Web presentation on Operationalizing Analytics

Presented by: Tim Trussel

Hosted By: Acadia Institute for Data Analytics , The Jodrey School of Computer Science

Abstract:

Through case study examples from Tim's experience with both large organizations and the startup / scale-up technology ecosystem, this talk will highlight the importance of the often overlooked (and interrelated) roles of Data Engineering, Development Operations, Cloud Architects and Site Reliability Engineers. While excitement only grows about AI and Data Science applications for organizations, "Operationalizing Analytics" explores the importance of thinking beyond the hype of building models to the detailed steps and considerations including: data and system architecture, model retraining & scoring, environment costing, lag, processing time, scalability, security, interpretability, and process integration.

About the presenter:

Tim is currently the COO at AIR Resilience Inc. leading an exciting startup B2B SaaS company in the vibrant mental fitness market. Prior to AIR, Tim held multiple leadership positions at Kinduct Technologies and SAS bringing his diverse experience and skills to foster business growth. His breadth of knowledge and personal strengths bring unique value as a business and technology leader. Specifically:

• He has fostered an innovative culture, leading teams both small and large in analytical adoption, software development, product expansion, and business strategy.
• He has a rare combination of technical, sales & marketing, and product management knowledge, including executive leadership positions as VP of Product & Technology and VP of Revenue.
• His successful project delivery and collaborations include some of North America’s largest companies and sports organizations, multiple funded grant applications, and multi-year product roadmap execution.
• He has professional experience on advisory boards and in entrepreneurial mentorship.

He looks forward to bringing his passion for strategic business growth to businesses within Atlantic Canada and beyond.

If you missed the talk, feel free to watch the recording here:

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Web Presentation on Machine Learning for Biodiversity

Presented by: Graham Taylor

Hosted By: Acadia Institute for Data Analytics, The Jodrey School of Computer Science

Abstract:

Up to 1M species face extinction in the next several decades, with biodiversity loss a major factor. In this talk, I will describe my team’s efforts to leverage advances in deep learning to monitor and improve biodiversity health. Our work is bolstered by the $24M University of Guelph-led BIOSCAN project, a global interdisciplinary effort to build a biodiversity observation system; and LIFEPLAN, a global biodiversity monitoring effort that collects data, including images, audio and DNA samples, from around 100 sites worldwide. Manual analysis of the data collected in these massive international biodiversity efforts are resource prohibitive and their success will depend on automating the analysis of images, sets, sequences, and graphs.

About the presenter:

Graham Taylor is a Canada Research Chair and Professor of Engineering at the University of Guelph. He co-directs the University of Guelph Centre for Advancing Responsible and Ethical AI and is the Research Director of the Vector Institute for AI. He has co-organized the annual CIFAR Deep Learning Summer School, and trained more than 80 students and researchers on AI-related projects. In 2016 he was named as one of 18 inaugural CIFAR Azrieli Global Scholars. In 2018 he was honoured as one of Canada's Top 40 under 40. In 2019 he was named a Canada CIFAR AI Chair. He spent 2018-2019 as a Visiting Faculty member at Google Brain, Montreal. He is the Academic Director of NextAI, a non-profit accelerator for AI-focused entrepreneurs.

If you missed the talk, feel free to watch the recording here:

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Web Presentation on Mobile personalization in gaming & social apps using federated ML Platform

Presented by: Rima Al Shikh

Hosted By: Acadia Institute for Data Analytics , The Jodrey School of Computer Science

Abstract:

Federated machine learning has the potential to revolutionize the field of user personalization. In this talk, the speaker will delve into the topic of on-edge federated ML and its many benefits, including increased privacy, improved security, and real-time performance. We will explore how a unique technology that Begin AI’s team launched in June 2022, holds great promise for the future of human-device interactions. The speaker, an innovator and a tech leader will highlight the challenges faced by traditional centralized approaches and demonstrate how on-edge federated ML can overcome them. She will provide valuable insights and a deeper understanding of the complex topic, making this talk a thought-provoking exploration of the exciting world of federated machine learning. Whether you are in the tech industry or simply have an interest in innovation, this talk is sure to captivate you. With the deep understanding, the speaker can afford on this topic, you'll be treated to a journey of discovery, exploring the power of AI.

About the presenter:

Rima Al Shikh is a successful tech innovator and entrepreneur. With over 15 years of experience, she has established herself as a respected leader in the tech community and an inspiration to many young entrepreneurs. Cofounding Nabbesh, Rima’s first startup, marked an early success and armed her with experience as a leader and an entrepreneur. She has since founded two other successful tech startups, including her current, Begin AI, which she founded in 2020 after relocating to Canada in 2018. As the CEO of Begin AI, Rima is leveraging the power of artificial intelligence to solve some of the world's most critical challenges, such as secure personalization and predicting user engagement through machine learning. Driven by her passion for innovation and entrepreneurial spirit, Rima is building not only a business but a technology that positively benefits humanity as a whole

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SEMINAR PRESENTATION

Friday, November 18th, 2022
2:30pm
Carnegie Hall 113

Lifelong Machine Learning and Reasoning

About the Presenters

Presenter: Danny Silver

Abstract:

Lifelong Machine Learning (or Continual Learning) considers intelligent systems that learn many tasks over a lifetime, consolidating the knowledge they have learned and transferring that knowledge to more accurately learn new tasks. This talk will review the basic concepts of Transfer Learning, Consolidation and Lifelong Machine Learning. We will show how deep learning has proven the value of developing internal representations and rich feature sets from unsupervised learning as well as supervised multiple task learning (MTL). We will review context-sensitive MTL and show how it can be used to develop deep Lifelong Machine Learning systems that can learn diverse families of functions and train architectures with multiple input/output modalities. Finally, we will discuss how Lifelong Machine Learning is providing insights into how to develop common knowledge representation for Learning to Reason.

About the presenter:

Danny is a Professor in and former Director of the Jodrey School of Computer Science, Acadia University, Wolfville, Nova Scotia. He is the founder and Director of the Acadia Institute for Data Analytics and leads the Lifelong Machine Learning and Reasoning research group at Acadia. He completed a Ph.D. in Computer Science from the University of Western Ontario, London, Ontario, in June, 2000. Danny’s research focuses on advanced methods of machine learning and their application in data analytics, intelligent agents and adaptive systems. He has authored over 70 refereed journal or conference papers, 38 industry project reports and delivered associated talks in Canada, USA, Mexico, Europe and China. He has received a number of awards; including the FLAIRS-2016 and CASCON-2017 best paper awards. From 2007-09, he was the President of the Canadian Society of Computational Studies of Intelligence (now the Canadian AI Association, or CAIAC), and was Past-President until 2013. In June, 2016, he received the CAIAC Distinguished Service Award and was made a CAIAC Fellow. In 2011 he received the Science Champion Award from the Nova Scotia Discovery Center for his work on youth robotics and the advancement of STEM education. And from 2014 to 2018 he was an Honorary Colonel in the RCAF attached to 415 Squadron of 14 Wing Greenwood, in Nova Scotia.