated natural commands into reliable device actions.

Software-hardware integration

Joined Python and C/C++ services across Raspberry Pi, Arduino, I2C, and infrared-control environments.

Product-level refinement

Improved command routing and user feedback across the boundary between embedded devices and backend services.

Awards and Honors

Academic distinction

Best Master's Thesis Award Nomination

Recognized among the top three master's theses in York University's Electrical Engineering and Computer Science department.

Graduate funding

Graduate Fellowship and Fully Funded Admissions

$67,500 York University Graduate Fellowship, with full-scholarship admissions from UCI, IIT, Drexel, and Western Ontario.

Long-term fellowship

National Elite Foundation Fellowship

Awarded in Iran for sustained academic excellence.

In progress

SC-500

Identity, network, data, compute, and AI workload security controls.

In progress

SC-300

Entra identities, authentication, workload access, and identity governance.

Education

September 2023 / May 2025

M.Sc. Computer Science

York University

GPA
3.9/4.0

September 2017 / August 2022

B.A.Sc. Electrical & Computer Engineering

Amirkabir University of Technology

GPA
3.84/4.0