Michael Poli
Founding Scientist at Liquid AI.
Computer Science Ph.D. Student at Stanford.
machine learning ∩ systems ∩ signal processing
Research:
I lead a research group at Liquid AI. We are building hardware-aware, custom and efficient AI systems at every scale, with a design theory for models grounded in classical first principles of dynamical systems, signal processing and numerical linear algebra. We are hiring exceptional researchers with diverse backgrounds (AI, systems, hardware, control theory etc), reach out if our mission resonates with you.
My interests are at the intersection of machine learning, systems and signal processing:
- Architectures for long context and new applications
T1, Hyena and HyenaDNA, StripedHyena, Evo (on the cover of Science!); - Automating and understanding the process of architecture design
Zoology, Mechanistic Architecture Design; Evolutionary Synthesis of Tailored Architectures (STAR) - Hybridization of methods from dynamical systems, signal processing, with learning
Hypersolvers, Differentiable Multiple Shooting; RTF - Efficient systems and algorithms for scaling and deployment on the edge
LaughingHyena;
Short bio:
I am a Founding Scientist at Liquid AI and a Ph.D. student in Computer Science at Stanford University. I am grateful to a long list of brilliant researchers and friends that have advised me through the years and (inexplicably) believe in my work:
Stefano Ermon, Chris Ré, Eric Horvitz, Bryan Wilder,
Seong Joon Oh, Animesh Garg, Ilija Ilievski, Jinkyoo Park, among others.
I am originally from Bologna, Italy, and I have had the wonderful opportunity to spend 5 fun years in Asia (China and South Korea).
My Chinese name is 宁致远.