Research Projects: Parkinson's Disease, Incomplete spinal cord injury, Transfemoral amputees, Cerebral Palsy, Toddlers; Applications: Activity Recognition, Fall Detection and Real-time response, Assessing quality of activities, Posture recognition, Computational neuroscience; ML Techniques: ML predictive and unsupervised models, Deep learning (CNN/RNN, Transformer architectures, autoencoders), Kubernetes/Docker Orchestration & Parallelisation, Hidden Markov Models.
Background
Research Interests: Using machine learning to advance medicine, particularly in wearable device analytics to aid clinicians in the treatment of mobility disorders, as well as broadly using AI to improve health outcomes.
Miscellany
Lab History: Formerly the Pervasive and Ambient Computing (PAC) Lab at Loyola University Chicago