I am a software engineer working as the IT manager for the Institute for Astronomy at University of Hawaii, Manoa. I manage a team of 6 IT specialists who support faculty, grad students and staff at 3 island campuses and 3 mountaintop observatories. I use my expertise in advanced computing technologies to support research projects that apply AI/ML to astronomy, astrophysics and information security. I collaborate with researchers across multiple academic institutions and industry on using high performance computing technology for astronomy and astrophysics. Current work includes COMA, a comet data repository; SPIN4D, using deep learning for Stokes inversion using MURaM cubes and SIR inversions; KoaStore, science data integration with Open Science Grid, National Research Platform and Open Science Data Federation, and cybersecurity in collaboration with MITRE Corp.

AI and Machine Learning

Solar Stokes Inversion

In 2019 I used Hinode SOP SP data to develop a neural network for fast Stokes inversion of solar spectropolarimetry which was accepted for publication as a poster at the 33rd Annual Conference on Neural Information Processing Systems  in 2019. I continue to work on improving neural network Stokes inversion using Hinode and eventually SDO and DKIST DL-NIRSP data.

Network Intrusion Detection

I am working on applications of AI and machine learning to the problem of network intrusion detection using auto encoders for anomaly detection.

High Performance Computing (HPC)

Data Transfer

I lead the “AstroFlows” group within the UH IRNC PIREN project. We work on performance tuning of data transfers of big data and real time data in astronomy over long distance, high latency network paths, e.g. Hawaii to Europe, Asia and the Middle East.

Cybersecurity

Working with the UH Applied Research Laboratory, I developed a method of efficient and complete information security assessment using the Risk Management Framework and the NIST 800-53 standard.

Semiconductor Test and Evaluation

While at Sof-Tek Integrators, Inc. I helped develop 3 patents related to parametric testing of semiconductor  light emitting diodes and lasers.

• U.S. Patent 9,551,669 Morrow D., J. Dummer, and S. Dodds. Method and system for characterizing light emitting devices. Jan. 2017
• U.S. Patent 9,128,144 Morrow D., et al. System and method of quantifying color and intensity of light sources. Sep. 2015
• U.S. Patent 8,593,148 Morrow D., J. Dummer. System and method of testing high brightness LED (HBLED). Nov. 2013

Publications

Affiliations

• Institute for Astronomy, University of Hawaii, Manoa
• NVIDIA Deep Learning Institute

• AI/ML neural network applications to astronomy and astrophysics
• AI/ML neural network applications to cybersecurity
• AI/ML for financial market prediction
• FISMA compliance, RMF, NIST 800-53/171
• High performance data storage and transfer

• Association for Computing Machinery
• Astronomical Society of the Pacific

Grants

• Co-I - NSF 2008344 Critical Early DKIST Science: Spectropolarimetric Inversion in Four Dimensions with Deep Learning, 07/01/2020-06/30/2023, $668,938 (PI Dr. Xudong Sun)
• Co-I - NASA 80NSSC19K0413 Cometary Observation Metadata Archive (COMA), an Interactive Science Portal for Primitive Solar System Objects, 07/01/19-6/30/22, $1,069,228 (PI Dr. Karen Meech)
• Collaborator - NSF OAC 2029312 IRNC Core Improvement: SC-Transport: Pacfic Islands Research and Education Network, 08/15/2020 - 07/31/2025 ,$4,494,140 (PI Dr. David Lassner)
• PI - USNO Task 19F8810 Information Management and Security Upgrades for United Kingdom Infrared Telescope (UKIRT), 05/13/2019-05/12/2020, $777,710
• PI - NSF OAC 1541471 CC*DNI INSTRUMENT: High Performance Reliable Network Access to MLO, 09/01/15-08/31/18, $398,207