Nov. 6 - 8 2023
In-person + Virtual

About the Conference

DIET23 focuses on how companies, academics, and governments are using and planning to use innovative technologies and methodologies in nuclear energy, medicine, regulation and more. Disruptive, Innovative, and Emerging Technologies, such as Artificial Intelligence, Machine Learning, Data Analysis, Big Data, and Digital Twins, are already being used to obtain new insight, perform analysis more efficiently and more accurately, be more sustainable and improve safety. Other technologies such as Adaptive Manufacturing, Digital Twins and Virtual Reality are being actively explored and implemented by those involved in nuclear activities and research.
This international conference is seeking presentations from individuals, organizations and academia pertinent to these and other innovation technologies either deployed or being considered for deployment in the full spectrum of nuclear related activities and research. Authors require to only prepare a presentation.

Topics and Themes

Innovation has been the key to the success of nuclear for the past 60 years and more collaboration is needed to meet the challenges it faces.
DIET23 provides a forum for this collaboration through exchanging views, ideas and information.
In keeping with this vision, and to help direct the development of the conference program, the theme of the conference is:
DIET 2023: Innovation Unleashed


Topics for the plenary and technical session include:
  • Data Analysis, innovative approaches/methodologies
  • Artificial Intelligence and Machine Learning
  • Regulatory frameworks
  • Big Data
  • Digital Twins
  • Virtual Reality
  • Robotics
  • Nano-technology
  • Fusion
  • Addictive Manufacturing
  • And more
Join us and share in latest knowledge and experiences in adopting innovative ideas, methodologies, and algorithms.

New This Year!

You told us the one change you most wanted to see in 2023 was the opportunity to network in person. We heard you, and this year’s conference will be a hybrid of in-person and online events.
The first day of the conference, November 6, will be in-person in downtown Toronto (location TBA). The last two days, November 7 and 8, will be entirely online.
Modern Scientific Computing – Kitting Your Stack
As an individual contributor, you may be interested to support your outputs with the latest analytic techniques and being the enterprising individual that you are… you have successfully pitched your employer to provide you with the time and money required to investigate opportunities. But where do you begin spending the valuable resources you’ve been allocated?  How do you set yourself, and your organization, up for success?
With the proliferation of options in terms of hardware, software, workflow, and methodology, it is difficult to understand what choices make sense.
This workshop introduces some of the most impactful stack components currently available to the practitioner. The discussion, intended to enable good choices in an overwhelmingly complex decision space, will highlight the hardware, software, development tools, workflows, and resources found on some of the most artificially intelligent desktops in the world.
If you are in your first epochs and learning an optimal path from online tutorial to online application… this very practical nuts and bolts discussion may be of use to you.
Workshop Overview
  • A high-level history of relevant methods, hardware, and software
  • Hardware CPUs, GPUs, RAM, and disks
  • Software operating systems, languages, libraries, and frameworks
  • Methods old and new
  • Supporting tools – IDEs, editors, code versioning, and package managers
  • Workflows and stacks – putting it all together
  • Advanced next-level use-cases
  • Resources
For more information, please contact:
1. Nick Torenvliet at NICK.TORENVLIET@brucepower.com
2. Aleem Juma at aleem.juma@opg.com

Machine Learning Tutorial

An easy-to-follow demo of computer vision machine learning using Python and Tensorflow.
This workshop requires some prior Python programming experience, but those without can still follow the machine learning training and inference process.
In this workshop you’ll see how to design, define, train, and use a Tensorflow model to identify different types of clothing, using the “Fashion MNIST” dataset. We will start with the basic notebook from the Tensorflow examples, then build on it, time permitting, by:
– Exploring misclassifications,
– Improving the model design,
– Reviewing overfitting, and
– Monitoring model training.
For more information, please contact Aleem Juma at aleem.juma@opg.com
This year our conference program is presenting three full days including a new vendor discussion section.
The conference will provide invaluable opportunities for networking, professional development, exchanging ideas, technical discussions, and updates on the AI/ML-based implementations and ongoing efforts in nuclear programs.
Our speakers play a large role in the success of our conference annually, and this year will not be any different. Becoming a speaker in the vendor discussion section gives you access to our top-tier industry attendees from Canada and visibility to your organization.
To learn more about our current opportunities and to get your organization in front of who matters in the industry, please email Nazgol Shahbandi at nazgol.shahbandi@opg.com

Registration Will Be Open Soon!

If not attending the first day in person (two-day virtual only on Nov 7 to 8):
Before September 30th 
After September 30th 
Students in Good Standing 
If attending both the first day in-person and the two-day virtual (Full Conference Nov 6 to 8):
Before September 30th 
After September 30th 
Students in Good Standing 
Early Bird Date: September 30th, 2023

Organizing Committee

What Theme Say

Read what the previous attendees had to say !

Contact Us

If you need assistance please contact:

1. Moe Fadaee: moe.fadaee@cns-snc.ca

2. Kelly Chu: kellychu.cns@gmail.com

3. Vibhuti Mallick: vibhutimullick@gmail.com

4. Elmir Lekovic (CNS Office): cns_office@cns-snc.ca

  • DATE

    Nov. 6 - 8 2023

    In-person + Virtual
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