Sreerag V N

• Exploratory analysis of driver interactions with automotive infotainment screens under different contexts, utilizing vehicle CAN bus data. • Master thesis topic: Context‑Aware In‑Car Recommender System: Predicting Interactions with Driving Context - for infotainment screens to enhance user experience. • Served as a key liaison for Porsche Engineering and Digital teams, for Porsche OneTouch project at POC phase overseeing model architecture, training, deployment, and testing.

• Built a machine learning pipeline and deployed dockerized machine learning models for leakage detection on vacuum bag for aircraft CFRP parts and web application on Nimbus, a modern cloud-compatible platform by DLR to transform awesome science into usable services. • Description of the experimental setup for data acquisition on the wing of an aircraft. • Design neural network architecture (Multi‑task learning or like YOLO) to predict the multiple leakage coordinate and quantify prediction uncertainty.

• Implemented data preprocessing pipelines ‑ data sanitation, validation, imputation, feature computation, for airfoil performance data. • Conducted extensive experimentation with various machine learning algorithms to predict the performance characteristics of new airfoils

• Led the product development team and other stakeholders in making critical decisions on product features and algorithms, resulting in the successful launch of Eltrix Lite, a widely adopted asset management software for thermal power plants. • Developed and maintained Grafana and Power BI dashboards to visualise and monitor power plant performance and KPIs for operational insights and to plan maintenance shutdown.