My research involves the design and evaluation of user-facing, data-driven systems aimed at increasing algorithmic transparency and preventing privacy violations. 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 decision-making.

My work mostly lies at the intersection of human–computer interaction, ubiquitous computing, 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 have built applications in several platforms, such as mobile apps and virtual reality systems. I have also organized a civic hackathon and competed in many web design/development contests. Recently, I joined Figure Eight as a research intern (Summer 2018) to advance the synergy of machine learning and large-scale human intelligence.

When my masters allow it, I'm out for a run or a hike in beautiful Upstate New York. I love traveling and learning about different cultures. Among other things I like are 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]
• Task-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]