Bio:

Vineeth is a Principal Machine Learning Engineer with over 7 years of experience developing enterprise-scale AI systems across industrial, governance, and compliance domains. At Schneider Electric, he leads the Anomaly Detection team serving Finance, Audit, Compliance, and Legal functions, delivering systems that have enabled high risk avoidance and process effiiencies 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.