Denis Willett
Adjunct Faculty
Software Engineer, North Carolina Institute for Climate Studies
Education
PhD Entomology and Nematology University of Florida
MS Earth Systems Stanford
Area(s) of Expertise
Focus: leveraging cloud technologies for the development of data processing and machine learning pipelines.
Denis specializes in designing and deploying full-stack, cloud-native data science solutions to intractable technical problems across domains. At the North Carolina Institute for Climate Studies, Denis works on petabyte scale multi-cloud data transfer pipelines, creating pipelines to furnish analytics-ready environmental data, and building production machine learning platforms applying MLOps principles to automate model development and deployment. Previous work has involved expanding the capabilities of scientific instrumentation using machine learning and optimization, building prediction platforms that materials science engineers could use to leverage machine learning for better product design, scaling IOT ingest and analytics pipelines, implementing workforce development plans for data science teams, and strategic positioning planning for bioinformatics companies.
Publications
- Ecological Impact of American Chestnut Hybrid Restoration on Invertebrate Communities Above- and Belowground , FORESTS (2024)
- Soil moisture conditions alter behavior of entomopathogenic nematodes , JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE (2024)
- Entomopathogenic Nematodes for Field Control of Onion Maggot (Delia antiqua) and Compatibility with Seed Treatments , INSECTS (2023)
- NOAA Open Data Dissemination: Petabyte-scale Earth system data in the cloud , Science Advances (2023)
- Expanding Access to Open Environmental Data: Advancements and Next Steps , Bulletin of the American Meteorological Society (2022)
- Phenology and Monitoring of the Lesser Chestnut Weevil (Curculio sayi) , INSECTS (2022)
- The Lesser Chestnut Weevil (Curculio sayi): Damage and Management with Biological Control Using Entomopathogenic Fungi and Entomopathogenic Nematodes , INSECTS (2022)
- The Smart Soil Organism Detector: An instrument and machine learning pipeline for soil species identification , BIOSENSORS & BIOELECTRONICS (2022)