News

Photography by Jon White

Over 100 undergraduate and graduate students gathered in Mathematics 3 early Saturday morning to tackle large datasets at The Data Open, a competition that brings together the best minds in mathematics, engineering, science and technology to collaborate and compete using the world’s most important data sets. Students received the data sets at 8:00 a.m. and, in teams of three to four, had until 3:30 p.m. to analyze the data, extract meaningful insights, and propose solutions to a socially impactful problem.

While challenging, DataFest 2018 was an incredibly rewarding experience that taught us about the nuances of real world data, resilience and the power of team work

Over 100 undergraduate students spent 48 hours on campus analyzing and applying data as they competed in the 2018 ASA DataFest competition this past weekend. Worldwide, more than 2,000 students participate in this competition at several of the most prestigious colleges and universities.

For two consecutive days, students worked around the clock to put their data analysis skills to the test with more complex data than what they would normally be exposed to in class. Once the data is analyzed, groups had only two slides and five minutes to convince the judges that the conclusions they drew from the data were deserving of one of three titles: Munich Re Best Insight, Best Use of External Data, or Best Data Visualization.

Imagine analyzing 10 trillion data points, from a variety of sources, collected at an extremely fast rate. The data can help address business challenges companies faces every day, and possibly even predict client behavior– but you’re not sure where to start. How do you sift through the data that’s available to you, and draw out just the information you need?

BELIVEAU, Audrey (PhD 2016, Simon Fraser University) comes to us from a Post-Doctoral position at the University of British Columbia. Her research interests include survey sampling, meta-analysis and applications in ecology and epidemiology. More specifically she has a number of interdisciplinary research collaborations with fisheries biologists. With her interest and experience with applications and her research focus, Audrey complements the department’s existing strength in biostatistics and greatly expands our scope for ecology related statistical research.

Supervisor:  Dr. Mohan Chaudhry

Project Title: Inverting transforms that arise in the study of Markov models

Many of the analytic solutions in queueing and other stochastic processes are derived in various transforms such as probability generating functions and Laplace transforms. The problems become more complicated if there are unknowns in the transforms. Several complicated algorithms/methods have been proposed to invert such transforms. We have developed a software program which inverts such transforms using the roots of high degree polynomials and transcendental functions. Our method of inverting such transforms is much more efficient and fast when compared with other methods.

Student's role: The student's role will be to invert such transforms using mathematical tools such as MAPLE/MATLAB or MATHEMATICA and QROOT, a software developed by us as well as do some mathematical typing.

We are very pleased to announce that the inaugural lecture in the David Sprott Distinguished Lecture Series will be given by Professor Art Owen from Stanford University on May 14, 2014 at 4 pm.