Israel Chen
Researcher, builder, and the first user of everything on this site.
ISRAEL CHEN is an AI scientist, builder and founder. His Ph.D. research is weight-space programming, or as he puts it, reprogramming the AI brain: language models that read and write the weights of other models directly, repairing and building networks instead of training them, a path toward recursive self-improvement. His RebaseLoRA, a merge-and-refresh adapter procedure for continued pre-training, is an arXiv preprint (2026), and his PRISMA systematic review of TinyML, on efficient inference and on-device learning, is published in IEEE Access. The Israel Chen Corporation's technology is built on the same research he publishes.
He is an active Ph.D. student in computer science and a second-year law student specializing in AI law, intellectual property and patent law, focused on where AI meets each of them, from patents to the rights in music and songs. He holds a B.S. in Computer Science, a B.A.S. in Supervision and Management, an M.S. in Software Engineering and an MBA, and is pursuing an M.S. in Computer Science, specializing in artificial intelligence, at the Georgia Institute of Technology.
What I am doing now
Publishing systematic reviews with ICAI, and studying what changes when AI does more of the research.
ICAI is an agentic AI platform for generating publishable, PRISMA 2020-compliant systematic literature reviews.
The paper
Peer reviewed, published, and the reason this tool exists.
A Systematic Review of TinyML Techniques for Efficient Inference and On-Device Learning
IEEE Access, 2026
With Irin Jose, Nickolas Kenyeres and Kailey Cozart Quesada
DOI 10.1109/ACCESS.2026.3736856
TinyML is machine learning on microcontrollers: devices that cost a few dollars and run on almost no power. The review maps the techniques that make inference efficient on hardware that small, and the ones that let a model keep learning on the device itself.
Every stage of that review, from the protocol to the PRISMA checklist, is a stage in ICAI. Same rigor, a fraction of the time.
The plan
- research about researching research
- do research on ai research
- let the ai research the ai research
- profit
Straight from my bio. Step 0 is already running.
Be the one.
ICAI is invite-only while I dogfood it. Tell me what you want to research; the research cohort goes first.
