Women in AI Virtual schedule

Catherine works passionately to provide senior executives with the hottest content and insights in the areas of Digital, Data, Analytics, Information, Business Development & Innovation. She hosts and moderates Corinium's largest events as well the Business of Data Podcast. She has a wealth of experience directing and designing Conferences, Bespoke Roundtables, Online events and more! Catherine is especially passionate about diversity, inclusion and accessibility work - and is an active ally and advocate for female and BAME leaders.

AI in the Financial Services Sector

AI has been disrupting every industry and has long since gone from an emerging trend to a pivotal foundational capability. In the coming years, financial service sector executives of all levels will need to understand how AI will impact their business, from understanding where the opportunities are to preemptively mitigating the well-known challenges impeding AI adoption and execution. This talk will begin by taking a quick look back in history to see how Canada's academic AI bench strength came to be and what advantages lie in the financial services sector. From there, it will outline key strategic machine learning opportunities before getting into the nitty-gritty impediments to execution that need to be overcome.

After completing a number of advance biomedical and mechanical engineering degrees, Paige decided to begin her career in management consulting. Working for McKinsey, she supported a number of multi-national financial institutions across a range of topics, from data strategies, to digital transformation, and even standing on multi-million dollar innovation centers. She's since accrued more than 10 granted patents (+13 pending) and continues to explore her various entrepreneurial endeavours, with the latest focused on clean river-run energy generation technologies.

Most recently, Paige left the Vector Institute for Artificial Intelligence, where she led several nation-wide engagements with Canada's largest financial institutions, consulting companies, regulators, and government agencies, to join TD's very own Layer 6 AI. At Layer 6, Paige is globally responsible for the end-to-end lifecycle of all Layer 6 use-cases across the bank.

Making Alexa more Knowledgeable

Would you like to understand the magic that happens in 1 second from the moment that you ask a question to Alexa to the moment it replies to you as if Alexa was a human? In this talk Saranya Govindan will go through cutting edge technologies in Artificial intelligence that are being developed in Alexa Research, Amazon to make a super complex product of automatic assistant using deep learning. After this talk you will know about concepts ranging from knowledge acquisition to question understanding and answering.

Saranya is an Applied Science Manager at Amazon. Previously, she was also a Machine learning Data Scientist at Tesco. She has an engineering background with 12 years of commercial experience working in the Retail and Insurance sectors and has held consulting and leadership roles in the Analytics space. Saranya is a graduate from Imperial College London and got her Masters in Business Analytics with a Research assistant scholarship. In her current role, she works on improving store space allocation and employs machine-learning techniques to solve business problems.

From POC to Multi-Million Dollar Investment: Rapid Scaling of AI Prototypes

A quick AI prototype is the best way to get buy-in for your great new concept! But after you have that green light from your enterprise, how do you scale? T-Mobile’s enterprise AI team began as a small, 12 week prototype – and now is a fully enterprise-essential team with multiple projects spanning business units and dozens of engineers. In this talk, Heather will guide us through the lessons she’s learned in her 4 years of experience designing prototypes, running POCs, and scaling successful experiments to create software that makes millions of real-time predictions a day.

Key Takeaways: • In agile POCs, people tend not to write logs – but they’re essential to iterating on your prototype at all. Logging must be MVP for AI prototypes.

• Design must be agile and run alongside dev teams. Agile design must be informed by data.

• Make your teams fully stacked – from analyst to DevOps engineer – to avoid wasting cycles coordinating with other teams for essential functions.

Heather Nolis is a founding member of the AI @ T-Mobile team, focusing the conversion of cutting-edge analyses to real-time, scalable data-driven products. She spends her time irl with her number-obsessed son Amber in rainy Seattle. You can find her @heatherklus on Twitter, where she talks about super sweet machine learning, data for good, and bad reality television.

Join a discussion group with speakers around the topic of "Advice for Navigating the World of AI". Ask your questions, share your thoughts and learn from the experiences of speakers and attendees alike.

Sidita is a seasoned Data, Analytics & AI leader with BSc and MSc degrees in Statistics from Western University and is an avid contributor and speaker in both the Data, Analytics and Artificial Intelligence (AI) Community. Currently Sidita holds the position of Associate Vice President, Analytics Strategy & Planning at TD Bank's Enterprise Data & Analytics team. Prior to that, Sidita joined TD from Bank of Montreal where she most recently lead a Data & Analytics teams for Wealth Management, as well as lead the creation of Enterprise AI, ML and Analytics COE to drive advanced analytics capabilities across the businesses. She has also held various D&A positions at both BMO and CIBC, where she focused on accelerating their analytics journeys and deploying analytics use cases to drive value for those organizations.

From POC to Multi-Million Dollar Investment: Rapid Scaling of AI Prototypes

A quick AI prototype is the best way to get buy-in for your great new concept! But after you have that green light from your enterprise, how do you scale? T-Mobile’s enterprise AI team began as a small, 12 week prototype – and now is a fully enterprise-essential team with multiple projects spanning business units and dozens of engineers. In this talk, Heather will guide us through the lessons she’s learned in her 4 years of experience designing prototypes, running POCs, and scaling successful experiments to create software that makes millions of real-time predictions a day.

Key Takeaways: • In agile POCs, people tend not to write logs – but they’re essential to iterating on your prototype at all. Logging must be MVP for AI prototypes.

• Design must be agile and run alongside dev teams. Agile design must be informed by data.

• Make your teams fully stacked – from analyst to DevOps engineer – to avoid wasting cycles coordinating with other teams for essential functions.

Heather Nolis is a founding member of the AI @ T-Mobile team, focusing the conversion of cutting-edge analyses to real-time, scalable data-driven products. She spends her time irl with her number-obsessed son Amber in rainy Seattle. You can find her @heatherklus on Twitter, where she talks about super sweet machine learning, data for good, and bad reality television.

Catherine works passionately to provide senior executives with the hottest content and insights in the areas of Digital, Data, Analytics, Information, Business Development & Innovation. She hosts and moderates Corinium's largest events as well the Business of Data Podcast. She has a wealth of experience directing and designing Conferences, Bespoke Roundtables, Online events and more! Catherine is especially passionate about diversity, inclusion and accessibility work - and is an active ally and advocate for female and BAME leaders.

The panel will focus on “The Future of AI and its Impact on the Talent Market” and cover areas such as: - What are some of the emerging trends in AI - Where do you see some of these emerging trends mostly impacting your business and clients/products - How do you envision that some of these changes will impact the future of work and experiences - What will be critical in our AI talent skill pool to stay up to date with these emerging trends - What are some of the complementary roles/skills that will be a great addition to an AI team as they shift into the next frontiers of AI

Anna Bethke is a Principal Data Scientist focused on fair, accountable, transparent, & explainable (FATE) AI in Salesforce’s Ethical AI Practice Team, collaborating with product and research teams to create AI responsibly and empower our customers to use it responsibly. They research and implement innovative techniques for assessing and mitigating bias and harm in AI. Anna received their MS and BS in Aerospace Engineering from the Massachusetts Institute of Technology concentrating on Human Factors Engineering. Anna was formerly the Head of AI for Social Good at Intel and previously worked at Facebook, MIT Lincoln Labs, Argonne National Labs, and Lab41.

Seasoned Data & Analytics executive who has managed significant national businesses within Financial Institutions. Over 20 years of Experience in leading and transforming large data and analytics teams. Highly strategic leader with proven ability to practically execute and deliver strong business results. Currently the Executive product owner of Data as a service for business segments over 800 colleagues in Canadian personal bank, America most convenient Bank, Business Bank, wealth and Insurance. A lifetime history of giving back to the community. Volunteer roles include Leading the TD Insurance Indigenous diversity pillar, senior leadership role for United Way Quebec, senior leadership in Women in leadership for Québec and an active influential speaker amongst several Montreal high schools, Cegep and Montréal University. Looking to expand governance contributions by serving organizations where skills, style and business experience can be leveraged. Sylvie holds a bachelor's degree in Mathematics, a master's degree in Statistics from Montreal University and a certificate of lean six sigma black belt for New York University.

Tatiana Zander is a Director of Technology Innovation, responsible for innovation and thought leadership across Ericsson North America. She drives and streamlines innovation and lab strategy across all operator and enterprise customers, while always looking for the next disruption. Tatiana began her career as a software developer and has worked with all Ericsson business areas since. Originally from Germany, she has had assignments in four continents. Tatiana earned a BSC in Scientific Programming from the University of Applied Sciences Aachen, MSC in Operations Research and an Executive MBA from Maastricht University. She currently serves on the Advisory Council of California State University East Bay. Outside of work, Tatiana is a former competitive gymnast and recently completed an Ironman.

I’m both the Emerging Technologies CEO at a London fashion based Research & Development company, Sophis Inc Ltd (t/a INRO London). I’m also the Director of Machine Learning & AI at our newly opened centre for Data, Technology & Innovation. I lead all technology initiatives within the business ranging from Machine Learning & AI applied research to leading Emerging technologies strategies at board level. Outside of my day job I’m a researcher within Machine Learning & AI, writing numerous papers and am frequently called upon to speak at some of the worlds largest technology summits, universities (on topics ranging from research level to careers guidance) and businesses to support their technology initiatives. I’ve also sat on numerous industry advisory boards to support development in STEM curriculum, namely around the Computing & Mathematical Sciences.

Join a 1-to-1 Speed Networking session to be randomly paired with others with a similar interest for short video calls to expand your network and connect with others.