Interview: Jason Wheeler , Design Technology Specialist – Computational Design, CallisonRTKL

  1. Q) Computation seems integral to the work that CallisonRTKL does, and a critical differentiator to other design firms as well. Could you give a couple of examples on how CallisonRTKL works differently to integrate computation into every day work?

At CallisonRTKL, we invest a lot into “computational thinking.”  We’ve been creating a community on how to think computationally. This enables us to have constructive conversations around “computational doing,” where we begin to construct scripts and developable workflows that impact our day-to-day.

For example, we conduct monthly all-hands webinars to share concepts and ideas, some more in-depth than others, but each one reveals a relationship to computational design. It’s these relationships that spark ideas and collaborations, which, eventually, turn into daily practice. In this respect, computational design becomes integrated into everyday work through the thought and questioning of how and what people are currently working on. How can do this become faster, better, more well informed, etc.

One of our webinars on documentation and Dynamo set off a discussion with a team from another office about the workflow. The team was renumbering the rooms in a large multi-building project. The conversation led them to a leaner, more efficient workflow. But, it didn’t stop there, they became more active in computational thinking and engaged our Design Technology Group regarding how these types of processes can help them in other areas of different projects. Again, once it gets into our circulatory system, this type of thinking doesn’t stop. The team shared their knowledge with the rest of their office and conversations began with other teams as well.

  1. Q) What do you see as the biggest challenge facing the wider adoption of computational design? Why isn’t it already as widely adopted as BIM?

Computational design is more of an abstract concept than BIM, so it takes more cultural adoption—more an approach than a tool. Building Information Modeling is pretty straightforward.

What does BIM give you?  BIM gives you information and data about your building as your modelling it, while computational design can give you a façade. Computational design can give you a building mass, pattern and texture. That’s a pretty big box of tools and, well, not really a box either. It’s hard to adopt something that isn’t so easy to pin down as black or white. There is a lot of grey area that surrounds computational design, and that’s part of what makes it so compelling.

The adoption of computational design in the AEC industry is already happening at a larger scale. It’s evident in company’s having positions such as my own. It’s evident in more conferences such as this one. It’s evident in the fact that software companies such as Autodesk and McNeel have started to fully integrate visual programming past the status of an add-on. The biggest challenge now for the industry is to dig deeper into the possibilities of using computational design. To get past the notion that it is just complex geometries or automating tasks. How can it help us to become better designers?  How can it provide us another canvas to express our thoughts and inquiries into design?


  1. Q) In your experience, what is the most common mistake that design firms make when leveraging computation for the first time?

Top down implementation. In my experience it rarely works. People need to experience it, sample it, before they buy into it. You can’t come into a project saying, “We are going to use computational design on this project,” as if you are sprinkling pixie dust on something.  It just doesn’t work that way. It needs to come about as the result of a problem that must be resolved.

There’s a different thought process that comes about when you are thinking about a design problem computationally—it’s integrative or organic, not additive. Getting team members to explore these thoughts naturally first always seems to work better than to push it onto them. The ones who are usually pushing it from the top down are usually the ones who don’t really understand what computational design really is or how it works.


  1. Q) What is the most convincing example you have to prove the value and ROI in computational design? Do you have any projects where design optimization, cost, speed or some other metrics has been measurably improved?


We’ve had many projects where scripts and workflows have saved hundreds of billable hours, led to discoveries that wouldn’t have been seen otherwise, provided us with more design time, etc. One example that comes to mind is a workflow using the clash detection data from Navisworks to be revisualized in Revit. This workflow had saved us time within the moment by clearly seeing our clashes in 3D with all other contextual systems that surrounded it. It also saved us from future problems by visualizing any further clashes that would have occurred while moving objects blindly to resolve that current clash.

The real hidden value that is of more interest to me, though, is the adoption of computational thinking and workflows by different teams and peers. The spread of knowledge and increase in the number of people inquiring about computational methods signals to me that CallisonRTKL is becoming more informed and conscious of the current movement.


  1. Q) Do you believe the AEC industry can benefit from collaboration as a way to enable mass adoption of computation? Are there any examples of successful collaborative projects or platforms where designers have shared tools, techniques or training methods?

As I said, I already feel that the AEC industry is adopting computational design on a large scale. I enjoy seeing this, but sometimes worry that those interested in “jumping on the train” will derail the conversation and see it as a simple automation tool.

The community is a largely open source one. A lot of us from different firms, different industries and different backgrounds find each other on various forums and blog sites to exchange information and thoughts. All dedicated to furthering the knowledge and use around computational design.

  1. Q) The advancement of computation is clearly linked to technology, such as the development of design software. What do you think is the next big technological leap that we should be planning for? What do you envision computational design to have the potential to achieve?

The next wave has already begun; that’s evident by all the recent clamour and investigation around machine learning techniques within the AEC industry. We as an industry have already found that data is king. This has led to a mass collection of data—data on all sorts of things from restroom count and location to Revit errors to clicks on a screen, etc. All this data has given us ways to see and understand relationships and value that we likely wouldn’t have seen otherwise, but now there seems to be a larger interest in “what more can our data do for us.”  These types of inquiries are what will drive this wave into machine learning.

  1. Q) What are you hoping to achieve from attending and presenting at Advancing Computational Building Design 2018?

I am very excited to be attending and presenting at the Advancing Computational Building Design conference this year. I’m most interested in learning. Just very eager to see and hear what everyone else is up to. Being able to not only attend the presentations but to be able to have some time for one-on-one and small group conversations. It’s up to us to steer this ship and define how computational design will engage and affect our industry, so for us all to be communicating about it and reacting to one another is key to how I see this evolving productively.

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