

"You can't use up creativity. The more you use, the more you have."
Proven AI/ML Engineer and Full-Stack Developer with expertise in backend development using Django, Flask, and FastAPI. Published researcher with two peer-reviewed papers in MDPI on AI-generated content detection and visual cyberbullying. Specialized in building RAG applications, generative AI solutions, intelligent automation agents, and production-level systems. Successfully deployed multiple production-ready platforms including AKTI Management Software and POS systems. Experienced AI/ML instructor having conducted 9+ training batches and delivered 17+ professional courses, training industry professionals and students at leading institutions including NUST, FAST, UMT, and PUCIT. I am dedicated to bridging the gap between theoretical AI concepts and practical, scalable software solutions, constantly exploring new technologies to drive innovation and efficiency.
Training Batches
Projects Done
Courses
Interns Trained
A timeline of building, leading, teaching, and shipping AI products.
13+
Roles
5+
Companies
350+
Mentees
Nexxaura (Part-time)
Wood Tech Mobel (Part-time)
The University of Chenab, Gujrat (Contract)
BuiltPulse
BuiltPulse
Tecrix
Big Binary Tech (Remote)
Arfa Karim Technology Incubator, DHA Campus
Autometa Limited
Arfa Karim Tech Incubator (DHA), Lahore, Pakistan
Arfa Karim Tech Incubators - DHA Franchise
Arfa Karim Tech Incubator (ASTP)
Arfa Karim Technology Incubator, DHA Campus
Context-aware representation learning model to detect AI-generated cryptocurrency tweets across multiple LLMs. Achieved 99% accuracy. Published in MDPI 2025.
End-to-end deep learning pipeline for visual cyberbullying detection using TensorFlow and Computer Vision. Achieved 98% accuracy. Published in MDPI 2024.
Multi-class classification system for 11 gastrointestinal conditions using VGG-16, VGG-19, DenseNet121. Best accuracy: 97% with VGG-16.
Transfer learning with layer freezing for medical image classification on LC25000 dataset. Achieved 99% accuracy.
Real-time hospital dataset with 8 bone fracture classes. Implemented VGG-16, VGG-19, ResNet50v2, DenseNet models.
Neural network model to recognize handwritten digits from MNIST dataset. Achieved 90.2% accuracy.
Scraped election data, performed EDA, trained ML model to predict election outcomes.
Scraped IMDb reviews using Selenium, preprocessed with NLTK, displayed sentiment analysis on Gradio using VADER.
Intelligent RAG system with web scraping via Selenium, vector embeddings using LangChain, authentication, and session management.
AI-powered educational platform using Groq, LangChain, Llama Vision, RAG, and OCR. Features Lecture AI, Book Chat, and quiz generation.
AI agent that generates comic book-style images based on story context with consistent character design and scene progression.
AI agent that extracts tasks from project priorities and automatically creates JIRA issues through function calling.
Integrated Groq API with multiple models, Tavily Search for retrieval, and Llama-Vision for image insights.
AI tool for data preprocessing and labeling using Llama models. Context-aware word correction feature.
AI-powered medical image analysis tool with IBM Watson, Aria API, TTS/STT for voice-based interaction.
Robust RAG system using Llama3.1:8B local model with runtime document embedding and Streamlit interface.
Bioinformatics web app for Lund University to predict amino acid variation pathogenicity using Django, Celery, RabbitMQ.
Comprehensive management system with portal and POS on Vercel with Neon PostgreSQL. Role-based access control, analytics, invoicing.
Transcription app supporting audio, video, and YouTube links with Whisper AI and Groq Llama 3.2 Q&A system.
Database validation with 200 bootstrapped models for prediction. Generates CSV reports sent via email.
Fully responsive portfolio with email configuration, password reset, and inline admin panel with runtime color changing.
Django app to scrape and compare product prices from three online stores using Selenium.
RAG bot for accounting queries using Llama3.2 and Groq API with GPT-like interface and admin upload page.
Dashboard for monitoring user queries and reviewing bot responses with chat history saved to database.
CRUD API using Flask with MVC architecture for clean and organized codebase.
Automation script to download pictures from Unsplash with dynamic content handling.
University of Management and Technology (UMT), Lahore, Pakistan
Superior College, Lahore, Pakistan
Production-tested across 6 disciplines — from transformer fine-tuning to scalable Django backends.
17 Skills
17 Skills
11 Skills
9 Skills
27 Skills
4 Skills
Published in MDPI journals — exploring AI-generated content detection and visual cyberbullying with novel deep-learning architectures.
Journal of Risk and Financial Management (JRFM), MDPI
This study addresses AI-generated financial text detection by constructing a dataset of financial tweets regenerated using six LLMs. A context-aware DeBERTa model was fine-tuned and compared against other transformers and traditional ML models. The proposed model achieved 94% accuracy, precision, recall, and F1-score, significantly outperforming competitors and demonstrating the effectiveness of context-aware representation learning for text authentication.
Information, MDPI
This paper presents a novel dataset (CVID) for visual cyberbullying detection with four classes: abuse, curse, discourage, and threat. Using deep learning models including VGG16, VGG19, and Vision Transformer, the proposed DenseNet201-based model achieved 99% test accuracy. The 5-fold stratified K-fold validation confirmed the model's generalizability in detecting cyberbullying in visual content.
Coursera
DeepLearning.AI
DeepLearning.AI
Open to discussing AI/ML projects, generative AI products, full-stack engineering roles, training engagements, or just trading ideas about emerging technology.
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