Abhishek Ningappa Walikar

1.Fine-tuned a Hugging Face transformer model on a self-collected YouTube-comments dataset, shipping a spam-detection classifier that achieved 96%+ accuracy for a subscription-based platform. 2. Automated end-to-end Python data pipelines across 12+ datasets, enabling reproducible train/validation splits for 25+ experiments. 3. Built ML pipelines (scikit-learn, TensorFlow) across 6 benchmark datasets and delivered performance dashboards to a 5+ person cross-functional team.

Developed Python-based applications, strengthening fundamentals in backend logic and database design.

Coursework spanning computer vision and security, extended through hands-on research applying deep learning and AI security methods (see Projects section below). Relevant coursework: Data-Driven Engineering (Grade: 1.3), Data-Driven Innovation (Grade: 2.0) , Web Security (Grade: 2.7), Human Factor