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Karachi
fayyaz khan

fayyaz khan

AI & Software Engineer

Technology / Internet

Karachi, سندھ

Social


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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.

Approximate rate: PKR₨ 3,000 per hour

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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