I am currently a research scientist at the Institute for Infocomm Research in Singapore where I lead the research on Interactive Visual Data Analytics in the Urban Systems Initiative. Other research includes data analysis for public health campaigns, urban planning, and developing apps for behavior change intervention.
I design, develop, and evaluate needs-driven infocomm technologies to address social challenges, such as urban design, sustainability and energy management, healthcare and well-being. My technological focus is on sensor-driven context-aware applications, which can do sensing, complex inference and decision making using rules and machine learning. With the ubiquity of sensing from mobile, wearable, and city-level data sources, I also aim to improve the usefulness and effectiveness of intelligent systems to help users and decision makers visualize and understand their underlying data and reasoning processes. Research methods include:
- User-centered design of technology driven by deep requirements analysis from domain experts and end-users through client discussions, surveys and interview studies.
- Developing new technologies by defining frameworks, and implementing toolkits and platforms to lower the barrier for rapidly developing AI- and Machine Learning-driven applications.
- Implementing and validating applications to demonstrate the effectiveness of the implemented technologies and features to achieve defined metrics.
I was a post-doc researcher at the Fraunhofer Center for Sustainable Energy Systems in Boston where I started and led the Home Energy Management (HEM) Lab. My research focused on creating the Fraunhofer Experimental Smart Home (FRESH) Research Platform as a hardware/software platform to partition and perform research in the areas of sensing and control, novel application logic using machine learning, customizeable user interfaces, and data storage and analytics.
I earned my Ph.D. in 2012 from the Human-Computer Interaction Institute (HCII) at Carnegie Mellon University. My advisor was Anind Dey. My thesis investigated how to support intelligibility in context-aware applications to improve user understanding and trust.
I have also obtained the A*STAR National Science Scholarship, providing funding for my undergraduate (Fall 2003 – Spring 2006) and graduate studies (since Fall 2007).