Raghav Sikka

Master's graduate in Artificial Intelligence from Queen Mary University of London, with a strong foundation in machine learning, NLP, and software development. Experienced in building AI-driven solutions, including an NLP-based Punjabi Polysemy Dataset project. Proficient in Python, TensorFlow, OpenCV, SQL, and full-stack development. Over one year of experience at Amazon Fresh, demonstrating teamwork, adaptability, and problem-solving skills. Passionate about developing scalable AI solutions and eager to contribute as a Graduate Software Development Engineer at Amazon.

• Mathematics for Machine Learning (Imperial College London)
• Machine Learning with Python (IBM Developer Skills Network)
• Data Science Foundations & Tools (IBM)
• AI for Everyone (Deeplearning.AI)
• Microsoft Certified: Introduction to Programming Using Python

• Gold Medalist – International Mathematics Olympiad (2014 – 2015)

Improving Word-in-Context: A Punjabi Polysemy Dataset and the Limits of Cross-Lingual Transfer, NLP, Python, PyTorch, Transformer Models, Built a Punjabi polysemy dataset to improve word-in-context understanding., Implemented cross-lingual transfer learning techniques to optimize NLP model performance., Achieved high accuracy in distinguishing polysemous word meanings across languages. Face Mask Detection System, Python, OpenCV, TensorFlow, Keras, CNNs, Developed a real-time face mask detection AI model using deep learning., Achieved 95% accuracy with optimized CNN architecture. Attendance Management System, Python, Django, Tkinter, MySQL, Designed a biometric-based attendance tracking system for educational institutions., Integrated real-time database updates and user authentication features.