Advanced Methodologies for Time-Series Analysis A comprehensive research program on deep learning for time-series, focusing on architectural innovation, novel data representations, temporal context, interpretability, and robust evaluation. Generative Models for Synthetic Biosignal Data Leveraging GANs and Diffusion Models to synthesize high-fidelity biomedical time-series data for data augmentation. VR Interventions for Veteran Social Anxiety Developing and evaluating VR exposure therapy for student veterans, from rapid prototyping to multimodal assessment of treatment efficacy. Assisted Labeling and Noise Correction for Time-Series Data Developing semi-automatic tools to efficiently identify and correct label noise in time-series data, combining deep learning with human-in-the-loop visualizations. Technology-Enhanced Physical Rehabilitation A research program on computer-aided rehabilitation, from Kinect-based avatars and haptic robotics to multilevel frameworks for human motion analysis. Non-Invasive and Automated Sleep Monitoring Developing multi-modal, non-invasive systems for sleep pattern analysis and creating novel methods for automated, real-time analysis of clinical sleep data. Multi-Modal Fall Detection -- From Vision to Personalized Wearables A research project exploring robust fall detection, first using viewpoint-independent depth cameras, and later with personalized, deep-learning models on smartwatches.
