Architecture Introduction for AS BIM In Practice REVIT– Hanyi

Yi Han (he/him), Pronouns: Yee Han

I chose architecture for three reasons:

First, I was inspired by documentaries I watched as a child—drawn to the way architecture carries history and shapes the world. It opened my eyes to its power as a medium of change.

Second, during my undergraduate study in civil engineering, I realized how limited structural design felt. As engineers, we are often tasked with ensuring safety and feasibility—merely “patching” existing design intentions rather than originating them. I found that passive role unsatisfying. I wanted to engage with the origin of form and logic, not just repair its consequences.

Third, structural design—especially at its routine and rule-based levels—is already being automated. Industrial software has replaced much of the calculation and verification work. In the era of AI, this trend will only accelerate: the more standardized and interpretable a system is, the more easily it can be replaced. What remains difficult to automate is design at the edge—where structure negotiates with form, where ambiguity and intention need to be interpreted. That space is shrinking. To stay relevant, I knew I had to move from solving predefined problems to shaping the questions themselves.

So I chose architecture not to avoid computation or engineering, but to confront both—at the origin point where design logic, meaning, and narrative emerge.

I first used Revit during an undergraduate competition on supertall building design. We used a structural analysis plugin based on Revit for modeling and documentation. That experience made me realize that Revit is actually a highly parametric system.Rhino.Inside gave me a glimpse of the differences between Grasshopper and Revit. Although both are parametric, Rhino.Inside seems to act as a kind of translator between them. I don’t fully understand it yet, but I’m interested.

My thesis is about using language commands to control parametric point clouds, rendered and interacted with in real time in Unreal Engine. I’m trying to build a pipeline that goes: language → geometry → engine → feedback environment. So I hope this course helps me better understand how parametric tools relate to each other—though honestly, it might already be too late but it is still good to know.

Marcos Novak and Carlo Scarpa.

I don’t confine myself to a single post-graduation path—whether that means practicing architectural design, building interactive systems, or working within the AIGC ecosystem.

What matters more to me is whether the work is technically meaningful, deeply human, and helps me better understand how the world operates.

At the same time, I recognize the importance of gaining real-world engineering or production experience early on. That’s why I’m not aiming for a specific job title right away. My priority is to position myself in environments that challenge and inform the systems I want to build.

Classical Chinese Literature – Non-linear narrative, indirect expression, and rhythm-based logic; a unique system of meaning construction.

Simulation & Management Games – Studying feedback loops, system behavior, and design as real-time governance. (e.g. Paradox Interactive games)

Artificial Intelligence.

I don't have pets, but I’ve been around two border collies named Nick and Wink for a while.

If I choose to work after graduation and want to pursue a career at the intersection of AI and architecture, which type of environment would be most suitable?Would joining a game company or an AI-focused tech company in the AEC industry bring me closer to that goal than working in a traditional architecture firm? Or would it be more practical to first gain experience within the architecture profession before shifting toward AI-driven systems?

Money is fog—an uneditable parametric interface.

It appears to be an equivalent of resources, but in reality, it acts as an API token to a power system, dynamically issued through sovereign credit protocols.

It dissolves the physical and social logic of resources, keeping participants trapped within the UI layer of fog—chasing constantly updated but structurally undefined permission variables.

The real price of resources has been formatted by a suite of complex, seemingly neutral algorithms—detaching value from both material reality and social meaning.