About

I am an Assistant Professor in the School of Information Technology at York University. I am a member of the Graduate Faculty for both the Department of Electrical Engineering & Computer Science and the School of Information Technology. Before joining York University I was a postdoc in the HCI group at Stanford University, where I worked with Maneesh Agrawala.

My research focuses on combining information visualization and human-computer interaction with natural language processing to address the challenges of the information overload problem. More specifically, I focus on devising novel visual analytics techniques to explore large datasets such as online conversations as well as understanding the utility and potential trade-offs of such techniques from the real user’s perspectives.

I received my Ph.D. in Computer Science from University of British Columbia, under the supervision of Giuseppe Carenini. Prior to that, I completed my M.Sc. degree at Memorial University of Newfoundland under the supervision of Orland Hoeber and Minglun Gong. I have conducted research on visual analytics at Tableau Software and the Qatar Computing Research Institute. My work has appeared in top journals and conferences including IEEE Transactions on Visualization and Computer Graphics, ACM Transactions on Interactive Intelligent Systems, ACM CHI, ACM IUI, ACM UIST, EuroVis, and ACL.

Prospective Students

I am looking for qualified students for positions in my research group, including MSc and PhD students in Computer Science, and Master of Information Systems & Technology students. Please drop me an email with your CV if you are interested in pursuing research in any of the areas of natural language processing, information visualization and HCI.

Research Interests

  • Information Visualization and Visual Analytics
  • Natural Language Processing
  • HCI

Recent Projects

Visual text analytics for online conversations

We developed visual text analytics tools and techniques for exploring and analying online conversations.

Natural Language Interactions with Visual Analytics

This project explores how principles from language pragmatics can be applied to the flow of visual analytical conversations, using natural language as an input modality.

User-Adaptive Information Visualization

This project explores how user characterstics impacts on visualization effectiveness and how can a visualization adapt to such characterstics.