Summary
Bhaskar Dhariyal is a Senior Data Scientist with nine years’ experience specializing in scalable time series analysis and multivariate anomaly detection, combining academic rigor from a PhD at University College Dublin with production-grade work at Huawei and PayPal. He designs ultra-high-scale anomaly detection and automated root-cause pipelines, fine-tuning time series foundation models and autoencoders for near real-time cloud telemetry monitoring. His research—published and presented at top venues like ECML-PKDD—includes novel channel selection methods for high-dimensional series and practical contributions to open-source forecasting tools (GluonTS, Sktime, Aeon). Comfortable bridging research and engineering, he has a track record of reducing MTTR in cloud systems and prototyping ML-driven battery health models at ION Energy. Colleagues value him for turning cutting-edge time series ideas into robust, scalable systems that run in production.
9 years of coding experience
5 years of employment as a software developer
Bachelor's Degree, Computer Science & Engineering, Bachelor's Degree, Computer Science & Engineering at COER University
Master’s Degree, Artificial Intelligence, Master’s Degree, Artificial Intelligence at University of Hyderabad
Doctor of Philosophy - PhD, Multivariate time-series analysis, Doctor of Philosophy - PhD, Multivariate time-series analysis at University College Dublin
Intermediate, High School/Secondary Diplomas and Certificates, Intermediate, High School/Secondary Diplomas and Certificates at Aryaman Vikram Birla Institute of Learning, Haldwani
English, Hindi