Open to students from any academic discipline at U of T, the IMI BIGDataAIHUB Case Competition is designed as a developmental opportunity for students to gain additional hands-on exposure to big data and artificial intelligence through real-world data - with the chance to win $25,000 in cash prizes.
WATCH: Two-time winner Alexys Pereira shares his experience with the competition and how it kickstarted his career at Scotiabank.
About the 2022-23 Case Competition
The 2023 IMI Big Data & Artificial Intelligence Case Competition is a multi-faceted competition open to graduate students and undergrads with big data/AI experience from any academic discipline in any year of their academic career at the University of Toronto. Some prior experience in working with big data / artificial intelligence is required.
In addition to the competition, there will be 6-8 advanced technical workshops. Attendance at these is encouraged but optional. They will address specific big data, artificial intelligence and machine learning techniques that competitors may wish to consider employing.
Registered competitors will automatically have access to these workshops, as well as a second set of seminars offered through the IMI BIGDataAIHUB Seminar Series. Students who do not compete in the Case Competition are welcome to register for the Seminar Series.
The event is designed as a developmental opportunity for students. Participants will gain additional hands-on exposure to big data and artificial intelligence as well as an opportunity to practice their formal presentation skills in a safe, fun and collegial, yet competitive, environment.
Students will have their participation added to their Co-Curricular Record (CCR).
Competition Details
Date: November 2022 - March 2023
Location: Hybrid
Entry is FREE and open to all U of T students (masters, PhD, and eligible undergraduates with experience in big data and artificial intelligence)
$25,000 in cash prizes for competition winners
Registration and Competition Details
Register as a COMPETITOR for the case competition - REGISTRATION IS NOW CLOSED. Good luck to all our participants!
The competition will be geared toward graduate students from all three U of T campuses and undergraduate students with advanced programming and AI skills.
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Competition Eligibility for Case Competitors |
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Competition Timeline and Agenda
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November 3rd @ 9:00 AM |
Online registrations open.
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| November 21st @ 5:00 PM |
Online registrations will be closed. Early registration is strongly encouraged as registration may close early depending upon the level of interest.
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| November 26th @ 11:30 AM - 1:00 PM |
Virtual Kick-Off Meeting – This information session is expected via Zoom (Details to follow). All registered competitors are expected to attend the entire Kick-Off Session.
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| November 2022 - March 2023 |
Technical Workshops – A series of big data and artificial intelligence educational workshops will be scheduled in November, December, January, February and March for registered entrants wishing to participate. These workshops are designed to enhance your learning and skill sets. They are encouraged but not required.
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| February 27, 2023 @ 5:00 PM |
All teams are to submit their approach, findings and recommendations via ten-minute voice-over PowerPoint video presentations (i.e. Zoom, or QuickTime videos).
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| March 20, 2023 @ 5:00 PM |
As a condition of remaining in the competition, all finalist teams selected will be required to document their approach, findings and recommendations in a written paper of up to ten pages in length, plus attachments. Some of these finalist team papers may be selected for subsequent publication. All finalists submit their PowerPoint slides and data submissions.
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| March 25, 2023 |
The final round of PowerPoint presentations will be delivered in-person in front of a panel of judges and an audience in the Innovation Centre at the University of Toronto, Mississauga. Finalists will present for up to 15 minutes and a 20-minute question and answer period will follow. The written submissions will be taken into consideration in the selection of the first, second and third-place winners.
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Case Competition: Technical Workshops
All technical workshops will be delivered by zoom. The zoom link will be found in your Quercus shell for the Case Competition. You are automatically enrolled in the Quercus shell as part of your registration.
Check back regularly for the updated technical workshop schedule!
Description: Topics in this workshop include: Introduction to the JupyterHub and Jupyter notebooks; Introduction to Programming Basics in Python; Strings, Booleans and Selection Statements, Functions and Loops; Lists, Numpy, Pandas Series and DataFrames; Presentation of the access to the UTM JupyterHub; Alternatively, installation of Anaconda or use Google Colab.
About the Presenter
Gerhard earned his PhD in Computer Science from the Hong Kong University of Science and Technology. He is an Associate Professor, Teaching Stream at the University of Toronto Mississauga, with a cross-appointment to the Rotman School of Management. His teaching experience, at both the undergraduate and graduate levels, from 2005 to present, includes the following departments and institutions: Mathematical and Computational Sciences at UTM, Rotman School of Management at UofT, Electrical & Computer Engineering at UofT, Management at UTM & UTSC, CCIT at UTM, University of Guelph-Humber, Humber College Business School, Sauder School of Business at UBC, and The Hong Kong University of Science and Technology.
Date: December 5, 2022
Time: 3:00 PM
Presented by: Gerhard Trippen, Associate Professor, UTM
For active case competition participants, view on Quercus
About the Presenter
Gerhard earned his PhD in Computer Science from the Hong Kong University of Science and Technology. He is an Associate Professor, Teaching Stream at the University of Toronto Mississauga, with a cross-appointment to the Rotman School of Management. His teaching experience, at both the undergraduate and graduate levels, from 2005 to present, includes the following departments and institutions: Mathematical and Computational Sciences at UTM, Rotman School of Management at UofT, Electrical & Computer Engineering at UofT, Management at UTM & UTSC, CCIT at UTM, University of Guelph-Humber, Humber College Business School, Sauder School of Business at UBC, and The Hong Kong University of Science and Technology.
Date: January 10, 2023
Time: 4:00 PM
Presented by: Gerhard Trippen
For active case competition participants, view on Quercus
In this hands-on session, we will walk through the steps from cleaning the data and pre-processing, to model selection and evaluation. Furthermore, this session will also cover graph datasets, and how to engineer features from datasets with graph structures. The concepts covered in this session may aid participants with the required skills on how to tackle the competition problems, especially tasks 2 and 3, where it is required to build models and work with customer connections.
About the Presenter
I am currently working as a Data Scientist for Scotia bank, where I research and develop graph models for improving/solving business needs. I obtained my Master's degree in Computer Science from the University of Ottawa, where my thesis was about using meta-reinforcement learning for dealing with online semi-supervised learning.
I have an excellent background in areas such as Deep Learning/Reinforcement Learning, Graph neural networks, and using ML models for solving tasks. I am deeply passionate about solving or improving different business tasks with ML models.
Date: January 19, 2023
Time: 5:00 PM
Presented by: Parsa Vafaie, Scotiabank
Description: Please note that while this was originally a technical workshop for the Case Competition, it has now been moved to the Seminar Series for March 13, 2023.
An accessible overview of quantum computing highlighting recent advances in the industry will be given, with applied examples of how quantum algorithms can be used to solve applied problems in finance. In particular, a quantum machine learning framework to solve a credit scoring problem and a hybrid quantum-classical algorithm to solve a portfolio optimization problem are demonstrated. The talk will also feature an interactive Q&A session to answer any questions the audience has about quantum computing in general and its current and near-term applications.
Members of CPA Ontario may receive CPD credits for attending the seminar
About the Presenter
About the Presenter
Gerhard earned his PhD in Computer Science from the Hong Kong University of Science and Technology. He is an Associate Professor, Teaching Stream at the University of Toronto Mississauga, with a cross-appointment to the Rotman School of Management. His teaching experience, at both the undergraduate and graduate levels, from 2005 to present, includes the following departments and institutions: Mathematical and Computational Sciences at UTM, Rotman School of Management at UofT, Electrical & Computer Engineering at UofT, Management at UTM & UTSC, CCIT at UTM, University of Guelph-Humber, Humber College Business School, Sauder School of Business at UBC, and The Hong Kong University of Science and Technology.
Date: February 8, 2023
Time: 3:00 PM
Presented by: Gerhard Trippen, Associate Professor, UTM
For active case competition participants, register on Quercus
About the Presenter
TBA
Date: March 2, 2023
Time: 4:00 PM
Presented by: Duncan Jones
For active case competition participants, register on Quercus
Co-Curricular Record (CCR) Notation
The Co-Curricular Record (CCR) is an official U of T document that recognizes the value of student engagement and co-curricular involvement as an important part of your holistic university experience.
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