Rauf Ali

ML Engineer focused on building and deploying end-to-end ML systems across computer vision, NLP, and Generative AI. I work in Python with a strong focus on model development and MLOps: Docker, CI/CD pipelines, AWS deployment, and experiment tracking with MLflow and Weights and Biases. My technical interests include LLM workflows, RAG architectures and scalable ML APIs. Currently collaborating with Edge Hill University (UK) on ML/AI research projects.

ML/Computer Vision Research Collaborator at Edge Hill University, Lancashire UK (2025-10 – Present)

• Designed domain-adaptive crack segmentation system using DeepLabV3+ and VAE-based Sobel-guided latent optimization, achieved a Dice of 0.71 and IoU of 0.64 on unseen UAV images without target-domain labels
• Annotated 20,000+ industrial steel structure images in CVAT, trained YOLOv12-N and YOLOv12-L models for crack detection and conducted a comparative study evaluating mAP50 and inference latency to assess deployment feasibility of each model
• Contributing to ongoing research papers in computer vision

Visiting Lecturer at Lahore College for Women University (2019-02 – 2023-02)

• Taught 150+ undergraduate students across CS/EE courses, achieving 92% average student pass rate and 4.3/5.0 evaluation score
• Mentored and supervised 15+ student research projects in Computer Vision and Signal Processing
• Authored 4 technical lab manuals covering C++, Python, MATLAB and signa processing

Teaching Assistant at Information Technology University (2018-09 – 2019-01)

• Supported 50+ graduate students through advanced ML implementations achieving 88% assignment completion rate
• Developed and delivered 5 lab sessions on scikit-learn, TensorFlow and PyTorch, improving project quality by 25%
• Graded 120+ assignments and mentored students on optimization, reducing debugging time by 35% via structured code reviews

ML and Data Science Practitioner at Freelance (2023-03 – Present)

• Delivered end-to-end machine learning projects in NLP, computer vision and structured data
• Built and deployed pipelines for speech and text processing (TTS/STT) and generative AI workflows
• Developed AI applications including document processing, multimodal generation, and LLM-based assistant using LangChain
• Implemented computer vison solutions using deep learning models for classification, segmentation, generative and analysis tasks

M.Sc. in Electrical Engineering (Major: Computer) – University of Engineering & Technology, Lahore (2015 – 2019)

B.Sc. in Electrical Engineering – Government College University, Lahore (2010 – 2014)