
I am a co-founder / CEO of Outerport. Our mission is to build AI that can design, engineer and optimize advanced manufacturing processes and industrial equipment.
We do so through an AI process engineering agent that can read engineering diagrams, generate designs, run simulations, and optimize design parameters.We also build AI foundation models trained on physical equipment data that can optimize processes 100x better than existing methods.
We are proud to be working with some of the world's most important companies in chemicals, semiconductor equipment, materials, EPC, and heavy industries.
Joined NVIDIA full-time as a Research Scientist in the Hyperscale Graphics Systems Group, focusing on fundamental research on simulation technologies. In particular I focused on how to effectively represent the geometry behind physical objects as data. 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.


