Assistant Professor, Electrical Engineering & Computer Science, College of Engineering & Computer Science
Faculty Affiliate, Aging Studies Institute
Curriculum VitaeBiography:
I am leading the Laboratory for Ubiquitous and Intelligent Sensing (UIS Lab) at Syracuse University. My research takes a multi-disciplinary approach to develop novel and practical human event sensing technologies that capture observable low-level physical signals from human bodies and surrounding environments and employ new machine learning, signal processing, and natural language processing techniques to rectify the existing sensing technologies. My research exquisition goes beyond the conventional learning or sensing approaches and addresses the research challenges, such as the uncertainties in physical world sensing, interpretability of ML inference, human factors such as the user-context and mobility, limitation of current technologies (i.e., IoT, CPS), and resource constraints of the sensing data and computation platform. A core focus of my research program is to integrate passive sensing and interpretable AI to advance human health assessment, identify latent markers, automate health monitoring and interventions. My recent and ongoing works include passive assessment of mental health and affective states; automated monitoring of asthma and dementia patients; identify markers of chronic kidney disease (CKD); understanding cognitive and sensorimotor factors of children-stuttering; interpret health-related atypical brain-activity patterns from EEG and MRI (fMRI) signals, etc. I am also an Assistant Professor (voluntary track) at SUNY Upstate Medical University, Syracuse, NY, USA.
