Brandon Oubre

Assistant Professor of Computer Science, University of Alabama at Birmingham

I am interested in how computing technologies can be used to understand, monitor, and improve human health. More specifically, my research interests include digital and mobile health, with a focus on quantitative behavioral assessment of neurologic disease. My work frequently employs data science and machine learning methodologies to model time-series sensor data representing human movement. In the context of digital and behavioral phenotyping and disease assessment, these data have the potential to 1) enable identification of subtle, early disease signs, 2) form the basis of more sensitive and ecologically valid measures of disease progression to support clinical trials, and 3) support patient-centric and personalized care. This research is highly interdisciplinary, and I enjoy close collaborations with domain experts in neurology, neuroscience, and biomechanics.

I received my Ph.D. in Computer Science from the University of Massachusetts Amherst, and was awarded the 2021–2022 Outstanding Dissertation Award by the Manning College of Information and Computer Sciences. I was a member of the AHHA lab during my doctoral studies. I completed my postdoctoral training at Harvard Medical School and the Massachusetts General Hospital Department of Neurology. I was a member of the Laboratory for Deep Neurophenotyping and, in addition to my research, helped to develop Neurobooth—a data collection platform that supports time-synchronized, multi-modal capture of behavioral task performance.

I am currently recruinting students! Click here for more information.

news

Aug 15, 2024 I will be joining the Department of Computer Science at the University of Alabama at Birmingham as an Assistant Professor for the Fall 2024 semester.
Feb 21, 2024 Our article, “Detection and Assessment of Point-to-Point Movements during Functional Activities using Deep Learning and Kinematic Analyses of the Stroke-Affected Wrist” has been selected as a featured article in the IEEE Journal of Biomedical and Health Informatics.
Feb 7, 2024 I presented a talk titled, “Digital and Quantitative Behavioral Phenotyping in Neurologic Disease,” at the ML4Health Seminar Series at the Broad Institute.

selected publications

  1. JBHI Featured Article
    Detection and Assessment of Point-to-Point Movements during Functional Activities using Deep Learning and Kinematic Analyses of the Stroke-Affected Wrist
    Brandon Oubre, and Sunghoon Ivan Lee
    IEEE J. Biomed. Health Inform 2024
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  2. TBME Featured Article
    Estimating Ground Reaction Force and Center of Pressure using Low-Cost Wearable Devices
    Brandon Oubre, Spencer Lane, Skylar Holmes, Katherine Boyer, and Sunghoon Ivan Lee
    IEEE Trans. Biomed. Eng. 2022
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  3. Cerebellum
    Decomposition of Reaching Movements Enables Detection and Measurement of Ataxia
    Brandon Oubre, Jean-Francois Daneault, Kallie Whritenour, Nergis C. Khan, Christopher D. Stephen, Jeremy D. Schmahmann, Sunghoon Ivan Lee, and Anoopum S. Gupta
    Cerebellum 2021
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  4. TNSRE Featured Article
    Estimating Upper-Limb Impairment Level in Stroke Survivors using Wearable Inertial Sensors and a Minimally-Burdensome Motor Task
    Brandon Oubre, Jean-Francois Daneault, Hee-Tae Jung, Kallie Whritenour, Jose Garcia Vivas Miranda, Joonwoo Park, Taekyeong Ryu, Yangsoo Kim, and Sunghoon Ivan Lee
    IEEE Trans. Neural Syst. Rehabil. Eng. 2020
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