I am an assistant professor in the Department of Computer Science at the National University of Singapore. I design, develop, and evaluate needs-driven infocomm technologies to address new societal challenges, such as urban systems, sustainability and energy management, healthcare and well-being. Research methods include:
- User-centered design of technologies driven by deep requirement analysis with traditional and sensor-based methods.
- Development of new technologies by defining frameworks, and developing toolkits and platforms for rapid prototyping of AI- and machine learning-driven applications.
- Implementation of hardware sensors to acquire context-awareness of users and the environment, machine learning models to interpret higher level semantics, and intelligible user interfaces and visualizations to provide effective insights and services.
- Validation of real-world applications to evaluate technologies in lab and field studies.
I have conducted research in intelligent systems across multiple modalities (IoT sensors, mobile interfaces, web and dashboards) and multiple scales (smartphones, smart homes, and smart cities). This allows me to develop impactful technological solutions for multiple domains, and to translate these innovations from the lab to society.
I am actively looking for highly motivated and talented PhD students, post-doctoral research fellows, interns, research engineers, and visiting scholars. If you are interested to work in the areas of human-computer interaction and ubiquitous / pervasive computing, please feel free to email me and send me your CV and transcript!.
I was 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 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).