
I am a co-founder / CEO of Outerport. Our mission is to help people bring physical products, technologies, and inventions into the world, from the initial concept all the way to manufacturing, with lower risk.
As a first step, we offer a platform to build AI agents, as well as built-in tools to help design engineers and manufacturing operators make better-informed decisions by making sense of the technical documents (datasheets, BOMs, drawings, etc) that sit between a concept and reality.
We don't just want to make work faster. We aspire to make new product cycles faster and lower risk. Our approach is to simulate the end-to-end engineering flow with a probabilistic model that combines engineering knowledge with financial models for the first time, so that the cost of design decisions can be predicted and catastrophic manufacturing and supply chain issues can be caught early in the cycle.
I left NVIDIA since I realized that what I wanted to do in life was help people create new things and wanted to do this in the most direct way possible. To find the most effective way to do this, I first explored by doing consulting and freelance work across animation, creative studios, publishers, construction, etc.
I kept seeing the same problem: the path from concept to product (whether it was merchandise or animation or a building) was full of costly, avoidable surprises. Eventually founded a company, but spent a while building ML infrastructure and document intelligence tools to build foundational technology for our real focus.
Joined NVIDIA full-time as a Research Scientist, officially in the New Experiences Research Group, but collaborating a lot with the Spatial Intelligence Lab. I focused on AI for 3D data, exploring how machines could better understand the geometry behind physical objects. I published over 10 research works with over 4500 citations (in top venues like CVPR, SIGGRAPH).
Concurrently, I also did a PhD at the University of Toronto, but I went on leave to start a company. Supervised by my amazing advisors, Sanja Fidler and Alec Jacobson.
Earned a bachelors from the University of Waterloo with a major in computer science. Took a whole lot of mechatronics courses. Spent my out-of-school hours building autonomous driving vehicles, starting in hardware systems engineering and later led the entire software division.
Did a couple of internships: Tulip Interfaces (which works on software that helps factories run their operations), and NVIDIA doing hardware-software integration for autonomous vehicles. Later did research at NVIDIA and Preferred Networks (in Tokyo!).
Started building robots — first in design, then manufacturing / fabrication, and then was the leader driving around town doing procurement, operating CNC mills, building schedules, and whatever needed to be done.
Born in Oregon, the land of semiconductor manufacturing. Growing up around Japanese technology and culture was a source of pride as an immigrant child. Influenced by biographies of Edison and Metal Gear Solid, learned the good and bad sides of technology. Learned to program and do 3D modeling. Aspired to invent technologies (especially robots) that make the world a better place.
Publications

Eurographics 2025
FastAtlas: Real-Time Compact Atlases for Texture Space Shading
Nicholas Vining, Zander Majercik, Floria Gu, Towaki Takikawa, Ty Trusty, Paul Lalonde, Morgan McGuire, Alla Sheffer
GPU-based atlas packing for real-time texture space rendering.

arXiv 2024
A LoRA is Worth a Thousand Pictures
Chenxi Liu, Towaki Takikawa, Alec Jacobson
LoRAs > embeddings for retrieval and clustering.

CVPR 2024
What You See is What You GAN: Rendering Every Pixel for High-Fidelity Geometry in 3D GANs
Alex Trevithick, Matthew Chan, Towaki Takikawa, Umar Iqbal, Shalini De Mello, Manmohan Chandraker, Ravi Ramamoorthi, Koki Nagano
Adaptive sampling in rendering = higher fidelity geometry.

SIGGRAPH Asia 2023
Compact Neural Graphics Primitives with Learned Hash Probing
Towaki Takikawa, Thomas Müller, Merlin Nimier-David, Alex Evans, Sanja Fidler, Alec Jacobson, Alexander Keller
Learned hash probing + hash tables = more compression & faster.

ICCV 2023
ATT3D: Amortized Text-To-3D Object Synthesis
Jonathan Lorraine, Kevin Xie, Xiaohui Zeng, Chen-Hsuan Lin, Towaki Takikawa, Nicholas Sharp, Tsung-Yi Lin, Ming-Yu Liu, Sanja Fidler, James Lucas
Optimize 3D generation over more prompts -> faster convergence.

CVPR 2023
⭐ Highlight (Top 2%)
Magic3D: High-Resolution Text-to-3D Content Creation
Chen-Hsuan Lin*, Jun Gao*, Luming Tang*, Towaki Takikawa*, Xiaohui Zeng*, Xun Huang, Karsten Kreis, Sanja Fidler, Ming-Yu Liu, Tsung-Yi Lin
Scaling up 3D generation with smarter data structures.

SIGGRAPH North America 2022
Variable Bitrate Neural Fields
Towaki Takikawa, Alex Evans, Jonathan Tremblay, Thomas Müller, Morgan McGuire, Alec Jacobson, Sanja Fidler
Learned indexing = more compressive than hash tables and grids.

EG / CGF 2022
Neural Fields in Visual Computing and Beyond
Yiheng Xie, Towaki Takikawa, Shunsuke Saito, Or Litany, Shiqin Yan, Numair Khan, Federico Tombari, James Tompkin, Vincent Sitzmann, Srinath Sridhar
Survey of representing vector fields with neural networks.

Tech Report 2022
RTMV: A Ray-Traced Multi-View Synthetic Dataset for Novel View Synthesis
Jonathan Tremblay, Moustafa Meshry, Alex Evans, Jan Kautz, Alexander Keller, Sameh Khamis, Charles Loop, Nathan Morrical, Thomas Müller, Koki Nagano, Towaki Takikawa, Stan Birchfield
Really big dataset of synthetic multi-view images.

CVPR 2021
⭐ Oral Presentation (Top 4%)
Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Shapes
Towaki Takikawa*, Joey Litalien*, Kangxue Yin, Karsten Kreis, Charles Loop, Derek Nowrouzezahrai, Alec Jacobson, Morgan McGuire, Sanja Fidler
Differentiable data structures + neural fields + GPU programming = fast.
Portfolio



Fun Things
- 2 themes in my life have always been art and machines. Computer graphics is a good medium between them.
- Outside of art and machines, I enjoy basketball, soccer, football, boxing, violin, and guitar.


