Engineering the path
from idea to production.

Use printed geometry to automate the experiment.

The opportunity

Combination-therapeutic research requires testing how drugs interact across different concentrations. Manual pipette dosing adds repetitive work, while planar culture dishes offer a limited representation of a three-dimensional cellular environment.

My contribution

For Evol Sciences, I developed a microfabrication 3D printing system with 4 µm pixels, alongside biocompatible, low-cytotoxicity printing resins for the cell-culture application. The system enabled three-dimensional matrices for studying drug interactions in an environment intended to better reflect aspects of in-vivo conditions than a planar dish.

I also developed microfluidic structures that automatically generated drug-combination gradients in cell culture, replacing manual pipette dosing for that step of the experimental workflow.

Why it matters

The value of additive manufacturing was not simply making a small part. It was using precisely controlled geometry and suitable materials to reduce repetitive dosing work and expand the experimental workflow for combination therapeutics.

Accelerate the tooling behind the airframe.

The opportunity

For drone airframes, I examined thermoforming and compression molding of thermoplastic-impregnated carbon-fiber sheets as a route to producing shells in minutes. The production opportunity was compelling, but conventional aluminum tooling introduced substantial cost and lead time between design iterations.

My contribution

I identified the mold as the bottleneck and developed an approach combining SLA-defined tool geometry, ceramic backing, and a reusable steel frame. The current process targets a three-day fabrication cycle, with an optional metallized face for wear resistance and heat spreading.

The manufacturing strategy

Use additive manufacturing to make the tool quickly, then use compression molding to make the parts repeatedly. This preserves rapid design iteration while creating a route beyond direct-printed prototypes to scalable composite production.

Customization starts with manufacturable geometry.

“The output should be a design that can be made—not just a shape that looks convincing.”

The opportunity

AI can accelerate concept creation and customization. Its practical value grows when design freedom is guided by the material, process, and production requirements of the final product.

My approach

I build toward workflows that guide customers through intuitive product choices and translate those choices into parametrically controlled designs. Text-to-image, multi-image generation and editing, mesh generation, and AI-assisted CAD become stages in a connected development process.

My design philosophy is to begin with controllable parameters and manufacturing constraints. Tools such as nTop and Metafold are reference points for this approach; the objective is to connect topology and geometry control with rapid, application-specific customization.

Design for the next step

Constrain features such as wall thickness, clearances, material behavior, build orientation, and post-processing needs. Review the resulting geometry against the intended process so that each iteration moves toward a production-ready part and a credible path to higher volumes.