Philippe Pasquier, PhD

January 05, 2017

“Rational problem solving is just the tip of the iceberg. People who use computers to design, compose music, or make visual art also deserve to have access to the power of modern AI."

Despite having a background in pure mathematics, logic, and artificial intelligence, Philippe Pasquier now explores the link between science and art.

Meet Philippe

1. How would you describe your professional work?

Being a SIAT professor (or in SFU in general) is basically three jobs packed into one: researcher, teacher, and administrator.

As a researcher:

I lead the Metacreation Laboratory in which we collaborate with our inspiring graduate students on research and artistic projects. The Lab counts between 10 and 20 members at any given time. With most of us being both scientists and artists, we have Postdoctoral fellows, PhD, MSc, MFA and even undergraduate students working with us on a variety of scientific and artistic projects.   

As a teacher:

I try to induce passion and diffuse principles and strategies that are most useful for equipping the next generation of Canadians and world citizens. I got to do exactly this for the last 8 years in SIAT, and it has been a blast.

As an administrator:

I help run the school and the University. We organize academic communities, artistic events, workshops, conferences and symposiums, both locally and internationally. 

2. What are your research interests right now?

My students and I are working developing on the next generation of creative systems that automate creative tasks, partially or completely. We then run experiments to see if people can tell—and whether or not the fact that it is a machine doing these creative tasks influences their perceptions.

We are also researching creative processes, as they exist in the real world, as well as processes that can only be thought of through computer programs. Currently, we have systems that generate music, audio, video, comics, animation, dance and visuals.   

3. What inspired you to pursue these interests?

For theoretical and practical reasons, I have always been fascinated by the possibility of automating tasks using machines. I was trained purely in mathematics, logic, and artificial intelligence, but I later realized that rational problem solving was just the tip of the iceberg; people who used computers to design, compose music, or make visual art also deserved to have access to the power of modern AI and machine learning algorithms. 

4. What drew you to SIAT?

SIAT is unique. I was tired of computer science and information systems departments. SIAT is the perfect blend of design, media art, and computational technologies. This is where the future lies.

5. What projects are you excited about right now? 

Like most people interested in technology, I am excited about the prospect of Deep Learning—a trendy name for artificial neural networks. We hope to benefit from the SFU big data initiative to get more computer power for this field.

One of our most exciting new developments is Audio Metaphor, a system that takes a sentence as input and generates a soundscape that is representative of that sentence. 

6. What do you hope students will take away from the SIAT courses you teach?

My class on generative art and computational creativity is a chance to teach non-scientist algorithms ranging from chance operation to Deep Learning. I believe that everyone needs to understand these algorithms to function in a world where they decide so much.

These algorithms fly planes, decide what is recommended for you on Netflix, which book you should read, which music you should listen to, or which post you should see. These algorithms curate our lives.

The class allows anyone to learn a little bit more about AI and machine learning through the lens of artistic practice and computer-assisted creativity.  

7. What SIAT courses do you teach? 

IAT 340: Sound Design

I introduced this course to SIAT when I arrived. It surveys the fundamentals of acoustics, sound effects, and sound production in the context of linear and non-linear media. In this class, we teach students everything they need to know about how to make professional sound design for their projects.

For example, we learn how to create sounds that evoke fear, sadness, or laughter for 30-second video clips. With sound design, we empower students to play with these high level affective parameters. Sound is so evocative, emotional and powerful.  

IAT 380: Generative Art & Computational Creativity

I also teach IAT 380, which is the new Kadenze/SFU class on Generative Art and Computational Creativity. SFU and Kadenze signed a partnership last year and this class is the pilot class that will run for the next 3 years online.

Only 7% of the world’s population has access to a University. We believe that access to the best resources should not depend on geography or economy, so the idea is to lower the bar to entry by providing free content, premium content for a little bit of money, or SFU credits for the usual price. These three levels come with different services, but allow everyone to access the content itself.

The class is a survey of generative art with a focus on the algorithms that used for generation in creative domains.

8. What advice would you give to students for succeeding academically and/or in the industry?

In order to succeed, you need to be focused and persevering. It’s easier said than done.

9. What is one thing your students may not know about you?

I am a yogi, and my headstand is okay.

10. Anything else you’d like to add?

Just do it! ...but read about it first.

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