Events for April 7, 2026

Sexton Campus, Halifax, Nova Scotia, Canada, B3J 1Z1

These are two NVIDIA workshops and attendees who have registered must attend both sessions, on March 31st and April 7<a href="http://th.Fundamentals" target="_blank" title="th.Fundamentals">th.Fundamentals of Deep Learning is a hands-on workshop designed by NVIDIA that introduces how businesses use AI, particularly deep learning, to solve real-world challenges across industries such as healthcare, retail, and automotive. Participants learn the fundamentals of training deep learning models, including techniques such as data augmentation and transfer learning. Through practical exercises and a final project, students build models from scratch and leverage pre-trained models, with all hands-on modules running on NVIDIA-hosted cloud resources. Those who complete the project and assessments receive an NVIDIA certificate. Space is limited to 40 <a href="http://participants.More" target="_blank" title="participants.More">participants.More information: <a href="https://www.nvidia.com/en-sg/training/instructor-led-workshops/fundamentals-of-deep-learning/Co-sponsored" target="_blank" title="https://www.nvidia.com/en-sg/training/instructor-led-workshops/fundamentals-of-deep-learning/Co-sponsored">https://www.nvidia.com/en-sg/training/instructor-led-workshops/fundamentals-of-deep-learning/Co-sponsored by: Faculty of Science and Technology, Humber Polytechnic / NVIDIASpeaker(s): Dr. Ernest Namdar, Ernest NamdarAgenda: Learning ObjectivesBy participating in this workshop, you’ll:- Learn the fundamental techniques and tools required to train a deep learning model- Gain experience with common deep learning data types and model architectures- Enhance datasets through data augmentation to improve model accuracy- Leverage transfer learning between models to achieve efficient results with less data and computation- Build confidence to take on your own project with a modern deep learning framework<a href="https://www.nvidia.com/content/dam/en-zz/Solutions/deep-learning/deep-learning-education/dli-fundamentals-of-deep-learning-1369828-r3-web.pdfRoom:" target="_blank" title="https://www.nvidia.com/content/dam/en-zz/Solutions/deep-learning/deep-learning-education/dli-fundamentals-of-deep-learning-1369828-r3-web.pdfRoom:">https://www.nvidia.com/content/dam/en-zz/Solutions/deep-learning/deep-learning-education/dli-fundamentals-of-deep-learning-1369828-r3-web.pdfRoom: J134-NORTH BUILDING, 205 Humber College Blvd, 1502, Toronto, Ontario, Canada, M9W 5L7

Fanshawe College students have the opportunity to attend a guided tour of Leggett & Platt, a global leader in engineered components and products that serve a wide range of industries, including bedding, furniture, automotive, and aerospace. The tour will provide students with insight into advanced manufacturing processes, innovative product development, and career opportunities within a multinational organization. Please note that students are responsible for arranging their own transportation to and from the Leggett & Platt facility, located at 459 Industrial Rd, London, ON N5V 3<a href="http://E5.Leggett" target="_blank" title="E5.Leggett">E5.Leggett & Platt has confirmed that they're seeking Fanshawe College students to fill co-op positions this upcoming <a href="http://term.IF" target="_blank" title="term.IF">term.IF YOU REGISTER FOR THIS EVENT AND CAN NO LONGER ATTEND, PLEASE UNREGISTER SO OTHER STUDENTS HAVE THE OPPORTUNITY TO <a href="http://PARTICIPATE.PPE" target="_blank" title="PARTICIPATE.PPE">PARTICIPATE.PPE REQUIRED: SAFETY GLASSES & SAFETY SHOESCo-sponsored by: Leggett & Platt459 Industrial Rd, London, Ontario, Canada, N5V 3E5

ABSTRACT3D perception, the ability to perceive depth and spatial relationships in the world, is fundamental to human cognition and holds immense potential across various sensing domains including robots and intelligent vehicles. The emergence of deep learning-based techniques offers a compellingalternative, potentially enabling 3D vision from monocular camera inputs without additional hardware <a href="http://modifications.This" target="_blank" title="modifications.This">modifications.This talk will delve into the principles and applications of traditional 3D sensing and computer vision methods. Subsequently, we will introduce predictive 3D sensing based on 2D cameras that use machine learning to generate 3D sensing, covering fundamental concepts, common architectures, and training data requirements. We will use intelligent vehicles to illustrate the predictive 3D vision concept including simultaneous localization and mapping (SLAM) and obstacle detection for <a href="http://illustrations.Speaker:" target="_blank" title="illustrations.Speaker:">illustrations.Speaker: Henry Leung, Fellow, IEEE, Professor, University of Calgary, CanadaBio:Henry Leung is the Schulich Industrial Chair Professor of the Department of Electrical and Software Engineering of the University of Calgary. Before joining the University of Calgary, he was with the Department of National Defence (DND) of Canada as a defence scientist. Hiscurrent research interests include information fusion, machine learning, IoT, data analytics, robotics, signal, and image processing. He has published more than 400 journal papers and 300 conference papers. He is an associate editor of various journals such as Scientific Reports, EEESystem, Man, Cybernetic Letters, and Journal of Sensors. He is the editor of the Springer book series on “Information Fusion and Data Science”. He is a Fellow of IEEE, SPIE, Engineering Institute of Canada (EIC), Canadian Academy of Engineering (CAE) and Royal Society of Canada (RSC).Room: Rm MA222, Sexton Campus, Halifax, Nova Scotia, Canada, B3J0H4

IEEE North Saskatchewan Section Meeting - April, 202657 Campus Dr, Saskatoon, Saskatchewan, Canada, S7N 5A9, Virtual: https://events.vtools.ieee.org/m/544433

ABSTRACTArtificial intelligence (AI) has become a foundational technology for diverse engineering disciplines. This talk discusses AI Engineering, focusing on the integration of machine learning (ML), deep learning (DL), and large language models (LLMs) into engineering research and system design. The presentation highlights how AI enables new capabilities in electrical engineering (wireless communications), computer engineering (intelligent systems), and biomedical engineering (AI medicine). Selected research examples illustrate the application of AI techniques to problems such as signal classification, system optimization, and multimodal data analysis. In addition, the talk discusses research methodology and technical paper writing, with emphasis on developing high-impact survey papers and comparative-study <a href="http://papers.Co-sponsored" target="_blank" title="papers.Co-sponsored">papers.Co-sponsored by: Gunes Karabulut KurtSpeaker(s): Dr. Yu-Dong Yao, Room: EV001-162, 1515 Ste. Catherine West (corner with Guy St.), MONTREAL, Quebec, Canada, H3G 1M8