Amil Bhagat

Amil Bhagat is a software engineer with experience at LinkedIn, where Amil developed Keimdall, a machine learning-driven tool for automated anomaly detection in Kubernetes logs, leading to a 75% reduction in Mean Time to Identify (MTTI). Amil also tackled challenges related to log diversity, volume, and noise filtering, improving system reliability. Prior to this role, Amil served as an undergraduate researcher at Indraprastha Institute of Information Technology, Delhi, focusing on Conditional Consistency Models for multi-domain image translation tasks. Amil holds a Bachelor of Technology in Computer Science and Artificial Intelligence from Indraprastha Institute of Information Technology, Delhi, with a GPA of 8.57, and completed secondary and higher secondary education at The Samhita Academy and Delhi Public School - R. K. Puram, achieving high percentages in CBSE examinations.