I am a software engineer at YouTube Music, working on models to understand our music corpus. Previously, I helped launch a query suggestion model in GBoard trained using federated learning. Prior to that, I worked on UIs for editing the Knowledge Graph.

I received a PhD from UC Berkeley's Department of Computer Science on Dec. 2013, where I was advised by Professor Maneesh Agrawala. I worked on various topics within human-computer information, specifically information visualization. My thesis was on techniques for improving the usability of existing charts.

During my time at Berkeley, I was affiliated with the Visualization Lab and the Berkeley Institute of Design. I also had the privilege of working with amazing people at Microsoft Research, PARC, and Autodesk Research.

Prior to Berkeley, I studied Engineering Science at the University of Toronto.

Recent publications

CHI 2014 - Text References Extracting References Between Text and Charts via Crowdsourcing.
Nicholas Kong, Marti A. Hearst, Maneesh Agrawala.
CHI 2014, pp. 31-40.
InfoVis 2012 - Graphical Overlays Graphical Overlays: Using Layered Elements to Aid Chart Reading.
Nicholas Kong, Maneesh Agrawala.
InfoVis 2012, pp. 2631-2638.
CHI 2012 - Delta Delta: A Tool For Representing and Comparing Workflows.
Nicholas Kong, Tovi Grossman, Björn Hartmann, George Fitzmaurice, Maneesh Agrawala.
CHI 2012, pp. 1027-1036.
UIST 2011 - ReVision ReVision: Automated Classification, Analysis and Redesign of Chart Images.
Manolis Savva, Nicholas Kong, Arti Chhajta, Li Fei-Fei, Maneesh Agrawala, Jeffrey Heer.
UIST 2011, pp. 393-402. [Notable Paper Award]


I was born in Calgary, Alberta, but I spent my formative years in The Netherlands. I'm very much a third culture kid. I'm constantly listening to music -- from metal to jazz to classical and everything in between. I'm also married to a wonderful data scientist.