Responsible & Intelligent Sensing for hEalth
Penn State University · College of Information Sciences and Technology
We explore how everyday devices can help us better understand and improve our health. Much of what shapes our health happens between clinical visits: in our daily activities, habits, and environments. We leverage ambient signals around us to monitor our holistic health, while protecting privacy and supporting human agency.
Our research combines ubiquitous computing, signal processing, machine learning, and human-centered computing across three connected directions:
We develop ubiquitous sensing methods to monitor environmental exposure, assess indoor air, and map the environments around us. By combining sensor measurements with machine learning and knowledge of physical systems, we aim to predict their health risks. Moving forward, we are collaborating with architectural engineering experts to monitor children’s exposure in daycare environments.
We use acoustic and wearable signals to understand health beyond clinical settings. Our interests include voice health, accessible speech technology, posture assessment, and human-centered interventions that fit into everyday life. Moving forward, we are collaborating with speech pathology experts to identify new biomarkers and improve communication for people with speech disorders.
How can sensing systems provide useful insights while respecting privacy and agency? We investigate unintended information leakage from audio and other sensor representations, develop privacy-aware methods with domain-adaptive protection, and advance trustworthy AI through explainability and evaluation. Moving forward, we are developing foundational privacy techniques, evaluation methodologies, and trustworthy health AI models.
Detecting and Reducing Generative Artifacts in Diffusion-based Speech Enhancement
IEEE ICASSP ’26
Reliable predictions from audio language models
Under preparation
Principal Investigator · Assistant Professor · Penn State IST
bbc5655@psu.eduBhawana Chhaglani is an Assistant Professor in the College of Information Sciences and Technology at The Pennsylvania State University. She received her Ph.D. in Computer Science from the University of Massachusetts Amherst. Her research lies at the intersection of mobile and ubiquitous sensing, human-centered computing, and responsible AI for health and wellness. She designs intelligent sensing systems that leverage everyday devices to generate meaningful health insights while preserving user privacy and agency.
Her research has appeared in premier venues such as IMWUT/UbiComp, SenSys, ICASSP, EMBC, BSN, and IROS, and has been recognized through honors including the ACM MobiSys Rising Star Award (2025), CPS-IoT Week Best Ph.D. Forum Award (2025), MLCommons Rising Star (2024), and UMass Amherst Dissertation Fellowship (2025). She has collaborated with Nokia Bell Labs, Samsung Research, Dolby Laboratories, Meta Reality Labs, and CMU to translate her systems into real-world deployments.
We are looking for curious, motivated students interested in machine learning, signal processing, mobile and embedded systems, and human-computer interaction. Let's build the future of healthcare together in happy valley!
Interested PhD, master’s, and undergraduate students: please complete our research interest form.
Student Research Interest Form →
Email: bbc5655@psu.edu
Office: E306, Westgate Building, Penn State University
