About

Dr. Rafal A. Angryk is a Distinguished University Professor and 2CI (Second Century Initiative) Professor of Computer Science at Georgia State University, with affiliate appointments in the Department of Physics & Astronomy and the Robinson College of Business. Before joining GSU, he was a faculty member at Montana State University, where he began his long-standing collaboration with the heliophysics community — a partnership that has defined much of his subsequent research agenda. He has been at GSU for over 13 years, directing the Data Mining Lab (DMLab) and building an interdisciplinary research program at the intersection of machine learning and scientific discovery.

His work sits at the intersection of intelligent systems, big data analysis, and scientific discovery — developing AI-driven tools that tackle high-stakes, rare-event prediction problems in domains where failure carries real consequences.

Research

Dr. Angryk’s research sits at the frontier of Artificial Intelligence and Machine Learning, with a primary application domain in data-driven space weather forecasting. His group designs and deploys advanced AI models — spanning deep learning, neural operators, and large-scale spatiotemporal analysis — for predicting high-impact rare events including solar flares, coronal mass ejections (CMEs), and solar energetic particle (SEP) events. These phenomena can severely disrupt satellites, power grids, and communication infrastructure, making reliable AI-based forecasting a critical scientific and societal challenge.

Beyond space weather, his work advances the broader methodology of AI for science — developing open-source machine learning toolkits, AI-ready benchmark datasets, and surrogate modeling frameworks that accelerate scientific simulation across physics domains. This research is supported by sustained federal funding from NASA and NSF, totaling over $18M in grants and contracts across his career.

His research contributions span:

• Rare event prediction using imbalanced and spatiotemporal datasets
• Open-source AI toolkits for scientific big data (MVTS-Data Toolkit, SWAN-SF Dataset)
• Neural operator surrogate modeling for heliospheric MHD simulation
• Multivariate time series analysis and benchmarking infrastructure

Leadership

Dr. Angryk is the Founder and Director of the Big Data & Machine Learning (BDML) Concentration within GSU’s M.S. in Data Science and Analytics program — one of the fastest-growing graduate concentrations at the university, with sustained year-over-year enrollment growth. He directs the Data Mining Lab (DMLab), supervising a research cluster of PhD students, postdocs, and junior faculty collaborators.

His administrative leadership extends to curriculum development, dual-degree program design, faculty mentorship across multiple departments, and service on university-wide research and P&T committees.

Background & Education

Dr. Angryk received his doctoral training in the United States, earning a Ph.D. in Computer Science from Tulane University (New Orleans, LA) in 2004, under the direction of Professor F.E. Petry (IEEE and IFSA Fellow, NRL Researcher). His dissertation — “Attribute-Oriented Fuzzy Induction: A Data Mining Approach” — was recognized by the Polish Academy of Sciences as equivalent to a Polish doctorate degree. He holds two master’s degrees from Polish institutions: an M.S. in Computer Science (with highest honors) from the Technical University of Szczecin, and an M.A. in Business Management from the University of Szczecin.

During his career he has held visiting faculty appointments at the Harvard-Smithsonian Center for Astrophysics (Cambridge, MA), the University of Minnesota — Twin Cities, and the University of Illinois Urbana-Champaign, deepening his ties to the heliophysics and spatiotemporal data mining communities.

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