Applied AI researcher with 5+ years of experience in designing and deploying edge AI systems for smart mobility and urban infrastructure. Specialized in LLM post-training, real-time computer vision, and embedded ML. Proven track record of translating research into deployable systems in high-stakes environments such as FIFA 2022 and smart city platforms.

asifk

Applied AI researcher with 5+ years of experience in designing and deploying edge AI systems for smart mobility and urban infrastructure. Specialized in LLM post-training, real-time computer vision, and embedded ML. Proven track record of translating research into deployable systems in high-stakes environments such as FIFA 2022 and smart city platforms.

Available to hire

Applied AI researcher with 5+ years of experience in designing and deploying edge AI systems for smart mobility and urban infrastructure. Specialized in LLM post-training, real-time computer
vision, and embedded ML. Proven track record of translating research into deployable systems in high-stakes environments such as FIFA 2022 and smart city platforms.

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Experience Level

Expert
Expert
Intermediate
Intermediate
Intermediate

Work Experience

Research Scientist (AI) at Qatar Mobility Innovations Center, Doha, Qatar
November 1, 2021 - Present
Designed and deployed a crowd queue length estimation system on NVIDIA Jetson Nano, utilized during FIFA 2022 for real-time metro station load balancing. Developed a multi-modal drone detection pipeline using acoustic, RF, and visual cues, enhanced by attribute-based encryption for unauthorized drone detection. Led end-to-end deployment of on-device CNNs using TensorRT for anomaly detection in road infrastructure. Contributed to Falcon-I smart city platform integration with AI-driven traffic insights.
Research Fellow (AI) at Qatar University, Doha, Qatar
October 31, 2021 - August 2, 2025
Investigated edge-based video surveillance techniques for constrained IoT environments. Developed WiFi AP handover prediction models using machine learning in cognitive wireless networks. Created RoadSense, a smartphone-based road anomaly detection system collecting and fusing multiple sensor data for real-time surface condition classification, deployed on Android. Developed crowd estimation system for metro stations during FIFA 2022 using PTZ cameras and custom CNN models deployed on NVIDIA Jetson Nano. Built acoustic-based detection and localization system for noisy vehicles integrating microphone arrays and various ML models. Developed a multi-modal unauthorized drone detection prototype using acoustic, RF, and visual modalities with secure alert propagation. Designed intelligent construction safety violation system detecting PPE violations with YOLO/Faster R-CNN optimized for Jetson deployment.

Education

Ph.D. at Qatar University, Doha, Qatar
January 1, 2014 - December 31, 2019
M.Sc. at University of Engineering and Technology Taxila, Pakistan
January 1, 2010 - December 31, 2013
B.Sc. at University of Engineering and Technology Peshawar, Pakistan
January 1, 2005 - December 31, 2009

Qualifications

TensorFlow Developer, Deeplearning.ai
January 11, 2030 - August 2, 2025
Deep Learning Specialization, Deeplearning.ai
January 11, 2030 - August 2, 2025
Machine Learning, Stanford University
January 11, 2030 - August 2, 2025
AWS Machine Learning, Amazon Web Services
January 11, 2030 - August 2, 2025
AWS Generative AI, Amazon Web Services
January 11, 2030 - August 2, 2025
AWS AI & ML Scholar
January 11, 2030 - August 2, 2025
AWS Cloud Practitioner
January 11, 2030 - August 2, 2025
Generative AI, Databricks
January 11, 2030 - August 2, 2025
Introduction to On-device AI, Qualcomm
January 11, 2030 - August 2, 2025
Fundamentals of Accelerated Computing with CUDA Python, Nvidia
January 11, 2030 - August 2, 2025
Getting Started with AI and Jetson Nano, Nvidia
January 11, 2030 - August 2, 2025
ChatGPT Prompt Engineering for Developers, Deeplearning.ai
January 11, 2030 - August 2, 2025

Industry Experience

Transportation & Logistics, Government, Computers & Electronics, Software & Internet, Real Estate & Construction

Experience Level

Expert
Expert
Intermediate
Intermediate
Intermediate

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