Akarsh Kumar

Contact

akarshkumar0101(at)gmail(dot)com

Bio
I'm a Ph.D. student at MIT CSAIL working with Phillip Isola.
I'm also a research intern at Sakana AI working with Yujin Tang and David Ha. I also collaborate with Ken Stanley.
My research is supported by the NSF GRFP!
Previously, I graduated from UT Austin where I worked with Peter Stone, Risto Miikkulainen, and Alexander Huth.

Research
I want to understand intelligence and all the different processes that emerge it.
More specifically, I'm interested in:

Applying principles from natural evolution and artificial life to create better AI systems.
Open-ended processes which keep creating "interesting" artifacts indefinitely.
Evolving intelligence from scratch, without the internet, like how natural evolution created us.

In practice, I'm espcially interested in meta-learning, RL, automatic environment generation, and multi-agent self-play.

Research

Questioning Representational Optimism in Deep Learning: The Fractured Entangled Representation Hypothesis

Akarsh Kumar, Jeff Clune, Joel Lehman, Kenneth O. Stanley

arXiv 2025

TLDR: We hypothesize that the standard paradigm of training networks today is producing spaghetti-like representations of it's (good) output behavior, leading to ineffective OOD generalization, creativity, and continual learning.

[Arxiv] [Code] [Tweet]

Automating the Search for Artificial Life with Foundation Models

Akarsh Kumar, Chris Lu, Louis Kirsch, Yujin Tang, Kenneth O. Stanley, Phillip Isola, David Ha

ALife Journal 2024

TLDR: ASAL is a new ALife paradigm using CLIP to search for (1) target, (2) open-ended, and (3) diverse simulations. ASAL helps us understand "life as it could be" in arbitrary artificial worlds.

[Web Paper] [Arxiv] [Blog] [Code] [Tweet]