
fayyaz khan
Technology / Internet
Services offered
Dedicated Computer Systems Engineering graduate also a MSCS specialization Artificial Intelligence and Data Science. Proficient in programming languages including Python, C, and C#, Java with hands-on experience in deep learning frameworks such as TensorFlow and PyTorch. Skilled in designing and implementing innovative solutions, with a strong focus on driving technological advancements. Currently serving as Manager AI at Stingray Tech, bringing advanced AI solutions and impactful innovations to the organization. Previously contributed over 2 years in academia, teaching and fostering student learning alongside technological research.
Experience
Manager - AI
Stingray Tech | Jan 2025 – Present
Leading the development of a real-time object detection system for safety checks on tank lorry vehicles using YOLOv8.
Focused on detecting components like fire extinguishers, railings, and verifying driver safety gear (helmet, gloves, shoes, seatbelt).
Research Project
GNSS Spoofing Detection using machine learning techniques on datasets (Taxbet and Oakbet) to improve signal security in GNSS systems.
Lab Engineer
KIET (Karachi Institute of Economics & Technology) | Feb 2022 – Dec 2024
Taught and mentored students in programming (C, C++, C#, Python), algorithms, and AI/neural networks.
.NET Intern
Honda New Autos | Jul 2021 – Dec 2021
Contributed to the development and enhancement of the bike portal using the .NET framework.
Education
MSCS – Artificial Intelligence & Data Science
Mohammad Ali Jinnah University | 2022 – 2024 | CGPA: 3.67
Coursework includes: Machine Learning, Deep Learning, Data Science, and Information Retrieval.
Thesis: Pothole Detection Using Deep Learning
Final Year Project: Smart Cart System (autonomous shopping cart with navigation and obstacle avoidance).
BE – Computer Systems Engineering
Mohammad Ali Jinnah University | 2017 – 2021 | CGPA: 3.41
Major projects include pothole/crack detection using YOLOv5, face recognition with DeepFace, and ML models on real-world datasets (MNIST, PIMA, Titanic).
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