Coordination of Dyadic Object Handover for Human-Robot Interactions is a project funded by NSF. In collaboration with Tunik and RIVER Labs at Northeastern, we are modeling natural human-to-human object handover dynamics in order to develop robotic behavior strategies for more human-like human-to-robot and robot-to-human object handover in human-robot teams of the future.
Mining for Mechanistic Information to Predict Protein Function is a project funded by NSF. In collaboration with researchers from the Chemistry Department, we are using machine learning techniques to develop computational models that can predict protein function from chemical and molecular structure. Models will also be explainable in the sense that active residues will be identified and their roles will be connected to predicted protein function.
Multimodal Signal Analysis and Data Fusion for Post-traumatic Epilepsy Prediction is a project funded by NIH. In collaboration with researchers at USC Medical School, we are using machine learning techniques to discover features from multimodal data such as EEG, fMRI, DTI, and blood chemistry, in order to build models that can predict if a traumatic brain injury (TBI) patient is susceptible to epileptogenesis – emergence of epilepsy following TBI.