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Instructors and Mentors

The following list of scientists, software engineers and instrument technicans are serving as mentors for the 2026 ARM Big Open Data Summer School:

Dr. Joseph (Joe) O’Brien is an Atmospheric Scientist Software Specialist working for the Geospatial Computing, Innovations, and Sensing department within the Environmental Science Division at Argonne National Laboratory. Joe’s career has been marked by extensive field research across the world studying in-situ observations of cloud and precipitation processes, from atmospheric rivers in Seattle to aerosol-cloud interactions within Southern Atlantic marine stratocumulus. Along with the specific research questions associated with each project, Joe’s research has focused on the observational limitations and uncertainty associated with in-situ cloud microphysical instrumentation on-board instrumented research aircraft. Joe’s current research is focused on development of the Python ARM Radar Toolkit (Py-ART) and associated radar products in the support of the Department of Energy’s Atmospheric Radiation Measurement (ARM) field experiments, development of the Chicago micro-net in support for the Department of Energy’s CROCUS Urban Integrated Field Laboratory, and support for the Atmospheric Radiation Measurement (ARM) user facility MicroPulsed Lidar (MPL) as associate-mentor.
InstructorAffiliationProject LeadLinks
Joe O’BrienArgonne National LaboratoryTBDProfessional Website
Github Link

Dr. Joseph (Joe) O’Brien is an Atmospheric Scientist Software Specialist working for the Geospatial Computing, Innovations, and Sensing department within the Environmental Science Division at Argonne National Laboratory. Joe’s career has been marked by extensive field research across the world studying in-situ observations of cloud and precipitation processes, from atmospheric rivers in Seattle to aerosol-cloud interactions within Southern Atlantic marine stratocumulus. Along with the specific research questions associated with each project, Joe’s research has focused on the observational limitations and uncertainty associated with in-situ cloud microphysical instrumentation on-board instrumented research aircraft. Joe’s current research is focused on development of the Python ARM Radar Toolkit (Py-ART) and associated radar products in the support of the Department of Energy’s Atmospheric Radiation Measurement (ARM) field experiments, development of the Chicago micro-net in support for the Department of Energy’s CROCUS Urban Integrated Field Laboratory, and support for the Atmospheric Radiation Measurement (ARM) user facility MicroPulsed Lidar (MPL) as associate-mentor.

Dr. Scott Collis is an atmospheric scientist and head of the Geospatial Computing, Innovations, and Sensing (GCIS) department in the Environmental Science Division at Argonne National Laboratory and a Senior Fellow at the Northwestern Argonne Institute of Science and Engineering (NAISE). Scott’s research is at the intersection of data informatics, atmospheric science, and radar meteorology. He uses and develops open-source tools to extract geophysical insight from remotely sensed data at scale, which enables a deeper understanding of atmospheric phenomena essential for the development of next-generation climate models. Scott is the inventor of the Python-ARM Radar Toolkit (Py-ART), which is an open-source community-based architecture for interacting with weather radar data. Scott acts as a Translator for a set of the Atmospheric Radiation Measurement User Facility’s Radar systems and leads the Measurement Strategy Team for the Community Research On Climate and Urban Science (CROCUS) a Department of Energy Urban Integrated Field Laboratory.
InstructorAffiliationProject LeadLinks
Scott CollisArgonne National LaboratoryTBDProfessional Website
Github

Dr. Scott Collis is an atmospheric scientist and head of the Geospatial Computing, Innovations, and Sensing (GCIS) department in the Environmental Science Division at Argonne National Laboratory and a Senior Fellow at the Northwestern Argonne Institute of Science and Engineering (NAISE). Scott’s research is at the intersection of data informatics, atmospheric science, and radar meteorology. He uses and develops open-source tools to extract geophysical insight from remotely sensed data at scale, which enables a deeper understanding of atmospheric phenomena essential for the development of next-generation climate models. Scott is the inventor of the Python-ARM Radar Toolkit (Py-ART), which is an open-source community-based architecture for interacting with weather radar data. Scott acts as a Translator for a set of the Atmospheric Radiation Measurement User Facility’s Radar systems and leads the Measurement Strategy Team for the Community Research On Climate and Urban Science (CROCUS) a Department of Energy Urban Integrated Field Laboratory.

Dr. Robert (Bobby) Jackson’s research involves using active remote sensing to create a better picture of Earth’s climate. Bobby specializes in using precipitation radars and Doppler lidars to explore the kinematics and precipitation occurring in our atmosphere. As a part of the ARM Translator group at Argonne, Bobby develops quality-controlled rainfall products from ARM Precipitation radars that are used to evaluate model simulations and explore rainfall and snowfall patterns over various regions of the Earth including Darwin, Australia, the Upper Colorado River Basin, and Bankhead National Forest. Bobby is the lead developer of a Multi-Doppler radar package PyDDA. PyDDA retrieved winds from radar networks are currently being used for Integrated Energy Systems Office’s Observationally-based Resource Assessment and Coupled Models (ORACLE) to assess how well current weather forecasting models predict extreme winds in Nor’easters.
InstructorAffiliationProject LeadLinks
Robert JacksonArgonne National LaboratoryTBDProfessional Website
Github

Dr. Robert (Bobby) Jackson’s research involves using active remote sensing to create a better picture of Earth’s climate. Bobby specializes in using precipitation radars and Doppler lidars to explore the kinematics and precipitation occurring in our atmosphere. As a part of the ARM Translator group at Argonne, Bobby develops quality-controlled rainfall products from ARM Precipitation radars that are used to evaluate model simulations and explore rainfall and snowfall patterns over various regions of the Earth including Darwin, Australia, the Upper Colorado River Basin, and Bankhead National Forest. Bobby is the lead developer of a Multi-Doppler radar package PyDDA. PyDDA retrieved winds from radar networks are currently being used for Integrated Energy Systems Office’s Observationally-based Resource Assessment and Coupled Models (ORACLE) to assess how well current weather forecasting models predict extreme winds in Nor’easters.

Dr. Bhupendra Raut’s research focuses on improving atmospheric observations and data analysis by leveraging statistics, computer vision, artificial intelligence, and edge computing. Bhupendra is involved in the U.S. Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) program and the Chicago Urban Flux Network, contributing to observational campaigns and value-added products, advanced radar algorithms, and adaptive sensing frameworks to quantify the spatiotemporal evolution of clouds and precipitation using multi-platform remote sensing. Bhupendra also contributes to open-source atmospheric tools including Py-ART, TINT, tobac, and ADAPT.
InstructorAffiliationProject LeadLinks
Bhupendra RautArgonne National LaboratoryTBDProfessional Website
Github

Dr. Bhupendra Raut’s research focuses on improving atmospheric observations and data analysis by leveraging statistics, computer vision, artificial intelligence, and edge computing. Bhupendra is involved in the U.S. Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) program and the Chicago Urban Flux Network, contributing to observational campaigns and value-added products, advanced radar algorithms, and adaptive sensing frameworks to quantify the spatiotemporal evolution of clouds and precipitation using multi-platform remote sensing. Bhupendra also contributes to open-source atmospheric tools including Py-ART, TINT, tobac, and ADAPT.

Dr. Gustafson’s research focuses on the development and application of global atmospheric, weather, and large-eddy simulation models with emphasis on cloud parameterization, aerosol-cloud interactions, regional downscaling, and issues of scale and scale dependencies within atmospheric models. In 2010, he was awarded a U.S. Department of Energy (DOE) Early Career award to study scale adaptability of atmospheric model parameterizations. Currently, he works with the DOE Atmospheric Radiation Measurement (ARM) user facility to develop the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) activity for routine LES modeling that complements ARM’s extensive atmospheric measurement capabilities. Gustafson has contributed substantially to the development of the chemistry version of the Weather Research and Forecasting (WRF) model to advance understanding of aerosol feedbacks to clouds and radiation, and has been the principal investigator on a NOAA project studying aerosol-cloud interactions. For his dissertation work, Dr. Gustafson studied Tropical dynamics with a focus on the Madden-Julian Oscillation.
InstructorAffiliationProject LeadLinks
Bill GustafsonPacific Northwest National LaboratoryTBDGithub

Dr. Gustafson’s research focuses on the development and application of global atmospheric, weather, and large-eddy simulation models with emphasis on cloud parameterization, aerosol-cloud interactions, regional downscaling, and issues of scale and scale dependencies within atmospheric models. In 2010, he was awarded a U.S. Department of Energy (DOE) Early Career award to study scale adaptability of atmospheric model parameterizations. Currently, he works with the DOE Atmospheric Radiation Measurement (ARM) user facility to develop the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) activity for routine LES modeling that complements ARM’s extensive atmospheric measurement capabilities. Gustafson has contributed substantially to the development of the chemistry version of the Weather Research and Forecasting (WRF) model to advance understanding of aerosol feedbacks to clouds and radiation, and has been the principal investigator on a NOAA project studying aerosol-cloud interactions. For his dissertation work, Dr. Gustafson studied Tropical dynamics with a focus on the Madden-Julian Oscillation.

Adam Theisen is the Instrument Operations Manager for the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) User Facility, where he leads the strategic planning, coordination, and execution of instrument operations across ARM’s fixed and mobile observatories. He oversees a diverse portfolio of atmospheric sensing systems—including cloud and precipitation radars, lidars, radiometers, and in situ instrumentation—with an emphasis on operational reliability, calibration integrity, and data readiness. Adam serves as the lead for the Atmospheric data Community Toolkit (ACT). Previous research efforts and interest include long-term data analysis, winter weather, and polarimetric radar.
InstructorAffiliationProject LeadLinks
Adam TheisenArgonne National LaboratoryTBDProfessional Website
Github

Adam Theisen is the Instrument Operations Manager for the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) User Facility, where he leads the strategic planning, coordination, and execution of instrument operations across ARM’s fixed and mobile observatories. He oversees a diverse portfolio of atmospheric sensing systems—including cloud and precipitation radars, lidars, radiometers, and in situ instrumentation—with an emphasis on operational reliability, calibration integrity, and data readiness. Adam serves as the lead for the Atmospheric data Community Toolkit (ACT). Previous research efforts and interest include long-term data analysis, winter weather, and polarimetric radar.