Big Data Challenge for High School Students

2020 Finalists

Calgary Finalists

Strathcona-Tweedsmuir School: Lindy Zhai, Brennan Cowley Adam, Bishneet Singh

Sir Winston Churchill High School: Shrinjay Mukherjee, Sunny Zuo, Max Zhong, Abhigyan Garg

Westmount Charter School, Western Canada High School: Duomi Ding, Allan Cao, Alexander Greco

Sir Winston Churchill High School: Ananya Trivedi, Amy Lai, Keanu Liwongan, Yumi Peng

Westmount Charter School: William Zhou, Tony Hu, Dhananjay Patki, Andrew Li

Fremont High School: David Zhang, Amos You

Webber Academy: Anya Pederson, Susan Fountain, Harsh Kumar Patel

Sir Winston Churchill High School, Robert Thirsk High School: Vishwanath Wimalasena, Faiz Hanafi, Ammar Vora, Nishan Soni

Torrey Pines High School: Brian Hsiao, Olivia Chen, Kelly Hu

Westmount Charter School: Priscilla Chirom, Amisha Gill

Toronto Finalists​

Earl Haig Secondary School: Eric Chen, Justin Pang, Leo Tao, Joshua Scripcaru

Earl Haig Secondary School: Arya Shababi, Robin Nash, Maria Pasyechnyk, Ali Seena Shakeri

University of Toronto Schools: Alex Zhuang, Baker Jackson, Jason Xiong, Nathan Kim

University of Toronto Schools: Ryan Alizadeh, Siddarth Dagar, William Szeto, Jerry Wang

Waterloo Collegiate Institute: Narasimha Kalimipalli, John Zhang, Karan Manku

St. Augustine Catholic High School: Louis Sun, Andrew Chen

Humberside CI, Harbord Cl: Lukas Bolsinger, Simon John

University of Toronto Schools: David Tang, Jacky He, Bill Hu, William Li

Erindale Secondary School: Joshua Lakdawala, Yash Jagirdar

Hillfield Strathallan College: Darian Ellis, Vikram Arora, Andrew Kang


New Climate and Information Realities:
From Oceans to Glass of Water

Analyze municipal, federal, global and humanitarian open data surrounding the impacts of climate change on water resources to uncover new trends of relevance to our local and global communities

Your investigation will aid the Canadian Commission for UNESCO in successfully reaching their 2030 Agenda by addressing multiple Sustainable Development Goals (SDGs), including Clean Water and Sanitation, Climate Action, and Life Below Water.

Under the patronage of the Canadian Commission for UNESCO

BDC 2019 Participants

2020 SF BDC Participant Demographics 1

What is the big data challenge?

The STEM Fellowship Big Data Challenge (BDC) is a unique inquiry-based learning program that enables high school students to strengthen their critical thinking and problem-solving skills while gaining familiarity with data science. By encouraging students to conduct research projects to collaboratively address issues of real-world significance, the BDC fosters the development of young leaders, innovators and digital citizens.

How it works: Teams of up to 4 students are each provided with data sets, workshops, learning resources and tools for data analysis. We present the general competition theme, within which you define a research topic of interest. With the guidance of peer and expert mentors, teams then undertake exploratory analysis of open data to develop sustainable solutions to local and global issues. At the end of the competition, teams submit their research findings in the form of a scientific manuscript. The top teams are invited to present their findings in front of a panel of industry and academic experts in the field.

The best part is you don’t even need to have prior data science knowledge to join! We deliver webinars and workshops teaching you the basics to get you started on your research!

Check out our full itinerary here.

All abstracts and the top finalists’ full papers will be published by the open access, peer-reviewed STEM Fellowship Journal, published by the NRC Research Press!


This year’s competition focuses on data analysis relating to impacts of global and micro-climate change in water and oceans for communities, energy generation, agriculture, entrepreneurship, and more. Your investigation will aid the Canadian Commission for UNESCO in successfully reaching their 2030 Agenda by addressing multiple Sustainable Development Goals (SDGs), including Clean Water and Sanitation (SDG 6), Climate Action (SDG 13), and Life Below Water (SDG 14).

Delve into  water, oceans, and climate change problematics through the prism of the Rabbit Hole of Knowledge 

Explore the UNESCO_SDGs and their interconnection with water and ocean quality

Analyze municipal, provincial, federal, global, and humanitarian open data surrounding water and climate to guide your investigation on how these changes impact our everyday life

Discover patterns using data analytic tools, formulate ideas, and develop models

Propose sustainable solutions for your chosen local, regional, and global environmental problems from an environmental or socioeconomic perspective

Present your research findings in the form of a scientific paper

Why participate


Computational Thinking
The ability to translate aggregates of data into abstract concepts and conduct data-based reasoning

Design Mindset
The ability to create solutions in contexts where only part of the requirements are known 

Social Intelligence
The ability to participate in the collaborative  construction of solutions

Digital Citizenship
The ability to utilize information technology in order to engage in society. 


Academic prizes:
– Scholarly publication of all project abstracts and full manuscripts publication of winning project papers in the open access, peer reviewed STEM Fellowship Journal, published by Canadian Science Publishing.
– SciNet Supercomputer Tour
– Receive mentorship from the League of Innovators to scale your project into an entrepreneurship venture

Monetary prizes:
– $1000 Scholarly Communication Award – Toronto
– $1000 Scholarly Communication Award – Calgary



September 21,
September 27,
October 8 -
Orientation Sessions

Q & A for teachers and their students about BDC mentorship and learning opportunities! Our orientation will be held via Facebook live-streams.

The orientation session recording can be found here.

January 18, 2020 - Project Submission Deadline

Submit your project report (developed in Overleaf) before the deadline (11:59 pm EST on January 18) for evaluation by a team of PhD and industry experts.

February 27-28, 2020
- Big Data Day

Take part in Big Data Day in Toronto or Calgary

Attend in-person or join in online for the presentations.

October 18, 2019 - Get Started! (Registration Deadline)

Crowdsource the knowledge and investigate analytics tools
SAS Programming, CISCO Academy Python Pandas, and open source data analysis courses and tools – choose one you will learn and use

Covering entrepreneurial innovations, Overleaf, Cisco Python, R, SAS, and Tableau. To access the workshops (which are available from the start of the challenge), students use JupyterHub, a cloud-based platform provided by Callysto, or download the software directly to their computer.

Organize and plan your project
We recruited a good number of industry experts who are willing to mentor student teams. Based on your team’s choice of data tools, we will match you with mentors from the data analytics and scholarly publishing community.

Work on your data set for 2.5 months
Work together with your mentor and provided resources to analyse your data and propose solutions.

Tell the story of your data discovery through a scientific report
Use Overleaf professional scholarly communication platform to prepare and submit your project report

February 6, 2020 - Finalists Selection

The finalists (top teams per location) will be announced!

If your team is selected, you will deliver a presentation at Big Data Day, the culminating event for the BDC.

2019/20 Reviewers

Dave Carter is a Research Council Officer with Digital Technologies. He holds a M.A.Sc. in Electrical Engineering and pursues work in syndromic surveillance and situational awareness.

Dave Carter (M.A.Sc.) is an engineer with the Text Analytics group at National Research Council Canada and is based in Ottawa. He is the technical lead for NRC’s situational awareness/outbreak detection platform.

Dr. Svetlana Kiritchenko is a research scientist at the National Research Council Canada. She received her Ph.D. in Computer Science from the University of Ottawa (Canada) and her M.Sc. in Applied Mathematics and Computer Science from Moscow State University (Russia). She primarily works in the areas of Computational Linguistics and Natural Language Processing (NLP). Her research interests include ethics and fairness in NLP, sentiment and emotion analysis, text classification, social media analysis, and medical informatics. As part of the NRC-Canada team, she has developed several text classification systems (for sentiment analysis and health-related social media mining) that ranked first in international shared task competitions.

Jason Bernard

Jason Bernard is a PhD Candidate at the University of Saskatchewan researching using artificial intelligence (AI) to model natural processes. This May, he starts a postdoctoral fellowship at McMaster University to investigate models of the brain using AI towards treating neurological disease and injury. He has received the NSERC Alexander Graham Bell CGS/D, Excellence in Research award, Alberta Innovates Technology Futures graduate student scholarship, and was twice recognized for providing outstanding leadership in the military. He is a review editor for Frontiers in Artificial Intelligence and is on the programming committee for the European Conference on Technology Enhanced Learning.

Christine Daly is a Senior Advisor of sustainability and reclamation in the oil sands industry. She holds a B.Sc. in Environmental Science with Honours, where her early research focused on the ecology of the Great Lakes, and a M.Sc. in Biological Sciences which focused on Oil Sands wetland reclamation. Both degrees are from the University of Windsor. Currently, Christine is pursuing a Ph.D. in Environmental Design at the University of Calgary with the intention to learn how to effectively integrate scientific and Indigenous knowledges into landscape design and reclamation in the oil sands.

Christine Daly
Simone Pujatti

Simone Pujatti is an Italian PhD student at the University of Calgary, where he is a member of the Reactive Transport Group. His research team aims to investigate hydrothermal systems in the shallow Earth, characterize mineral reaction rates and test the feasibility of the geological storage of CO2 in rocks. He started his studies at the University of Padova (Italy), then for his master’s he moved to Utrecht University (the Netherlands) where he built a solid background in petrology. His PhD research focuses on water-rock interactions in the oceanic lithosphere, ore-forming processes at the seafloor and silicification reactions in Archean rocks.

Estefania Roldan Nicolau has a BSc in Physics, an MSc in Earth Science, and a profound interest in plants, especially trees. For the last couple of years she has been studying tree interactions with different physical environments. Now, for her PhD project she will explore the mechanisms that allow tree growth on cliffs. To achieve this, she is planning to: analyze the rock stability by modelling rock falls; utilize water budgets and soil-vegetation-atmosphere transport models to understand water transport; and use stable isotopes to determine the age of the water these trees use.

Emilie Falconer

Emilie Falconer is from the University of Toronto, Honours Bachelor of Science in Archeology and Biology. She chooses to focus on the connections people have with their landscapes and ecosystems (for better or for worse) with an emphasis on using science for a more hopeful future.

Samaneh Miri is a second-year Ph.D. student of computer science at the University of Windsor. Her research interests revolve around Big Data Analytics, Artificial Intelligence, Machine Learning, Security, Privacy-Preserving, and Optimization. She is currently working on her thesis with the focus on finding benefits and challenges of applying new framework of AI, named Federated Learning, to healthcare.

_Samaneh Miri

Bonaventure C. Molokwu is a Sessional Instructor at the School of Computer Science, University of Windsor as well as an active researcher in the domain of Artificial Intelligence (AI) with focus on Social Network Analysis (SNA) using Deep Learning (DL) methodologies. Also, he has served as a program committee reviewer/member in the 26th International Conference on Neural Information Processing (ICONIP) which is an A-rank conference based on Computing Research & Education (CORE) classification.

2017/18 Big Data Challenge

  • SAS Award - Tony Xu and Shayan Khalili (Earl Haig Secondary School)