Café Scientifique

Join us for an informal evening of "Talks with Docs!"

Café Scientifique is a series of informal discussions connecting research to important issues of interest to the community.  Enjoy light snacks and refreshments while engaging with cutting-edge, award-winning researchers from Simon Fraser University's (SFU) Faculty of Science.

Our fall Cafes are now over, thank you to everyone who joined us. The next cafe will take place on January 23, 2015. (See schedule below)


All events are held at Boston Pizza (private room) 1045 Columbia St., New Westminster
(2 blks from the New West Skytrain station).

Refreshments are available for purchase. Everyone is welcome to attend.

Reserve your free seat by emailing: cafe_scientifique@sfu.ca
**Note that there is no accent above the "e" in this address.

 

Current Schedule

Location:
Boston Pizza (private room)
1045 Columbia St.,
(2 blks from Skytrain)

New Westminster

Time:
7:00PM - 9:00 PM

Format

In our series, speakers will discuss their health or popular-science related topic, without the use of audio visual materials or handouts, for approximately 30 minutes.  A discussion with the audience will ensue for about 45 minutes while participants enjoy appetizers and beverages.  

Friday, January 23, 2015

Speaker: Dr. Tim Swartz, Professor, Dept of Statistics & Actuarial Science, SFU

Research interest: My general interest is statistical computing. Most of my work attempts to take advantage of the power of modern computing machinery to solve real statistical problems. The area where I have devoted a lot of attention is the integration problem arising in Bayesian applications. Lately, my interest in statistics in sport has grown to consume a fair bit of my time, perhaps too much of my time.

Topic: Sports Analytics

Sports analytics has become an important area of emphasis for professional sports teams in their attempt to obtain a competitive edge. The discussion will revolve around recent work that Dr. Swartz has conducted in sports analytics such as the optimal time to pull a goalie in hockey, insights into home team advantage and the value of draft positions in major league soccer.

 

cafe scientifique

Friday, February 20, 2015

Speaker: Dr. Ryan Morin, Assistant Professor, Department of Molecular Biology and Biochemistry, and School of Computing Science, Associate Member SFU, Scientist, Genome Sciences Centre, BC Cancer Agency

Research Interest:
Applying high throughput sequencing to cancer and human genetic diseases

Topic: "Genome sequencing in cancer and personalized medicine"

Every individual shares a similar albeit unique assortment of chromosomal DNA that collectively encodes the blueprints for life. New DNA sequencing technologies enable rapid and affordable determination of the entire genome sequence of an individual thereby cataloging the genetic differences that make us individuals including the many "errors" in our genomes known as mutations. Potential near-term medical applications of whole genome sequencing include therapeutic decisions in cancer and other diseases as well as prenatal screening. The possible near-term applications and implications of these technologies on our society will be discussed.

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Friday, March 20, 2015

Speaker: Dr. Paul Tupper, Associate Professor, Department of Mathematics

Research interests: I am an applied mathematician, meaning that I use mathematics to answer questions that arise in other fields. I am particularly interested in the fields of linguistics and cognitive science, and use my expertise in differential equations and stochastic methods to model phenomena in these areas.

Topic: Big Data and You: A Skeptic’s Guide

Governments and corporations collect data about you and your activities every day of your life. Data miners use this information to predict your behaviour (such as who you will vote for) or figure out personal details about you (such as whether you are pregnant or not). It is easy to be alarmed. But how powerful really are the techniques in data mining? Dr. Tupper will provide a skeptical look at some of the surprising claims of the new data science.