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Alumni

Ryan Avery

Ryan received his MS from the Department of Geography at UC Santa Barbara in 2020, studying vegetation remote sensing and machine learning to detect smallholder agriculture in sub-Saharan Africa.

Biography

Ryan joined the WAVES Lab in Fall 2017. Prior to UCSB, Ryan graduated from UC Berkeley in 2016 and then served as a Geoinformatics Fellow with the NASA DEVELOP program. He advised applied remote sensing projects and helped develop a time series of forest disturbance maps for Glacier National Park and a python program to model regional light pollution for the Natural Sounds and Night Skies division of the National Park Service.

His research interests include modeling of hydrologic processes, remote sensing of land cover/land use change, and the applications of machine learning in the geographic sciences. Ryan is currently applying these methodologies as a National Geographic Explorer to model field scale water use across the various drylands in order to examine the sustainability of intensive agriculture in groundwater dependent systems, as well as the impact of this water use on water availability in ecosystems. He is also a GSR with the Mapping Africa project, where he works on applying computer vision, machine learning, and cloud computing techniques to map smallholder agriculture across Ghana. When not at a computer, you can usually find him rock climbing, trail running, or getting a sunburn.

He also serves as an instructor for Software Carpentry.

Recent Publications

High Resolution, Annual Maps of Field Boundaries for Smallholder-Dominated Croplands at National Scales

L. Estes, Su Ye, Lei Song, B. Luo, J. R. Eastman, Zhen-zhi Meng, Qi Zhang, D. McRitchie, Stephanie Debats, J. Muhando, Amukoa, Brian W. Kaloo, Jackson Makuru, Ben K. Mbatia, Isaac M. Muasa, Július, Mucha, Adelide M. Mugami, J. Mugami, Francis W. Muinde, Mwawaza, Jeff Ochieng, Charles J. Oduol, Purent Oduor, Thuo Wanjiku, Wanyoike, Ryan Avery, Kelly Caylor

Frontiers in Artificial Intelligence · 2022

Accounting for training data error in machine learning applied to Earth observations

A. Elmes, S. H. Alemohammad, Ryan Avery, Kelly Caylor, J. R. Eastman, Lewis Fishgold, M. Friedl, Meha Jain, D. Kohli, J. L. Bayas, D. Lunga, J. McCarty, R. Pontius, A. Reinmann, J. Rogan, Lei Song, H. Stoynova, Su Ye, Zhuang-Fang Yi, L. Estes

Remote Sensing · 2020

Accounting for training data error in machine 2 learning applied to Earth observations

A. Elmes, H. Alemohammad, Ryan Avery, Kelly K. Caylor, J. R. Eastman, Lewis Fishgold, M. Friedl, Meha Jain, D. Kohli, J. L. Bayas, D. Lunga, J. McCarty, R. Pontius, A. Reinmann, J. Rogan, Lei Song, H. Stoynova, Su Ye, Zhuang-Fang Yi, L. Estes

2020

A Convolutional Neural Network Approach to Segmenting Smallholder Agriculture

Ryan Avery, Kelly K. Caylor, L. Estes, R. Eastman, Su Ye, L. Song, K. Zhang, S. Xiong, D. McRitchie, T. Woodard

2018

Recent News

Laptop workspace - coding and programming
Sharing data science skills with the DataUp program and Software Carpentry
GeneralNov 29, 2018

Ryan visited Old Domion University to teach research computing skills in a two day workshop.

a bunch of small flags on a stick
Ryan Avery developing ML system for Omidyar Network at Clark Labs
ResearchJun 29, 2018

Ryan is working as a Researcher at Clark Labs to develop the scalable machine learning component of an active learning system to detect smallholder agriculture

Education

BS in Environmental Sciences

UC Berkeley . MS

2026

MA in Department of Geography

UC Santa Barbara

2020

Quick Info

Status
Alumni

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