A Deep Learning Approach for Intelligent Thinning of Satellite Data

CG Auditorium
Sarvesh Garimella

As new observation platforms are launched into orbit, the amount of satellite data generated globally is increasing rapidly. Transmission of large amounts of data to ground stations is limited by available bandwidth. Also, the amount of data that can be ingested into numerical models is limited, especially if the models are run within operational time constraints. In this study, a deep learning approach is used to compress satellite data intelligently into a specified dimensionality. By learning the latent representations of the complex patterns in high dimensional satellite data, this approach provides a method for creating statistically-optimized lossy representations of the of the observational data as well as a method to decompress the resulting latent representations. In particular, an autoencoder architecture trained with a mean squared loss function is compared to one trained with an adversarial loss function. Since the dimensionality of the latent representation can be specified, this approach also lends itself as an intermediate step to applying transfer learning with pre-trained models for subsequent classification tasks.

Speaker Description: 

Dr. Sarvesh Garimella is the Chief Scientist and Chief Operating Officer at ACME AtronOmatic, LLC. His work is at the interface of artificial intelligence and atmospheric science, and he leads the research and operational efforts at ACME to create innovative new features for the users of the MyRadar app. With a background in planetary science and environmental engineering as an undergraduate at Caltech (BS ’11), his graduate career focused on clarifying the role of anthropogenic emissions of particulate matter on clouds and climate. He completed his doctorate in Climate Physics and Chemistry at MIT (PhD ’16), where his research focused on representing the microphysical underpinnings of ice cloud formation in global climate models with a machine learning approach. As part of his affiliation with the MIT Center for Global Change Science, his work also examined the the policy implications of this research from both a climate and human health perspective. In addition to his scientific interests, Sarvesh is an avid jazz trumpet player in several groups in the Portland area. He is currently the President of the NoPo Big Band, a community organization dedicated to providing high quality jazz music to the Portland community. His other hobbies include exploring the outdoors and listening to live music.

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