Main Stage Program : September 29th 2020

All sessions will be live streamed online and available on-demand until Oct.31.

Main Stage

  • Opening Keynote: Using Tech for Good Can Power Greater Representation

    08h45 - 09h15

    This year, we have witnessed a massive call to action for leaders across industries to take a hard look at their organizations as we navigate cultural and societal changes. But what can the technology industry stand to learn from itself during this time? We know that technology can bring us together even if the world feels divided, but it needs to go a step further. 

    We need to empower the world with an opportunity to use tech for good. This means leaning into social matters and remaining flexible, open and understanding as massive cultural movements occur. It means resetting standards and prioritizing diversity, equity and inclusion in every business decision – from policies and practices to processes and products – and taking accountability. 

    In this keynote, Eric Merkow, Industry Manager, Technology at Facebook will discuss: 

    • How to blend the efficacy and efficiency of technology with the warmth of human connection to drive genuine, authentic and positive social impact
    • The importance of technology leaders innovating for a better future by building more representative and diverse teams
    • How to use tech for good – from leveraging the unprecedented resources, data and aid available across technology platforms for social good – to using tech to foster creativity, increase engagement, distribute information and drive real change
    • Eric Merkow Industry Manager, Technology Facebook
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  • Bridging The Tech Skills Gap - Panel

    09h15 - 10h00

    Recruiting a workforce with the necessary technical skills is vital for driving digital transformation. Currently, this is a major challenge in this era of innovation and businesses must ensure that the workforce of the next decade has the required skills. Join our panel of industry experts as they explore how to identify, recruit and retain the right talent for the job.

    • Maryam Haghighi Director, Data Science Bank of Canada
    • Kerry Joel VP Digital Experience Rogers Communications
    • Christian Menkens Chief Technology Officer Intact Insurance
    • Michael Baraban [Moderator] Managing Director iFathom
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  • Break & Networking

    10h00 - 10h30
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  • How Organizations Can Put Their Data to Work and Build 10,000 Responsible, Human-Centric AI Models

    10h30 - 11h00

    Organizations have the raw material needed to transform their businesses sitting in their databases around the world. Many have built AI proofs of concepts, launched pilots, and some have even succeeded in scaling those initiatives. But how can all organizations go from where they are today to a future where AI permeates every decision and service? How can they fundamentally transform their business while still having complete trust in the models that they produce? In this talk, Kurt Muehmel, Dataiku's Chief Customer Officer, will discuss the technical, organizational, and ethical requirements for doing so.

     

    • Kurt Muehmel Chief Customer Officer Dataiku
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  • Keynote: Deep learning for Self Driving Vehicle Technology

    11h00 - 11h30

    At the Uber Advanced Technologies Group's (Uber ATG) R&D centre, we are working on advanced state-of-the-art machine learning models for solving a large range of problems in self driving vehicle technology including perception and prediction, motion planning, mapping and localization, sensor simulation, and more. All that work is publicly available through academic conferences and venues. In this talk Inmar will cover some exciting recent advances out of the company's Toronto R&D hub and also discuss the path to production, namely how Uber ATG goes from research prototypes to deployed systems on their fleet of self-driving vehicles. 

    • Inmar Givoni Director of Engineering Uber Advanced Technology Group, Toronto
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  • Tale of Data Science

    11h30 - 12h00

    Everyone thinks data science is a recent field, but it actually began over 20,000 years ago. In this talk, Dr. Hilal will take you on a journey of how data science has evolved over the years. From using bones to count, all the way to the modern computing and mobile era, discover what the real meaning of data science is and what good data science looks like. 

    • Ella Hilal Director of Data Science and Engineering Shopify
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  • Lunch break

    12h00 - 12h45
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  • Canadian Landscape Panel

    12h45 - 13h30

    Canada continues to strive to unlock the benefits of technological transformation through embracing a culture of innovation. Some of Canada’s great start-up founders will come together to discuss building a sustainable and successful start-up and ultimately how to leverage emerging opportunities to compete in the global economy.

    • CG Chen Founder and CEO Ample Labs
    • Arsene Toumani Co-Founder and CTO TelosTouch
    • Ryan Khurana [Moderator] Research Fellow Montreal AI Ethics Institute
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  • Main Stage
  • MLOps, Governance and Trust

    13h30 - 14h00

    More and more companies have the ability to build Machine Learning models, but models only generate value once they hit production. The reality is that a lot of data science projects never go to production and remain POCs. Having a good process to validate, deploy and operationalise models and then manage and monitor them in production is becoming increasingly important for organisations to scale their use of Machine Learning. Data Science teams need to have strong processes to ensure high standards model governance approved by IT and compliance functions: this is what we call MLOps. In this presentation, DataRobot shows and tells why, what, and how you should think about MLOps, regardless of where models are built or where they’re deployed.

    • André Balleyguier Chief Data Scientist EMEA DataRobot
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  • Putting Big Data Self-Service Analytics in the Hands of Businesspeople (Big Data Toronto)

    14h00 - 14h30

     

    Analytics is currently the purview of a narrow group of data scientists and trained analysts, with business users bottlenecked by those experts, or left to rely on static BI dashboards that are too slow for data exploration.  

    In this talk, Peter Kacandes, product marketer at Imply, will discuss:

    • the origins of this problem in the architecture of the current analytics tech stack, and the emerging hot analytics technology stack, which opens up self-service analytics on real-time big data to hundreds or thousands of business people at a company.  
    • how a real-time data store that is 10-100X faster than data warehouses or data lake query engines, combined with an intuitive and high-speed UI, can empower untrained “citizen analysts” such as marketing, product, and operations managers, to make myriad daily decisions faster and data-driven. 
    • The learnings of well-known companies who have implemented hot analytics for use cases such as user behavior, network, application and service performance monitoring, and real-time fraud detection.  

       

       

    • Peter Kacandes Software Product Marketer and Manager Imply.io
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  • The Architecture Behind Modern Cloud Data Warehouses

    14h30 - 15h00

    The first generation of cloud data warehouses emerged several years ago, allowing BI/reporting and data analysis teams to benefit from cloud infrastructure and self-service provisioning. However, cloud infrastructure services and data warehouse technology have evolved a lot since then, leading to a new generation of cloud databases built on principles such as separation of compute and storage. Let's dig in and take a deeper look at cloud data warehouse options, both new and old, to uncover key architectural differences and understand why now is time to move on from older, first-generation services.

    • Shane Johnson Director Product Marketing MariaDB
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  • AI / ML and Space Exploration (NASA missions)

    15h00 - 15h30

    The majority of planetary missions return only one thing: data. As space exploration missions’ ambitions keeps evolving as well as the development of very mature instruments maximizing the value of each bit sent back to Earth, Science Autonomy -- the ability for science instruments to autonomously tune, operate, analyze, and direct themselves to optimize science return -- is necessary. Recent developments have demonstrated the tremendous potential of robotic explorers for planetary exploration and for other extreme environments. NASA believe that science autonomy has the potential to be as important as robotic autonomy (e.g., roving terrain) in improving the science potential of these missions because it directly optimizes the returned data. At NASA Goddard Space Flight center, we are developing a first step toward this vision: a ML approach for analyzing science data from the Mars Organic Molecule Analyzer (MOMA) instrument, which will land on Mars within the ExoMars rover Rosalind Franklin in 2023 to search for molecular biosignatures that might reveal signs of ancient martian life.

    • Victoria Da Poian Aerospace Engineer NASA
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  • Break & Networking

    15h30 - 16h00
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  • Data Virtualization - Unlocking Data – From Silos to Success?

    16h00 - 16h30

    Desjardins is the largest financial services cooperative in North America and a Canadian-wide financial services firm with divisions covering retail banking, insurance, real estate, and wealth management. This complex business structure in several highly regulated sectors creates a data environment that is composed of disparate data warehouses and data lakes. Desjardins found it difficult to physically combine and represent data across all divisions in a timely manner while respecting all the regulatory requirements.

    Jean-Marc Boivin, Chief Advisor, Data Technology Centre of Excellence at Desjardins, in conjunction with Vincent L’Archeveque of SimplicityBI will outline the situation, how Desjardins approached the problem, and then outline how this was resolved using a data virtualization approach to create a logical data fabric, alleviating the need to move data across divisions.

    • Vincent L’Archeveque Founder, Data Architect for BI and Analytics SimplicityBI
    • Jean-Marc Boivin Chief Advisor, Data Technology Centre of Excellence Desjardins
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  • Getting to Yes – What Investors Look for in Big Data & AI Startups

    16h30 - 17h00

    Everyone knows that early stage investors want to back great founders and ideas, but it’s difficult to anticipate precisely what will resonate with VC firms. Join this panel of tech investors as they talk through their process of evaluating a startup using AI and ML and the trends they are most interested in today. Topics to be discussed: Which interesting big data and AI trends are investors most excited about today? How should founders best communicate their startup vision to potential customers, VCs, and broader industry? What qualities they look for in founders? How do they evaluate the product and market? What are the sequence of events and asks when fundraising?

    • Ivy Nguyen Investor Point72 Ventures
    • Jamie Rosenblatt Principal Golden Ventures
    • John Cowgill Partner Costanoa Ventures
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