ShopAgent
FlagshipCurrently WorkingAn agent-based shopping workflow designed to simplify product discovery and booking.
Hi, I'm
AI / ML ENGINEER

Building intelligent systems that solve real-world problems.
I'm Bahawal Khan, a BS Computer Science student at the University of Lahore (UOL), currently in my 7th semester with a CGPA of 3.06. My focus is on Artificial Intelligence and Machine Learning — spanning classical machine learning, deep learning, NLP, transformers, Generative AI and Agentic AI.
3.06
CGPA
7th
Semester
BS CS
Program
Alongside AI/ML, I also have hands-on web development experience, building interfaces and APIs with HTML, CSS, JavaScript, React.js, Next.js and FastAPI. I enjoy turning ideas into practical, end-to-end systems that can retrieve information, use tools, maintain context and interact with users.
Grouped by discipline — from classical ML through deep learning, generative and agentic AI, to the retrieval and tooling that ties it together.
Five systems, one flagship — real architectures, real metrics, and how each one actually fits together.
An agent-based shopping workflow designed to simplify product discovery and booking.
A multimodal agentic AI assistant capable of interacting with users, retrieving information, using external tools and working across text, vision, PDF, voice and image-generation workflows.
An NLP/RAG support system that classifies incoming queries and retrieves grounded answers — transformer-based classification paired with embedding retrieval over a Postgres/pgvector-oriented store.
A deep learning model fine-tuned to detect plant diseases from images across the PlantVillage dataset — a real agricultural use case, trained end-to-end on CPU.
An end-to-end machine learning pipeline predicting customer churn, comparing multiple models before selecting a winner on real test data.
Stage 01
EDA, feature engineering, regression, ensemble models
Stage 02
ANN, CNN, RNN, LSTM, GRU, transfer learning
Stage 03
TF-IDF, text classification, embeddings, semantic search
Stage 04
Self-attention, DistilBERT, transformer-based NLP
Stage 05
LLMs, LangChain, prompt engineering, model APIs
Stage 06
Retrieval pipelines, vector databases, context management
Stage 07Current
LangGraph agents, tool calling, memory, HITL
An explanatory view of how the stack layers together — not a claim that every project uses every piece.
AI / ML
Generative AI
Agentic AI
PostgreSQL / Vector Retrieval
Have an AI project, idea, or opportunity?