Ph.D. Computer and Information Science
Arizona State University, Tempe, Arizona
Ph.D. researcher · Human-centered AI
Trustworthy AI for multimodal human sensing.
I am a Ph.D. candidate in Computer and Information Science at Arizona State University, building fair, interpretable, and privacy-preserving machine learning systems for human-centered sensing.
Research agenda
I study how machine learning systems can reason from human-centered sensor data while remaining reliable, equitable, and privacy-aware.
My work sits at the intersection of ubiquitous computing, machine learning, and responsible AI. I use multimodal data from wearables, speech, thermal imagery, UWB sensors, IMUs, and physiological signals to understand stress, affect, speech, and health-related behavior in real-world settings.
Research snapshot
Methods for reliable, equitable sensing in real environments.
Selected publications
Accepted and published work.
Education
Education and credentials.
B.S. Computer and Information Science
BMS College of Engineering, Bangalore, India
Experience
Research appointments and systems.
Technical stack
Methods, tools, and sensing platforms.
Achievements
Fellowships, awards, service, and coverage.
Fellowships and awards
Service
News coverage
Contact
I welcome conversations about trustworthy AI and human-centered sensing.
I am especially interested in multimodal sensing, federated learning, privacy, fairness, and interpretable ML for human-centered systems.