Farrukh Nauman

My primary areas of expertise in AI are time series and computer vision. My current interests are self-supervised and meta-learning to deal with the challenge of building generalizable AI models in the small data regime. I am currently involved in two projects related to sustainable fashion: AI for resource-efficient fashion (2021-2024) CISUTAC (2022-2024) I am pursuing projects at the interface of science and machine learning. In particular, I find modeling multi-scale or stiff differential equations fascinating. Current time series forecasting and differential equation-based models are too computationally expensive or cannot deal with long-range dependencies observed in many physical systems. My background is in computational fluids and plasmas (Ph.D., 2015).