In April, 2004, as a young Ph.D. post-doc working in New York City, Zhou Wang co-authored a seminal academic paper called “Image quality assessment: from error visibility to structural similarity.” That paper, now cited more times than any other worldwide in the discipline of video quality analytics, heralded Wang’s arrival as a rock star in the field. Since then, Dr. Wang has continued to burnish his reputation as one of the world’s go-to authorities in the area of video transmission. He has helped pioneer the ability to measure the quality of a video transmission in real time — something of a holy grail for broadcasters, large and small. His academic rigour has attracted students who themselves have gone on to become giants in the field, including Dr. Abdul Rheman and Dr. Kai Zeng, who, in 2013, joined Wang in forming SSIMWAVE, a world leader in video analytics. Professor Zhou Wang at the Image and Vision Computing, University of Waterloo As SSIMWAVE’s Chief Science Officer, Dr. Wang’s work has not only driven ground-breaking research but additionally helped produce cutting edge, industry-ready products, was acknowledged in 2015 when he won a Primetime Emmy Award for Outstanding Achievement in Engineering Development from the Academy of Television Arts and Science. “You don’t want to pick the best school when you do a Ph.D., you want to pick the best professor,” said Rehman, explaining how he came to work with Dr. Wang back in 2009. “That’s Dr. Wang. “Really, he is one of the best, if not the best, experts to work with. That’s why I came here.” Known around the SSIMWAVE office as simply “The Prof,” a term that reflects equal parts of affection, reverence and the fact that he remains a full professor at University of Waterloo, Dr. Wang is SSIMWAVE’s heart and soul. He delights in asking, and answering, tough questions — “interesting questions,” as he calls them — and then applying that knowledge to solve commercial problems. Dr. Wang sat down recently to talk about his work, his background and SSIMWAVE’s mission — to help broadcasters deliver the highest quality video images possible with efficiency and economy. Q — Hello, and thank you for joining us. First of all, tell us about your company and what it does, and why it’s important. A — So, if you’re going to store and transmit video from one location to another on the internet — from a broadcast studio to a home television, for instance — you need huge, huge bandwidth. You need so much bandwidth that it’s necessary to do some kind of compression, otherwise the cost [of transmission] would be too high. Video compression is something that a lot of people have been working on. The major difference with our video encoder compression method is optimized for perceptual quality. That’s the key difference. Q — When you say, “optimized for perceptual quality,” you mean that you can tell how good or not the images are during transmission, and then make adjustments, is that right? A — Yes, exactly. We use these perception metrics to drive all kinds of things within this video compression method so that the final outcome of the compressed video is optimized to have the best compromise between perceptual quality and bandwidth. It allows us to gain huge bandwidth savings over typical video coding standards. Q — And those bandwidth savings help your customers, is that right? They achieve better quality with less cost, essentially … A — Precisely that. Q — How did you start down this path? A — I started working on my Ph.D. in 1998, in Austin, Texas. During my Ph.D. research I kept seeing that video image quality was a big problem. I didn’t work on that as my thesis, per se, but one chapter of my thesis was about that. That section [on video visual quality] is growing into what we have now. So that’s 20 years. In the past 20 years, there have been a lot of significant achievements by the research community, but surprisingly these achievements are not reflected in industry, in the real world. Q — And that’s why you started SSIMWAVE, then, is that right? A — Yes. It’s not a theoretical topic. It’s a very practical topic — to predict how humans see quality, it’s very, very practical. Even though people might not understand the algorithms, but the final outcome, everyone can understand and see this is useful stuff. Q — You came from China, to Texas, to New York University, back to Texas, and now Waterloo, and you’ve remained Waterloo-based. How did you end up at University of Waterloo and why have you remained? A — I had a friend from college who was at University of Waterloo and he said there was a position open and he said my background was exactly what they were looking for. I had heard about Waterloo. It has a very good reputation in the academic world and the students are very, very good. So, they asked me in for an interview. And I got a very good impression. I’ve come to really appreciate the academic environment in Canada. As for why we based our company here, well, the university is very supportive. Some very good research takes place there. And Waterloo Region as a whole is very supportive of technology startups, so there’s a lot of upside. You have to remember, when we started, we were three Ph.D.’s. We got a lot of business assistance from the University’s commercialization office — WatCo, as it’s known — and the Accelerator Centre and without it we would have made many mistakes as we grew the company. Q — Tell us a bit about your family background. Why engineering? A — Well, I was born in China. Both of my parents are engineering professors. My father was teaching mechanical engineering, and my mother was teaching thermal dynamic courses. So, it was probably a pretty natural thing that I’d choose the engineering path. I have an older brother, he’s also an engineer, in China. He’s very similar to me, solving technology problems. Q — You were the teacher, the Ph.D. supervisor at University of Waterloo, of your company’s CEO — Abdul Rehman. You’ve clearly remained close. What’s that relationship like? A — Abdul came here in 2009 as a Ph.D. student. He was in Germany doing his Masters. One day he sent me an email and said he wanted to do a Ph.D., and asked if we had a position. I looked at his resume and it looked really nice. He was clearly a really smart kid. So, I recruited several students at that time, including one of the other guys here, Kai [Zeng, SSIMWAVE’s Chief Technology Officer]. At that time the only thing I was focused on was just doing good research. We had no thought of commercializing any of the stuff we were doing. But we were very ambitious about the goals in terms of research. We wanted to make an impact in the field. Every student of course is different, but Adbul is kind of a special student: You don’t have to worry about him, basically. You can give him ideas of where to go and he’ll figure out how to do things. He’ll come up with ideas. Also, he is good at collaborating with other fellows in the research lab. This is something I like: I’m trying to create an atmosphere such that people don’t hide things. They work with each other. This is pretty different from other research labs. Q — What about that Emmy Award? A — Well, it was a big surprise for me. I said, ‘What? I got an Emmy Award?’ I didn’t even know there was a technical Emmy Award. It’s nice in that it means that we’ve had some impact on the industry, but compared to what we’re aiming for now, that’s nothing. Q — What is it about this field that continues to interest you, after nearly two decades of research? What is it that sets SSIMWAVE apart? A — When I work on something, I need passion. I love doing things that are really cool — things that make an impact. I like that. That makes me happy. If I didn’t have passion, I’d get bored very quickly. The things that we’re doing here at SSIMWAVE are, we believe, game-changing. So, I’m excited, even after doing this research for 20 years. That’s my passion. Nothing can stop me from doing that.