AI-Powered Design And Manufacturing For Embodied AI
Mechanical Engineering & Materials Science
Meets Artificial Intelligence
Meets Artificial Intelligence
My mission is to enable anyone to be able to design functional artifacts across scales and domains, and with a special emphasis on robotics and other cyberphysical machines. I want to empower novices and accelerate experts' workflows.
I research simulation methods, design algorithms, digital manufacturing processes, and methods for overcoming the sim-to-real gap, for inventing in both virtual and physical worlds. With the right tools, we can augment human creativity, advance more capable computer creativity, and build computational systems that work for everybody, not just a select few.
My work has been published at top venues and featured in popular science periodicals such as, well, Popular Science, and others like Scientific American, TechCrunch, and more. I am a recipient of the Unity Global Fellowship, the DARPA I2O Fellowship, the MIT Sandbox Innovation Fund, and a Harvard GRID $100K award.
Presently, I am a Postdoctoral Associate at Harvard University, where I work with Prof. Jennifer A. Lewis in the aptly named Lewis Lab and collaborate closely with Prof. Karen Liu at Stanford. I received my PhD from MIT's Computer Science and Artificial Intelligence Lab, where I was advised by Daniela Rus and Wojciech Matusik. During my PhD, I did two stints at Disney Research, Pittsburgh and Zürich. In Olden Days of Yore, I did my undergrad/Master's at Cornell.
I am on the academic job market and will be applying FA '23.
Feel free to get in touch!
(✈️ = Spiel's On Wheels, i.e. travel)
11/17/2023 -- Our new paper on differentiable visual computing is live, in Nature Machine Intelligence!
11/10/2023 -- Time Crystal has been accepted to Nature Futures. More details when it's in print!
✈️ 10/21/2023 -- Thank you to Maker Faire: Bay Area for hosting me for a talk about The Scion, and for helping to sell early editions!
10/17/2023 -- I finally updated my old forgotten website with a new website I'm sure to forget to update. Please bear with me as some content is still being added and some formatting may be adjusted.
Funding and Collaborations
Research Funders (They like the shoutout)
Generative yet optimal, fabricable, certifiable robot co-design
User-Centric AI-Powered Co-Design Algorithms
Digital Fabrication Powered By Physical Intelligence
Modeling For Design across Domains and Morphologies
When someone invents a novel device in the virtual world, it should just work in the physical world. How do we overcome the sim-to-real gap, not just for one robot, but for any robot?
How can we quantify and control uncertainty in design and manufacturing?
How do we marry analytical simulation with data-driven models, providing the best of both worlds?
This last part "closes the loop," allowing data from designs to improve and adapt modeling (and future designs) to novel domains.
▲ Building modular design technology stacks.
🤖 Methods that learn from the data they produce:
i.e. supervise on the simulator, not an external dataset.
🖱️ Keep the practitioner's wants and needs in mind:
Research is most useful when it is usable!
🤓 Make core research accessible through open-sourcing/
releasing what we can.