Bio:

Vineeth is a Machine Learning Engineer with over 7 years of experience developing enterprise-scale AI systems across industrial, governance, and compliance domains. Previously, at Schneider Electric, he led the Anomaly Detection team serving Finance, Audit, Compliance, and Legal functions, delivering systems that enabled high risk avoidance and process effiicencies through scalable ML architectures. His expertise spans deep learning, MLOps pipelines, and hybrid anomaly detection frameworks combining unsupervised learning, supervised models, LLMs, and rules-based approaches. He holds a Master’s in Data Science from Northeastern University, where he received the Outstanding Research Award for his work on Husky Sort.