Manil Maskey

Manil Maskey is a Senior Research Scientist and Project Manager at NASA and serves as an Adjunct Faculty member in the Atmospheric Science Department at the University of Alabama in Huntsville (UAH). He plays a key leadership role in NASA's Science Mission Directorate, focusing on artificial intelligence, data systems, and Earth science innovation. He has contributed significantly to the development of NASA's AI strategy and leads the Visualization, Exploration, and Data Analysis (VEDA) project.

• B.S. in Computer Science and Mathematics
• M.S. in Computer Science
• Ph.D. in Computer Science

His research interests lie at the intersection of artificial intelligence and Earth science, with a focus on machine learning, data-centric AI, geospatial intelligence, and high-dimensional data visualization. He is particularly interested in applying deep learning to environmental challenges such as tropical cyclone intensity estimation, hail detection, and smoke monitoring using satellite and radar data. His work emphasizes robust data systems, ethical AI, and scalable computing frameworks for scientific discovery.

The recent publications reflect a strong trend toward foundation models, data-centric machine learning, and AI-driven Earth system science. Topics include Clifford neural operators, metadata for ML-ready datasets, and traceability to prevent data swamps, indicating a shift from purely model-centric to holistic data-systems thinking in AI for science.

• Senior Member, IEEE
• Chair, IEEE GRSS Earth Science Informatics Technical Committee
• Co-chair, NITRD Big Data Interagency Working Group
• Steering Committee Member, National AI Research Resource (NAIRR)

Manil Maskey has mentored numerous students and served on thesis committees across computer science and atmospheric science. He has led competitive NASA programs including ACCESS and CSDA, and played a central role in establishing data management frameworks for commercial smallsat data. His work bridges research, policy, and infrastructure development in support of AI for Earth science.

He is actively involved in several scientific teams and initiatives, including the IMPACT project at NASA, where he helped establish a data science team, and leads the GRSS Working Group on High-Performance and Disruptive Computing in Remote Sensing (HDCRS). He also contributes to international collaborations through the NASA-ESA-JAXA Earth Observation Dashboard and promotes open science through workshops and tutorials on cloud computing and machine learning.