PhD Researcher at the Centre for Vision, Speech, and Signal Processing, University of Surrey. My work spans across Machine Learning, AI, with a focus on Computer Vision, Medical AI, and Generative AI. Passionate about applying technological innovations to real-world problems, I am actively seeking collaborations on projects that push the boundaries of what's possible in AI.

• PhD Candidate, CVSSP, University of Surrey, focusing on Computer Vision and Signal Processing.
• BSc Computer Science (Hons), First Class Honours, University of Surrey. Specialized in AI, Deep Learning, NLP.
• Transferred from Lahore University of Management Sciences (LUMS), Pakistan, with a cGPA of 3.61.

• Research Assistant, CVSSP, University of Surrey. Worked on semantic face editing, synthetic image generation, and multimodal search.
• Technology and Development Intern, National Database and Registration Authority, Pakistan. Contributed to the development of the national identification system for Somalia.

• Languages: Proficient in Java, Python, C++, with experience in Ruby on Rails and JavaScript for front-end development including React for building interactive UIs.
• Frameworks & Libraries: Expertise in PyTorch, TensorFlow, Keras for deep learning, FastAPI for efficient backend services, and React for scalable front-end applications.
• Technologies: In-depth knowledge of Vision Transformers, Convolutional Neural Networks (CNN), Generative Adversarial Networks (GAN), and Diffusion Models for state-of-the-art generative AI applications.
• Development Tools & Practices: Proficient in CI/CD methodologies using GitHub Actions, experienced in using Docker for containerization, and familiar with Kubernetes for orchestration.
• Data Science & Analysis: Skilled in using NumPy, Pandas for data manipulation, and Matplotlib, Seaborn for data visualization to extract insights from data.
• Machine Learning & AI Techniques: Deep understanding of machine learning algorithms, natural language processing (NLP), and reinforcement learning for complex AI systems.
• Software Engineering Best Practices: Knowledge in Agile development methodologies, test-driven development (TDD), and object-oriented programming (OOP) principles for high-quality software design and architecture.
• Cloud Computing: Experience with cloud services such as AWS, Azure for deploying and managing applications in the cloud, leveraging cloud-based machine learning services.

• CARDIO-VT: End-to-End Remote Cardiac Vital Signs Estimation using Vision Transformers: Innovated with transformer-based networks for remote heart rate estimation, overcoming challenges related to illumination and motion artifacts. Developed a unique architecture and a GUI for real-time analysis, deployed on Hugging Face.

• Automated Skin Cancer Detection with Deep Learning (YOLO): Created a system to detect and classify skin lesions using YOLO v5 and v8, trained on the HAM10000 dataset, enhancing early diagnosis and care in skin cancer.

• Two Stage Training on Population-based Optimisation for Image Classification: Investigated a novel two-stage training method with population-based optimization for image classification, outperforming traditional gradient-based optimization techniques.

• Deep Neural Network Based Human Kidney Cortex Cell Image Classification: Tackled medical image classification challenges, such as overfitting and data augmentation, in classifying kidney cortex cells, utilizing a dataset from the Broad Bioimage Benchmark Collection.

• NLP Multi-Class Emotion Classifier: Led a project to develop an NLP model for classifying emotions from text, using a variety of preprocessing techniques and machine learning algorithms to improve classification accuracy. The project involved extensive data analysis, visualization, and the application of several experimental variations to optimize model performance.

• Invitation Card Transfer Protocol (ICTP): Developed a protocol to promote the use of digital over paper cards, utilizing UDP for secure, efficient file transfer, aiming at reducing the environmental impact of paper cards.

• E-commerce Website for Clothing Store (Ruby on Rails): Designed and developed a fully functional e-commerce website for a clothing store using Ruby on Rails, incorporating features such as product catalog, shopping cart, and user authentication.

• Firefly (Web Application): Served as the backend team lead, managing the development of core functionalities like chat and forum using Ruby on Rails and ReactJS. Ensured project coherence and performance through effective git version control, assisting in frontend tasks to accelerate deployment, and successfully launched the app on Heroku.

These projects showcase my expertise in health AI, machine learning, computer vision, and more, reflecting my commitment to leveraging AI for real-world applications and advancing digital solutions.

Projects related to Machine Learning, Artificial Intelligence, especially those focusing on Computer Vision, Medical AI, and Generative AI. Interested in both academic and practical applications that can make a difference.

• Email: taimoorriz@hotmail.com
• LinkedIn: taimoorrizwan
• GitHub: @Taimoor-R