Ravindra Patil

Field of work

I am a postdoctoral researcher at the Western Norway University of Applied Sciences (HVL) and a member of the HVL Robotics Research Group. My work covers core areas of AI and related data-driven fields, including machine learning, deep learning, computer vision, hyperspectral and multispectral imaging, data science, time-series forecasting, and scientific computing. It also incorporates sensor fusion, database systems and analytics, embedded and edge AI, robotic perception, and the design and curation of representative datasets. I develop and apply data-driven methods for real-world monitoring, prediction, classification, automation, and decision support.

My current work combines hyperspectral and multispectral imaging with machine learning and deep learning for precision agriculture, focusing on raspberry yield prediction, fruit-quality assessment, and the early detection of diseases and pests within the FutuRaPS project.

My experience spans both academia and industry and includes, but is not limited to, the development of practical AI solutions and data-driven analytical systems for precision agriculture, embedded vision and robotics, environmental and sustainability monitoring, AI-based plastic-recycling systems, NLP-based text classification, power-factor monitoring and control, database analytics and time-series forecasting, predictive modelling using Norwegian open-access datasets, underground sewer monitoring, structural-health monitoring of the Herøysund Bridge, and a conceptual multimodal AI framework for early hydrogen-leak detection.

I completed my PhD at UiT The Arctic University of Norway, focusing on artificial intelligence, computer vision, and data analysis, with funding through the SPRING Horizon 2020 project and support from the UTFORSK PEERS project. I have teaching and supervision experience at bachelor's and master's levels and currently assist with student projects involving machine learning and spectral imaging.