Computer Engineering Graduate from NUST, specializing in AI, Machine Learning, and Computer Vision.
Deep learning architectures & neural network optimization
Image processing & pattern recognition systems
Medical image segmentation & diagnostic systems

# Neural Network Architectureclass AIModel: def __init__(self, layers): self.layers = layers self.optimizer = "adam" def forward(self, x): for layer in self.layers: x = layer(x) return x def train(self, data, epochs=100): for epoch in range(epochs): loss = self.compute_loss(data) self.backpropagate(loss) return self.metricsExplore my portfolio of AI and machine learning projects, showcasing cutting-edge solutions in computer vision, deep learning, and data science.

Developed ANN architecture for image classification of potential threats in luggage images with high accuracy in threat identification.

Created pipeline for license plate localization using edge detection and implemented robust plate isolation system.

Built system to recognize Braille characters through dot pattern analysis and distance metrics for character differentiation.

Implemented CNN models with and without pooling and dropout layers, demonstrating regularization techniques.

Designed segmentation system using Connected Component Labeling and achieved accurate results with IoU metrics.

Developed method for segmenting retinal structures using point and multi-level thresholding techniques.
CareCloud (MTBC) - Bagh, AJK
RiseTech - Islamabad, Pakistan
A comprehensive overview of technical skills and expertise acquired through academic coursework and research projects
Industry-recognized certifications validating expertise in AI, Machine Learning, and Software Development
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Comprehensive certification covering Machine Learning, Deep Learning, Computer Vision, and AI deployment strategies.
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Professional certificate covering Generative AI fundamentals, LLMs, and AI engineering practices.
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In-depth training on deep learning frameworks including PyTorch, Keras, and TensorFlow for building neural networks.
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Specialized certification in Retrieval-Augmented Generation (RAG) and building agentic AI systems.
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Hands-on certification for building Generative AI applications and intelligent agents.
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Advanced engineering practices for working with Large Language Models in production environments.
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Operations and deployment strategies for Large Language Models including monitoring, scaling, and maintenance.
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Specialized training in implementing Retrieval-Augmented Generation for enhanced AI applications.
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Enterprise-level data strategy and architecture for implementing Generative AI solutions.
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Application of deep learning techniques for medical and clinical decision-making systems.
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Comprehensive training in modern C++ features including C++11, C++14, and C++17 standards.
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