Projects
Our projects focus on integrative multimodal perception and intelligent systems, combining machine learning with heterogeneous data sources such as vision, audio, tactile sensing, and physiological signals. Applications span healthcare, assistive technologies, and real-world intelligent systems.
Featured Projects
Early Autism Detection from Voice Biomarkers
Deep learning for speech-based screening signals
Research on early autism detection using voice biomarkers and deep learning, with emphasis on robust feature learning and careful evaluation for health applications.
Multimodal Perception and Sensor Fusion
Learning representations across heterogeneous data
Methods for integrating multiple data modalities (e.g., vision, audio, tactile signals) to improve robustness and generalization in real-world intelligent systems.
Other Projects
Additional Projects
More details on other projects coming soon