Deep Learning
Satellite Land Classification
CNN and Vision Transformer workflows for classifying satellite terrain in precision-agriculture scenarios.
PythonKerasPyTorchCNN
Computer Science • AI/ML • AI Engineering
Building intelligent systems with AI, machine learning, and software engineering.
Final-year Computer Science undergraduate at FAST-NUCES Karachi, working across deep learning, data engineering, and the practical systems that move AI from experiments into applications.
Open to AI/ML engineering opportunities· Karachi, Pakistan
ENGINEERING SCOPE / 2026
01Data systems
02Model development
03AI applications
04Production software
Selected work
Projects built around real technical problems.
Deep learning and applied AI work, documented with the engineering decisions behind each system.
Generative AI
Aircraft Damage Classification & Captioning
A multimodal pipeline using VGG16 to classify aircraft damage and BLIP to generate image descriptions.
PythonTensorFlowKerasVGG16
Deep Learning
Waste Classification with VGG16
A transfer-learning classifier that separates organic and recyclable waste using feature extraction and fine-tuning.
PythonTensorFlowKerasVGG16
Machine Learning
Content-Based Movie Recommendation
An NLP recommendation engine that ranks similar movies from metadata using TF-IDF and cosine similarity.
PythonPandasScikit-LearnTF-IDF
Deep Learning
Fashion-MNIST CNN in PyTorch
Two PyTorch CNN variants for Fashion-MNIST, including a batch-normalized architecture and tracked validation performance.
PythonPyTorchtorchvisionCNN
Generative AI
Generative AI & LLM Learning Lab
An evolving notebook repository for practical Generative AI, large-language-model, and RAG learning exercises.
PythonJupyter NotebookGenerative AILLMs
AI / ENGINEERING FOCUS
From models to production systems.
Developing depth across the full AI engineering lifecycle: structuring data, training models, composing intelligent services, and building the software around them.
01Data
02Models
03LLMs
04Retrieval
05Agents
06APIs
07Applications
08Deployment
Current direction
Learning with a systems mindset.
Currently completing the IBM AI Engineering Professional Certificate and extending a foundation in CNNs, RNNs, and Vision Transformers toward Generative AI, RAG, agentic workflows, and production AI engineering.
View technical profile01
Generative AI and LLM applications
02
Retrieval-augmented generation
03
AI agents and agentic workflows
04
Production AI engineering
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