Austin J. Brockmeier

Austin J. Brockmeier is an Assistant Professor in the Department of Electrical & Computer Engineering at the University of Delaware. He holds a PhD in Electrical & Computer Engineering from the University of Florida. His research focuses on data science, machine learning, signal processing, and statistical modeling applied to biomedical engineering, neuroscience, and natural language processing. His work bridges theoretical frameworks with practical applications in healthcare and neurotechnology.

Key research areas include predictive modeling for post-concussion injury risks in athletes, anomaly detection via autoencoders, and EEG-based studies of early-stage psychosis. He also explores computational methods for brain aging prediction, visual cortex feature extraction, and fragrance release dynamics in industrial capsules. His interdisciplinary approach integrates mathematical rigor with real-world biomedical challenges.

Notable recent work examines longitudinal clinical studies linking functional brain networks to neuropsychiatric outcomes. His methodology combines advanced signal processing (e.g., optimal transport, contrastive learning) with medical imaging modalities like MRI and EEG. Brockmeier’s publications span machine learning optimization, neural decoding, and reinforcement learning frameworks for biomedical applications.

He maintains an active research group focused on translational data science, collaborating across engineering, medical, and computational disciplines. His lab develops tools for interpretable AI in healthcare diagnostics and neuroprosthetics, emphasizing ethical and practical implementation of machine learning systems.