Big Data Challenge

STEM Fellowship Big Data Challenge 2017-2018

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Now in its fourth year, the STEM Fellowship Big Data Challenge introduces high school students to Data Science and helps them develop their analytical abilities as digital citizens.

The STEM Fellowship Big Data Challenge is an online Big Data inquiry and experiential learning program where students participate in-person or remotely in orientation sessions, workshops, mentorship, and Big Data Day. 


Theme for 2017-2018 Challenge

Think Global and Act Local with Big Data”

This year’s theme surrounds the UNs 17 Sustainable Developmental Goals.

The competition is an opportunity to develop

Global Citizenship – The opportunity to be part of designing and implementing a vision for a more sustainable world by 2030.
Computational Thinking – The ability to convert large amounts of data into a broad working problem (or How Might We… Problem) and conduct data-based reasoning to refine the problem’s scope.
Design Mindset – The ability to generate and create solutions in contexts where only part of the solutions’ requirements are known ahead of time.
Cognitive Load Management The ability to evaluate the quality of obtained data and then filter the usable information that is needed to produce successful solutions.

Get to know the most pressing problems surrounding climate change through the online footprint of the world’s top academic research publications. Please see the Digital Learner Inroads into Climate Change and UNESCO sustainable development and environmental data.


Participating Teams

30 teams from: the Abelard School, Bayview Secondary School, Earl Haig Secondary School, Erindale Secondary School, Lowell International Academy, Northern Secondary, Princeton International School of Mathematics and Science- P.R.I.S.M.S., St. Francis High School, The Academy for Gifted Children – P.A.C.E.,  TanenbaumCHAT Wallenberg, the University of Toronto Schools, Villanova College, and Webber Academy have joined the competition.

 


Finals

Project submissions were reviewed by a team of PhD, PhD-candidate and MS readers (their profiles have been provided below!) Readers were randomly split into teams of 3 and were randomly assigned to review 7 papers each. Submissions were assessed based for techniques (data and statistical analysis); methods used/implemented; the diversity and representativeness of the data sets utilised and the correlations among them; the results, discussion and compelling arguments made; and presentation (report language, figures, plots, etc.). Each submission was assessed by 3 readers independently. The results of the team project submissions are (max. score is 3):

Team Score
Tanenbaum CHAT
Jason Arbour, Jordan Juravsky, Shahar Lazarev, Josh Zwiebel
2.75
The Abelard School
Tasneem Badshah, Dominik Bednarczyk, Joshua Rosenberg
2.75
Princeton International School of Mathematics and Science
Yingyi Liang, Zhamilya Bilyalova, Haohao Fu, Cheng Guo
2.75
Tanenbaum CHAT 
Jonah Garmaise, Ethan Ohayon, Mason Silver, Jonah Belman
2.67
St. Francis High School
Rohit Menon
2.67
Phillips Exter Academy
Jack Zhang, Evan Chandran
2.67
Bayview Secondary School
Peter Lai, Sean Tao, Kaveeshan Thurairajah, Ryan Yu
2.67
University of Toronto Schools
Katherine Gotovsky, Alain Lou, Arielle Shannon, Jing Yi Wang
2.5
Webber Academy
Aaron Abraham, Kevin Lin
2.5
Earl Haig Secondary School
Tony Xu and Shayan Khalili
2.42
PACE
Ashlee Jiang, Daniel Pechersky, Kayley Ting
2.33
Earl Haig Secondary School
Seyed Sepehr Seyed Ghasemipour, Shayan Ghaffari, Rishabh Jain, James Kosic
2.33
Earl Haig Secondary School
Nathaniel Chan, Jacky Lee, Tony Liu, Jason Yuen
2.33
Villanova
Jamie Birker, Valerie Hermanns, Akera Otto, and Olivia Wignall
2.25
Villanova
Yixuan Chen, Mo Chen, Loredana Cirillo, Haoru Meng
2.17
Tanenbaum CHAT 
Joseph Train, David Roizenman, Seth Damiani, Ronny Rochwerg
2.08
PACE
Jonathan Chiang, Isaac Fung, Ritvik Singh, Gabrielle Terekh
2
Earl Haig Secondary School
Ayeze Hassan, Nameera Azim, Andre Cao, and Pearl Clam
1.92
Earl Haig Secondary School
Parsa Moghaddam, Farbod Naji, Arash Motazedian, and Milad Saadati
1.67
PACE
Serena Perera, Lily Azzopardi, Adi Fishkin, Andrew Schmittat
1.67

 

The top 8 Canadian teams and top 2 International teams who advanced to the finalists’ round at Big Data Day are:

(Big Data Day: SAS Headquarters, 280 King St East, Toronto, ON M5A 1K7 on February 22nd, 2018- teleconferencing is also available!)
Contact: bigdata@stemfellowship.org

Tanenbaum CHAT 
Jason Arbour, Jordan Juravsky, Shahar Lazarev, Josh Zwiebel
The Abelard School 
Tasneem Badshah, Dominik Bednarczyk, Joshua Rosenberg
Princeton International School of Mathematics and Science
Yingyi Liang, Zhamilya Bilyalova, Haohao Fu, Cheng Guo
Tanenbaum CHAT 
Jonah Garmaise, Ethan Ohayon, Mason Silver, Jonah Belman
St. Francis High School
Rohit Menon
Phillips Exter Academy
Jack Zhang, Evan Chandran
Bayview Secondary School 
Peter Lai, Sean Tao, Kaveeshan Thurairajah, Ryan Yu
University of Toronto Schools 
Katherine Gotovsky, Alain Lou, Arielle Shannon, Jing Yi Wang
Webber Academy
Aaron Abraham, Kevin Lin
Earl Haig Secondary School 
Tony Xu and Shayan Khalili

 


Prizes

  • Arnold Chan Student Innovation Award
  • SAS prize ($1000)
  • Digital Science Award (Altmetric, Overleaf and Figshare)
  • Invitation to the SAS box for the Raptors game 
  • SciNet Supercomputer Tour
  • Scholarly publication of the top three projects with the STEM Fellowship Journal
  • Royal Bank of Canada Award (TBD)

More prizes are on the way!

 

 


Reviewers

 Shreya Badhrinarayanan

Shreya Badhrinarayanan is a fourth year Canadian medical student studying in the United Kingdom. She is a self-motivated and dedicated individual with a keen interest and extensive experience in Data Science, Leadership and Management within STEM. She is passionate about digital health and care deeply about building clinical communities and improving patient care. She is looking forward to discover the analytical and inquiry potential that participants have acquired in data science fundamentals through the Big Data Challenge.

 

Sarah Rosengard

Sarah Rosengard is an oceanographer from Queens, NY, gradually curing her fear of waves by exposure to the sea. Sarah completed a PhD in chemical oceanography at MIT/ Woods Hole Oceanographic Institution, where she researched organic carbon in the Southern Ocean and Amazon River Basin. There, she developed a deep interest in applying earth science through policy and outreach. Now, as a postdoctoral fellow in the University of British Columbia Ocean Leaders program, Sarah uses optical measurements of the sea surface to study the phytoplankton communities in the North Pacific Ocean and their impact on local salmon populations. She hopes that this work improves policies for managing the Pacific sockeye salmon, and opens up creative opportunities to share important ocean concepts with the public.

 

 

 Kaleigh Davis

Kaleigh Davis is a first year PhD student at the University of British Columbia and lover of all things aquatic. She studies the effects of temperature on species interactions and community structure in bacterial and planktonic systems. Alongside her academic research, she loves to share her passion for science through engagement with local science communication and outreach programs. When she is not in the lab, you can find her birdwatching, doing yoga, or hunting for new additions to her record collection. To keep up with Kaleigh, follow her on twitter at @kaleighedavis.

 

Jianing Lu

Jinaing Lu is currently studying physics at University of Toronto. She is passionate about solving real world problems with systematic thinking and mathematical modelling, and have relevant experiences in competitions like the Mathematical Contest in Modelling. In her spare time, Jianing enjoys writing sci-fi stories.

 

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 Dr. Emily Estes

Dr. Emily Estes is a chemical oceanographer interested in geo-microbiology, mineralogy, STEM education, and hiking with her dog. She is currently a postdoctoral scientist at the University of Delaware working with George Luther to assess the role hydrothermal vents play in supplying trace nutrients, such as iron, to remote parts of the ocean. Emily received her PhD from the Massachusetts Institute of Technology – Woods Hole Oceanographic Institution Joint Program, advised by Colleen Hansel. There, she investigated organic carbon in extremely old sediments (> 1 million years) to determine how that carbon is stable on such long time scales. Emily tweets about science and the environment @emmoxiely.

 

Hema Nadarajah

Hema Nadarajah is a PhD student in Political Science specializing in International Relations and is originally from Singapore.  Her research interests concerns studying the political processes of translating scientific knowledge into international policy and cooperative management in regions such as the Arctic as well as studying the influence of legal instruments pertaining to science and technology, in inter-state relations. Hema has a Master of Environment from the Australian National University where she specialized in Climate Change Policy and Economics, and a Bachelor of Science from the University of Toronto where she majored in Geography and Geology.

 James Bramante

James Bramante is a PhD student in the MIT/WHOI Joint Program in Oceanography. He researches the structure and evolution of coastlines in the Pacific Ocean constructed from modern and ancient coral reefs. He also studies climate variability over the past 5-10 thousand years and how it has influenced the formation of tropical cyclones (aka hurricanes, typhoons) in the Pacific. The best part of his job involves traveling to remote islands and digging in the sand and mud there. When not performing research, he enjoys the outdoors, playing board games, and exploring the world through the eyes of his three-year-old son.

Helena McMonagle is a research assistant at Woods Hole Oceanographic Institution. She is interested in climate impacts on fish ecology, fisheries management, science communication, STEM education, and being outdoors (preferably in the water). She graduated from Wellesley College in 2016 with a Bachelor’s Degree in Biological Sciences.


Mentors

 Arjun Asokakumar 

Arjun is currently a Senior Manager at BMO leading a HR Analytics practice for the retail and wealth management businesses.With over 10 years of experience in HR and Masters degree in Management Analytics from Queen’s, his career has been focused on evolving HR to be more scientific through descriptive, predictive and prescriptive analytics. He is an avid researcher, self-professed data geek and life-long learner. He hopes to instill some of this enthusiasm in the next generation of data scientists.

 Artem Zaloga

I studied Engineering Physics (Queen’s U) and Physical Oceaongraphy (UBC), and am now working on some online mathematics education projects for students in grades 6-12. I would like students to be curious, be able to think for themselves, and think of the dynamics between people and the planet – which is why I am doing this.

Farooq Qaiser

Farooq  is a Data Analyst with MaRS Data Catalyst where he uses data science techniques to advance understanding of innovation and entrepreneurial activity in Canada. Prior to that, he worked as a Market Research Analyst at Bell.

In his spare time, Farooq enjoys giving back to community (Data4Good), competing  in hackathons (winner at HackOnData 2017) and working on side projects (currently building a self-driving car).

Farooq has a BSc in Accounting and Finance from the London School of Economics and Political Science.

 Indrani Gorti

Indrani Gorti is currently working as  Data Scientist in Banking.  She has a Masters in Computer Science  and has experience working as Data Scientist/Data Engineer in her previous roles at Bell Canada and Nuance Communications. She was a winner in the Toronto Apache Spark Hackathon 2016 (Toronto) and has keen interest in working with data from different domains.  Indrani is interested in mentoring students and to aid in discussions regarding career options in working with large scale data.

 Jay Rajasekharan

Jay Rajasekharan started his career as a project engineer at Honeywell Aerospace, where he managed a portfolio of projects that focused on quality improvement, cost reduction, and process improvement for Boeing, Airbus, and Lockheed Martin. Subsequently, Jay 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 drive insights from business operations and implementing optimizations such as streamlining workflows, improving service levels, and ultimately reducing cost. Aside from his career, Jay is very passionate about teaching – he volunteers as a tutor at his community library and as an Alumni mentor at the University of Toronto.

Mark Fruman

Mark studied physics and atmospheric physics at York University and the University of Toronto.  After his Ph.D., he spent nine years researching multi-scale waves in the atmosphere and oceans, first at Ifremer in Brest, France, and then at the Goethe University in Frankfurt, Germany.  He currently works as a data scientist at CaseWare International in Toronto, applying machine learning algorithms to problems involving financial data.

 Michael Levinshtein 

More than 20 years of SAS experience. 15 years of Response Models development including Data Mining, 2 years of Credit Risk Models development in TD Bank.

Motasem Salem

Motasem is a Data Scientist / Data Engineer at Flipp. His background is in Computer Science and he is currently pursuing a Master of Information and Data Science degree from UC Berkeley. He worked previously in Software Engineering, Enterprise Application Integration and technology focused strategy consulting.

Pranav Barot

I am a second year mechatronics engineering student from the University of Waterloo, currently working as a data scientist for co-op at TalkIQ, looking to share my knowledge with young, eager data scientists however possible! I have experience with machine learning, deep learning and natural language processing and I’d be happy to help anyone looking to learn more about these topics. I am a hackathon enthusiast (winner at McHacks 2016) and am very much into fitness, music and learning new (linguistic) languages and technologies and exploring their applications in the modern world.

 Roy Gupta


Roy is currently working as Manager, MIS Analytics in Banking with more than 6 years of experience in Business Analytics – including last one year in machine learning / predictive modelling. While engaging Machine Learning methodologies in Global Banking and Markets, Roy is also involved in extracting and delivering key actionable business insights for the senior level executives. Passionate about continuous learning and training – Roy wants to mentor the students participating in STEM Fellowship Big Data Challenge to share the knowledge he gained during his education and work experience in business management, computer science and management analytics.

Shruti Bhanderi

Shruti is a Masters (Computer Science) student at McGill University. She has been working as a Data Scientist intern at Ericsson. She applied to to be a STEM Fellowship mentor to help and motivate students for their career in data science. She wants to share her insights in Computer Science gained through her journey of undergrad, masters and industrial experiences.

 

 


The challenge is recognized by the Parliament of Canada

 


Orientation Session Recordings from the 2017-2018 Big Data Challenge 

Presentations of competition resources, tools and topics by SciNet UofT and SAS.

SAS Canada Academic Program Resources for Faculty in Canada

 

SAS Canada Academic Program Resources for Students in Canada

Orientation Session Full Teleconference


Big Data Challenge 2016-2017 Winners

(as published in the STEM Fellowship Journal)

screenshot-2

 

 

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