Human-AI Technology Lab Members

Principal Investigator

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My research is at the intersection of health, mobile and ubiquitous computing, AI, and HCI. I work on computational modeling of human behavior (incl. Activity Recognition) from data streams collected through mobile, wearable, and embedded sensors. Examples of my work in the health domain include detection of behavior change in people with depression, predicting mania-depression episodes in bipolar disorder, estimation of symptom severity in cancer patients, and modeling of surgical activities inside the operating room.

I also work on intelligent applications for social good. My recent work in Context-aware Peer-to-Peer economic exchange is focused on connecting communities of people through mobile technology to enable successful and meaningful service transactions, especially in low-income communities. In my research, I draw on methods from Machine Learning, Data Mining, Statistics, and Human-Computer Interaction

Email: ad4ks@virginia.edu

For more information, please visit my faculty page.

PhD Student

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Runze is working towards developing a computational framework for automated discovery and modeling of human rhythms. This project aims to understand the complex principles behind the physical and
psychological abnormalities of human bodies, to plan life schedules, and avoid persisting fatigue and mood and sleep alterations due to the desynchronization of those rhythms.

Email: ry4jr@virginia.edu

PhD Student

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My research interest lies in the confluence of artificial intelligence and human mental health analysis and prediction. My current research looks into the role of passive mobile and fitness sensors in developing the MoodRing application for detecting and predicting changes in adolescent depression. The aim of the project is to enable patients, caregivers, and parents with early intervention alerts to prevent the worsening of symptoms. This project is a reflection of the lab's goals to promote health and well being through intelligent learning of patterns and trends.

Email: tum7q@virginia.edu

 

PhD Student

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My research is focused on Human-Robot-Interaction using emotion recognition and adaptation in humanoid robots. I am particularly interested in using these adaptive humanoid robots for applications such as pain management in children, mental health wellbeing, and fighting loneliness. I use reinforcement learning methods along with facial expression recognition and voice quality analysis for emotion recognition. With the help of these adaptation methods, I hope to explore the capabilities of these robots for detecting unique individual patterns and behaviors for improvement in health outcomes and positive interactions with members of our community. In my free time, I am interested in filmmaking and participating in debates. 

Email: sid@virginia.edu

 

PhD Student

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My research focuses on developing technology dedicated to supporting people's well-being, focusing on mental health and social wellness. To accomplish this, I hope to develop and utilize technology capable of detecting human emotion through sensors, machine learning, and human computer interaction. I plan to use these technologies to help people better understand their mental health and to communicate with others.

PhD Student

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I am interested in modeling for complex, real-world systems. My research focuses on machine learning techniques for times series anomaly detection and risk prediction. I am especially interested in machine learning methods that can account for domain-based constraints or other types of domain knowledge; for example, in the identification and treatment of Parkinson's Disease, hospital readmission prediction, and in other health care applications. I also research techniques for reducing bias in models deployed in consequential real-world settings.