Meet Jian Zhao, a professor passionate about data and novel ways of analyzing, presenting and interacting with it

Tuesday, November 26, 2019

Jian Zhao joined the Cheriton School of Computer Science in fall 2019 as an assistant professor. Previously, he was a senior research scientist in the Enterprise AI group at FX Palo Alto Laboratory in Palo Alto, California.

His research lies at the intersection of information visualization, human-computer interaction and data science. He develops advanced visualizations that promote the interplay between human and machine. He focuses primarily on designing interactive visualization techniques to support complex analytical workflows — from exploratory data analysis to model curation and explanation to insight communication and storytelling.

Jian received his PhD from the Department of Computer Science at the University of Toronto. He is the recipient of several scholarships, including an NSERC Postdoctoral Fellowship and a Mitacs Award. He has received multiple paper awards at top-tier venues and holds more than a dozen patents.

photo of Professor Jian Zhao

Tell us a bit about yourself.

I did my PhD at the University of Toronto under the supervision of Ravin Balakrishnan. My research focus was on information visualization and human-computer interaction. After finishing my doctorate, I worked for about a year at Autodesk Research in Toronto on visualization of complex systems. I then moved to California to start a position as a research scientist with FXPAL in Palo Alto. I was a member of the Enterprise AI team, where I designed and developed visual analytics techniques to support communication and collaboration in an enterprise environment. 

I worked at FXPAL for several years, but I wanted to return to academia so I applied for faculty positions. I’m happy to be back in Canada and I’m excited to be here at the University of Waterloo as a faculty member in computer science.

When did you become interested in computer science?

That’s an interesting question. I wrote my first program when I was in high school. I used Turbo C, a now discontinued development environment that had an MS DOS interface with the blue screen. My cousin helped me install the environment on a computer and he gave me a popular textbook that was used in college at the time. I read the book and learned a lot about programming. 

I built things — I also broke things — and was fascinated by the logic and building blocks in the programming exercise. That’s when I was first introduced to computer science and when I got hooked.

Before joining the Cheriton School of Computer Science, you were a senior research scientist in the Enterprise AI group at FX Palo Alto Laboratory. What attracted you to the School of Computer Science?

It comes down to three reasons.

First, everyone here is welcoming and the school is very collegial. It’s a very friendly working environment.

Second, the strength of research here is very high. I’m a member of Waterloo HCI, a research group with four faculty members from the School of Computer Science — Daniel Vogel, Edith Law, Ed Lank and now me. I work on information visualization, which overlaps a lot with HCI, but it’s an interdisciplinary area connected to work in machine learning, AI and data science. I thought I could act as a bridge between the HCI group and other research groups here. I hope to bring new skills, techniques and insights to the HCI group while also collaborating with researchers in machine learning, AI and data systems. 

Third, I enjoyed my time in Toronto when I was a PhD student and I felt like I had become a Canadian, so being at Waterloo is a bit like coming home.

Another take on this question is why I returned to academia after working in industry. When I was a student I loved the energy of campus life, but you can’t be a student forever. But I can be a faculty member and I hope to contribute to the life and energy of this campus. 

I do value industry experience and I hope to pass on what I’ve learned from my time in industry to my students. Industry is typically much more focused on practical problems, and it’s good to have this perspective along with a good theoretical foundation.

Tell us a bit about your research.

My research is at the intersection of information visualization, human-computer interaction and data science. Information visualization is my main area. The overarching goal of my research is to promote the interplay of human, machine and data within a data science workflow.

We live in the era of Big Data — so much data is available to process and at the same time computation power has never been greater. We’ve created a lot of complicated models, neural networks with millions of parameters. Algorithms are also growing increasingly complex. And the humans who drive the analysis of the data — the number of users working on a problem — is also growing. I want to leverage visualization and interaction techniques to help humans do more within this ecosystem.

I think the bottleneck here is humans. The amount of data just grows and grows as does computation power, so the scale of the problem keeps increasing, but humans haven’t changed. Interactive visualization can help solve this problem because it can amplify our cognitive capabilities, allowing us to see and explore abstract data, abstract models and abstract algorithms more easily. 

I focus on techniques to increase collaboration between humans and machines. How can we work with machine-learning models and abstract algorithms in a way to solve complicated problems. Visualization combines design and data analysis in a way that engages the users. The design part of visualization is critical and we shouldn’t underestimate its importance. 

Do you see opportunities for new, collaborative research, given the breadth and depth of research conducted at the Cheriton School of Computer Science?

There’s a strong HCI group here and each faculty member within it is conducting different research. As a visualization expert I hope to bring new insights to the group’s research. I can see a lot of opportunities for collaboration. In fact, Edith Law and I are already collaborating on a project to use comics to teach programming concepts.

The School of Computer Science also has strong AI, machine learning and data systems research groups. Visualization is not only about users; it’s also about the data. You can view visualization as a way that allows users to interact with abstract data more effectively, so I see a lot of opportunities to collaborate with researchers in the Data Systems Group. I’ve talked to Jimmy Lin and other faculty members in the group about how I can help leverage their techniques to generate visualizations and to use them to explain their data and techniques. It’s a mutually beneficial loop — I can use their techniques and they can use mine.

What do you consider your most significant contribution or work to date?

A couple of years ago I developed a system called FluxFlow, a tool that reveals and analyzes anomalous spreading of information in social media. We’re still talking about fake news and rumours today and it’s an ongoing problem on many social media platforms.

FluxFlow is a system that lets you visualize tweeting and retweeting behaviour across a timeline. It reviews the temporal dynamics of conversations between multiple users on social media. It not only visualizes general conversations, but it can also be used to identify misinformation, rumours and false news and to visualize propagation behaviour patterns across time.

FluxFlow has two parts. It uses machine learning algorithms to detect anomalies and it creates visualizations for presenting detected threads for deeper analysis. The paper on this won an honorable mention award at the 2014 Conference on Visual Analytics Science and Technology. I think this is my most cited paper.

Have early events in your life provided inspiration that you use today?

Yes, I learned to paint during my childhood. I would draw, sketch and paint for fun and I did it for about 10 years. When I went to university I studied computer science, and I found a way to bring my love of art to computers through visualization. Good visualization has a design aspect as well as a data-driven aspect. You can’t concentrate on just one or the other to do visualization well.

What do you do in your spare time?

I enjoying hiking. When I lived in California, in the Bay area, I used to hike a lot. I’ve started to hike in the region here, too. I really enjoy spending time outside, embracing nature and getting inspired by it.

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