Abdul Rehman Khan Durrani

I am a Data Science undergraduate at FAST-NUCES Islamabad, currently in my 7th semester, with strong expertise in artificial intelligence, machine learning, and large-scale data systems. My journey blends academic rigor with hands-on experience, where I have developed AI-powered applications, deep learning solutions, and distributed data pipelines that bridge research and real-world use cases.

Recently, I worked as an AI Intern at Abacus, where I focused on Large Language Models (LLMs), Retrieval-Augmented Generation (RAGs), and fine-tuning techniques such as LoRA/QLoRA. My contributions involved adapting open-source models for enterprise domains, improving retrieval accuracy, and optimizing generative AI workflows. This gave me practical exposure to deploying scalable and domain-specific AI systems.

In addition to my internship, I have built several impactful projects:

• Domain-Specific Medical LLM: Fine-tuned a large language model for the medical domain to answer pathology-related queries with improved accuracy and context understanding.
• AI Study Helper: Designed a personalized learning assistant capable of generating flashcards, summaries, and diagrams, with integrated image generation features. It maintains chat history using PostgreSQL, making it a persistent, interactive learning tool.
• Conversational Chatbot: Built a lightweight chatbot system for general queries, integrating NLP techniques and rule-based logic for interactive assistance.
• Music Recommendation System: Leveraged Apache Kafka, Spark, and MongoDB to process a 100GB dataset in real time and deployed it via Flask.
• Food Detection & Nutrient Analysis: Applied OpenCV to detect food items, estimate portion sizes, and compute nutrition.
• GPU-Accelerated Image Classification: Trained CNNs with TensorFlow & CUDA for efficient image recognition tasks.
• Parallel Data Processing Pipelines: Designed distributed workflows using MPI, Dask, and Spark for high-performance big data processing.
• Interactive Dashboards: Built dashboards with Tableau, Power BI, and D3.js, transforming raw data into actionable insights.

Alongside technical skills, I bring strong leadership and collaboration abilities, demonstrated through leading teams, managing budgets, and coordinating outreach initiatives in student societies. These experiences have sharpened my project management and communication skills, enabling me to deliver effectively in team-oriented environments.

With proficiency in Python, R, SQL, Spark, Hadoop, Apache Kafka, MongoDB, TensorFlow, PyTorch, and modern visualization tools, I am passionate about advancing AI-driven solutions. My long-term goal is to specialize in applied machine learning and generative AI, with a focus on LLMs, RAG systems, and deep learning applications that create meaningful real-world impact.