Big Data Challenge

 

STEM Fellowship Big Data Challenge 2016-2017

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Now in its third year, the STEM Fellowship Big Data Challenge is a competition that helps high school students get excited about Data Science and its potential to support inquiry-based learning and problem solving.

                     The challenge is recognized by the Parliament of Canada                                        2016-17 Conference Proceedings

            

 

[24/02/2017] – We are delighted to announce the winners of the 2016-2017 Big Data Challenge, as determined by a final round of presentations at SAS Canada headquarters in Toronto on February 24, 2017 (“Big Data Day”). Prizes for the teams are listed below; the top three teams will also have their final project reports published in the STEM Fellowship Journal.

SAS Grand Prize Winners - Pierre Elliott Trudeau High School

Leon Chen, Curtis Chong, Emily Huang, Nathan Lo
'Effects of Climate Change on Canadian Forest Fires'

IBM Big Data University Award Winners - Earl Haig Secondary School

Tony Xu, Shayan Khalili, Cynthia Deng
'A Study on Factors Related to Readership of Scientific Articles'

Digital Science/Altmetric Award Winners - Earl Haig Secondary School

Peter Chou, Kevin Hong, Chandler Lei, Haolin Zhang
'Correlation Between Cancer Research Trends and Real World Data: An Analysis of Altmetric Data'

SAS Prize Winners - TanenbaumCHAT Wallenberg Campus

Joseph Train, David Roizenman, Seth Damiani, Ronny Rochwerg
'An Analysis of Time and Engagement for Articles Relating to Oncology'

Big Data Day Finalist Presentation Livestream:
Part 1 | Part 2 | Part 3
Big Data Challenge 2016-2017 Figshare

Theme for 2016-2017 Challenge

Using impact data to understand and predict the future directions of science”

This time, competing teams are challenged to interpret and extract insights about the future directions of science from scientific publication attention data provided by Altmetric – a portfolio company of Digital Science.

Computational methods and tools have also been generously supplied by the computing research group SciNet from the University of Toronto, SAS and IBM Big Data University. These will support the students as they try to take an evidence-based approach towards proving or rejecting their own ideas about the future directions of scientific research.

Digital Science will also provide all participating students with tools to help make the the process of managing their project information and producing their final reports easier. A cloud-based collaborative writing tool called Overleaf will be provided. This will help the students work with their mentors to write up the results of their project in a standardized template, similar to those required by actual scholarly journals.

The full project reports of previous Big Data Challenge winners can be viewed in the STEM Fellowship Journal archives.

Overleaf is a portfolio company of Digital Science.

 

What are the prizes for the winners?

  • The prestige of scholarly publication of all project abstracts and full manuscripts of winning project papers in the prestigious STEM Fellowship Journal, published by NRC Research Press.
  • Monetary prizes for award winning teams include $1000 from SAS, $1000 from IBM Big Data University; and $1000 from Digital Science and its portfolio companies Altmetric, Overleaf and figshare.
  • Academic prizes include a SciNet Supercomputer Tour; and special invitations to Talk-and-Tea engagements with leading academic and corporate executives for the teams that receive honorable mentions from the judges.
  • SAS will also provide the winners with tickets to the SAS box for a Toronto Raptors game on March 16, where students will have the opportunity to watch the game while mingling with SAS executives and customers throughout the evening.

Who will be competing this year?

21 teams have entered the STEM Fellowship Big Data Challenge so far.

These include teams from:
all-schools


Abelard School, Toronto
Earl Haig Secondary School, North York
Lowell International Academy, Scarborough
The Academy for Gifted Children – P.A.C.E., Richmond Hill
Pickering College, Newmarket

Pierre Elliott Trudeau High School, Markham
TanenbaumCHAT Wallenberg, North York
Villanova College, King City
Upper Canada College, Toronto


Who is on the judging panel?

Adrian Stanley, Vice President, Digital Science
Mike Boroczki, Director, Canadian Science Publishing
Dr. Bruno C. Mundim, IBM Canada/SOSCIP/SciNet
Polong Lin, Data Scientist, Big Data University, IBM
Mark Morreale, Academic Lead, SAS, and Professor for Epidemiology and Biostatistics, McMaster University

 

Timeline for STEM Fellowship Big Data Challenge 2016-2017

Key Milestone Deadline Date
Deadline for participating student teams to make their project submissions.

  1. Submit your project report before the deadline for evaluation by a team of PhD and industry experts.
  2. Google Share your project report with bigdata@stemfellowship.org, or submit through Overleaf (more details coming soon!)

The Panel of judges will evaluate the projects based on the following criteria:

  • Idea proposed and approach to achieve it
  • Techniques for data and statistical analysis and methods used
  • Number of data sets utilized and correlations between them
  • Results, discussion and compelling arguments
  • Quality of the final report produced: language, figures, plots, etc
January 14th, 2017
The judges select and announce a maximum of 8 competition finalists.

Abstracts of all submitted projects will be published in the winter issue of the STEM Fellowship Journal

Finalists will be expected to prepare a presentation on their project for Big Data Day

Week beginning February 6th, 2017
On Big Data Day, all the teams are invited to the SAS Canada Headquarters, Toronto (280 King St East, Toronto, ON M5A 1K7)

Experts will speak about the latest developments in data science and scholarly publishing.

Top teams will present in front of judging panel of industry and academia leaders.

Judges will select and announce the winners.

February 24th, 2017

Big Data Challenge 2016-2017 Mentors

Anna Mkrtchyan

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Anna received her PhD in Applied Mathematics from The University of Western Ontario working on cell divisions and tissue formation. Afterwards, she joined biophysics lab at McGill University as a postdoctoral fellow where she developed computational models and used simulations to study the dynamics of embryo growth. Anna is currently interested in machine learning and its applications in computational biology and healthcare. Aside from research, she greatly enjoys running, cooking and eating foods from various cuisines.

Jay Rajasekharan

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Jay graduated from University of Toronto with a degree in Mechanical Engineering (minor in Sustainable Energy). He started off his career as a Project Engineer at Honeywell Aerospace, where he managed a portfolio of six projects ($2.3M) that focused on quality improvement, cost reduction, and process improvement for Boeing, Airbus, and Lockheed Martin. Subsequently, he made a switch from engineering to analytics and joined IBM as a Business Analyst under the Infrastructure Services division. Currently, he is driving several productivity programs – using data analytics to optimize business operations by streamlining workflows, improving service levels, and ultimately reducing cost ($2.5M in 2016).

Aside from his career, he is also very passionate about teaching – he volunteers as a tutor at his community library, and as an Alumni mentor at UofT. He looks forward to mentoring the next generation of Data Scientists.


Ching Pan

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Ching Pan is an independent data scientist who currently registers in the Northwestern University’s Master of Science in Predictive Analytics Program. He has worked in China, US and Canada across Energy, Education, Finance and IT industries with rewarding experience in STEM fields. His curiosity in energy and environmental issues motivates and encourages him to team up with younger generations to explore potential resolutions toward challenging social issues with sound data analysis.

His volunteer experience includes being a passionate kid coach in Future Possibilities for Kids organization, where he witnesses how Kids can make differences on the local communities we live in.

He earned his M.Sc. Degree in New York University in 1995 and B.Sc. Degree in Shanghai Jiao Tong University in 1988. He is also a Certified Information Systems Security Professional (CISSP).

Allan Esser

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Allan is an independent consultant with 20 years of experience in advanced business analytics that include; strategy design, portfolio analytics, project implementation and results measurement. Allan’s passion is in solving problems by developing and delivering solutions that add value through transforming data into knowledge and actionable decisions that can deliver measurable bottom-line results.

Allan has experience in a variety of functional areas within the financial services sector including; information management, database design, marketing research, financial modeling and risk management. He has worked with risk management industry thought leaders such Algorithmics, as well as a full range of domestic and International Financial institutions including; Bank of Montreal, GE, and Scotiabank International. Allan’s interests include; credit and market risk management, financial modeling, automated decision process re-engineering, direct marketing and analysis, research methods and design, and customer management strategy development.

As an adjunct faculty member of number of colleges in the GTA, Allan currently divides his time amongst a variety of projects including; program and course development, training and facilitation, public speaking and consulting.


Ross Graham

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Ross Graham began his career developing software for firmware mainframe applications in 1984. He became a Technical Project Manager in 1990. Since then he has been managing both business and technical projects and programs – including data warehouse and big data based projects – in the banking, financial, retail, utilities, and governmental spaces.

Ross Graham is a certified Project Management Professional, and is currently in the process of completing the Data Science Fundamentals Learning path at Big Data Univeristy.

Derek de Montrichard

Derek

Derek is the Director of Credit Risk Modeling at CIBC. An avid SAS user, he is also a member of the Toronto Area SAS Society.

 

 

 

 


Orientation Session Recording

Presentations of competition data from Altmetric, tools from SciNet UofT, IBM Big Data University.

orientation-session


Big Data Challenge 2015-2016 Winners

(as published in the STEM Fellowship Journal)

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