My research engages the design and evaluation of novel data-driven systems aimed at increasing algorithmic transparency, preventing privacy violations, and building trust. I'm particularly interested in studying how such systems can enable users to understand and control data practices in the age of ubiquitous computing, inferences, and automated decisions.

My work mostly lies at the intersection of Human–Computer Interaction (HCI), Ubiquitous Computing (UbiComp), and machine learning, but I have also worked on authentication, accessibility, and people-nearby applications. My advisor is Prof. Yang Wang.

I enjoy breaking building things. In the past, I've built applications on several platforms, such as mobile apps and virtual reality systems. I've also organized a civic hackathon, participated in many web design/development competitions, and done research internships at Facebook, Airbnb, and Figure Eight (f.k.a. CrowdFlower). Outside of research, I enjoy running, traveling, sci-fi movies and books, synthwave/retrowave music, geometric abstraction, and games (tabletop, PC, and retro).

• A demo of the crowdsourcing framework I designed at Figure Eight (internship) [video] [paper]
• Command-based browsing powered by machine learning and crowdsourcing [video]
• UniPass: an accessible smart device-based password manager [video] [paper]
• Accessible QR Code Device Pairing [video]
• 3D virtual reality floristry app at ITE Singapore (undergraduate internship) [video]