I am an incoming Assistant Professor in the Design and Artificial Intelligence programme and Information Systems Technology and Design pillar at SUTD. I lead the Context-Aware Interaction Lab and co-direct SHUAI Lab. In a previous life, I was also a Senior Member of Technical Staff at DSO working in Cognition and Human Factors.
I received my PhD in Information Systems from Singapore Management University, and was fortunate to have been able to work with amazing people like Rajesh Balan, Archan Misra and Youngki Lee and my numerous friends and colleagues in LiveLabs.
My research focuses on two main areas: cyber-physical sensing to augment human performance and understanding and enabling Human-AI interaction.
I design and develop context-aware interfaces that can bridge interaction and communication between people and help them empathise with each other. I use techniques such as computer vision, audio processing, and natural language processing to empower these interfaces. My thesis work was on an augmented virtuality system Empath-D which intelligently utilises computer vision to help mobile user interface designers situate their designs when they design for less abled users.
I focus my research in particular for healthcare and wellbeing. I am collaborating with the Samaritans of Singapore combining methods from human-computer interaction and natural language processing to improve their services. I am also working on computer-mediated interventions that help parents of children with speech language developmental disorders provide parent-based care to improve speech delay therapy outcomes.
I am keenly interested in understanding the tension between humans and AI. My research focuses on exploring the challenges and opportunities in Human-AI interaction. I examine questions such as the following: how can we build trust between humans and AI systems? What are the factors that influence trust in AI systems? How can we design AI systems to engender trust and confidence in their users? How can we improve AI systems’ ability to understand and interpret user intent, particularly in the context of natural language processing? What are the challenges associated with interpreting user input, and how can we design AI systems that accurately understand and respond to user intent? In particular, I am examining the impact of Large-Language Models (LLMs) such as GPT on social media, and for education.