8:30 am Breakfast & Networking

9:00 am Chair’s Opening Remarks

Harnessing Machine Learning & AI

9:10 am Developing a Data Collection & Governance Strategy to Prepare for Machine Learning & AI in Computational Design

  • Sean Page Partner, Computational Designer, Architect, RDG Planning & Design


  • Going beyond the collection of data by establishing a well-defined data governance team that has a clear understanding of your data strategy
  • Discussing the creation of a system that can help categorize data and make it available at the right time
  • Leveraging data in order to create more meaningful and easier design work by having a digital reference point allowing for coordination between past and current projects

9:50 am Case Study: Identifying Use Cases for Machine Learning & AI to Maximize Value in the Design Process


  • Highlighting where the current opportunities for machine learning & AI are in the context of computational design
  • Discussing what the data sources and requirements are for an effective integration of machine learning & AI within design processes
  • Leveraging institutional knowledge to maximize the usability of internal resources
  • Evaluating the benefits of open data and deciding what partners should have access to it

The Integration of Workflows

10:30 am Ensuring Quality Assurance of Models Generated through Computation to Secure High-Performance Consistency

  • KiSeok Jeon Vice President & Director - Digital Transformation, STV Inc


  • Understanding when and how quality assurance should be done in order to minimize the risk of computational errors
  • Developing quality assurance mechanisms for non-experts in computation to be able to easily assess their digital outputs
  • Highlighting the importance of time-effective quality assurance in order to maintain the time-saving characteristic of computation tools
  • Feeding errors back into the development of computational tools for increased future performance

11:10 am Morning Refreshments

11:40 am Addressing Barriers in the Current Contract Environment to Data Sharing & Maximizing the Benefits of Computational Design Across Projects


  • Overcoming concerns around data ownership and commercial IP
  • Differentiating between project delivery methods and the level of information sharing that each of these allows
  • Discussing the additional clauses that can be included in order to enhance data sharing and support of computational design

12:20 pm Case Study: Unveiling How Contractors are Using Parametric Design Outputs to Enhance Time & Cost Certainty in Preconstruction


  • Discussing how to improve integration of contractors in design models to access the right data and enable iterative design
  • Understanding how knowledge of simple parametrics can help translate into a more detailed estimate without full design development
  • Using parametric rules to automate basic technical detailing to reduce time wasted on monotonous manual design input

1:00 pm Networking Lunch

2:00 pm Addressing the Feasibility of Design Workflows for Fabrication, On- Site & Supply Chain Optimization


  • Navigating the design space between design parameters, cost, and quality to ensure design fidelity is executed
  • Leveraging contractor knowledge and computational tools early on towards optimizing the design
  • Using BIM to enhance collaboration and review design requirements on an ongoing basis

2:40 pm Case Study: Leveraging Computational Design & Modular Construction to Enhance Project Delivery


  • Discussing the ways in which modular construction enables computational design for better overall project performance
  • Discussing the opportunities for deploying computational design for modular construction
  • Understanding the practical usability of a computational design tool built for modular ductwork

3:20 pm Chair’s Closing Remarks

3:30 pm End of Conference