6 out of 200: Paul Müller is visualizing objects on your screen
Meet Paul Müller in this Q&A series with 6 out of 200 computer scientists and mathematicians participating at the 4th Heidelberg Laureate Forum, September 18-23, 2016. 22 Laureates (Abel Prize, Fields Medal, Nevanlinna Prize, Turing Award) will attend the forum together with them. For a full week, Heidelberg in Germany will be the hot spot of mathematics and computer science.
What is your name and where are you from? I am Paul Müller from Germany.
Where did you study and where are you currently based? I studied Computer Science in Germany and am currently with the Computer Science department at Stanford University.
What is your current position? I joined Stanford as a Visiting Student Researcher and will soon start my PhD in visual computing with an emphasis on real-time graphics.
What is the focus of your research? We are focusing on the whole pipeline of visual computing. Take the rendering of water splashes as an example: One starts with the mathematical description of the underlying physical systems, thinks about how this can be efficiently computed, and finally how to get that onto the screen. The end result is either something rendered in a good-looking way or a visualization of something that is not even visible in reality.
I am at the end of that pipeline, with a special emphasis on real-time graphics and physically-based shading. I look how one can efficiently design the material and lighting properties of such objects and the underlying techniques to render them on the screen as fast as possible.The video shows three examples demonstrating the breadth of applications that use visual computing. The fiber mesh simulation is an example for a physical system that has been simulated to achieve a certain visual effect, as it is used in the film industry. It shows an effect that can be directly visualised. The tooth brushing simulation is an example how visual computing can be used for product design. In this case, the plaque removal performance has been visualized like it would have been done for evaluating different product models. This example uses false colors to visualize a phenomenon that can only be visualized indirectly in reality, e.g. by using coloured toothpaste or by observing plaque buildup over time. The airflow simulation is also an example how visual computing can be used for evaluating products. However, for this example only one slice of the air flow field can be visualized at a given time. The sub-field of scientific visualization addresses the question how such systems can be visualized intuitively and efficiently. © J. P. T. Mueller, Dominik L. Michels, CC BY-NC-ND 4.0.
Why did you become a computer scientist? Wind back the time to the 1990s. Cinema. Steven Spielberg. Jurassic Park. Even though I could not see the movie right when it came out, when I finally got the chance to see it a few years later, the film really left a lasting impression on me.
It was one of the first films that used computer generated imagery to create living, breathing creatures. I was immediately fascinated and awestruck how that was possible. I tried to learn as much as I could, started programming before middle school, and naturally found my way into studying computer graphics—now with a strong background in maths and computer science.
What do you see yourself doing in 10 years? Frankly, the same thing as ten years ago—computer graphics. I doubt the magic will ever go away. I can see my future after my PhD in both academia and the industry.
What are you doing besides research? The bay area around Stanford is absolutely fantastic. We go cycling, hiking, exploring the amazing city that is San Francisco, and walk up the mountains that surround the valley. When I am not outside exploring the bay area or occupied with some of my spare time projects, I also—oddly enough—enjoy reading legal literature
Why did you apply for the HLF? In Stanford I have experienced both groundbreaking research as well as very strong connections to the industry and a real culture of startups that I have never seen before. In the Silicon Valley there is a butter smooth transition between invention and innovation. But even here I cannot meet so many amazing role models all in one place like at the HLF—it is really a unique opportunity.
What do you expect from this meeting? Looking at the laureates, I too see great inventors and innovators. But more importantly, I want to hear from other young researchers how they see their role—and how much emphasis they personally put on invention versus innovation. As inventors, have they already found their area in which they love to work? As innovators, have they maybe even started their own startups? I would love to hear their stories.
Which laureates present at the forum would you really like to talk to? As someone from computer graphics, the natural choice would of course be Fred Brooks and Ivan Sutherland. The more often I look into Brooks’ Mythical Man-Month the more it rings true. And everyone should take a look at Sutherland’s classic presentation, the Sketchpad Demo. In those days, there were no graphical user interface systems, and Sutherland gave a first sneak peek into what might be possible. Today we take these systems for absolutely granted.
As a researcher one can easily get reminiscent of the »good old days« when the frontier of science was very different from what it is today. Some might even argue that we do not have the same opportunities as previous generations of researchers had before. But I do not subscribe to that. I think that every generation of researcher feels like they missed the »golden age« of what happened just before them—but nevertheless they shape the next thing. We do not have the opportunity to write something like Sketchpad. But we’ve got new opportunities, and they are getting more numerous and better with each and every advancement.
So one question I would have for them would be rather strange and deeply personal: Whether they felt like they missed out on something they would consider the »good old days« when they were young. And what helped them going forward to shape the next big thing.