Israel Chen
Researcher, builder, and the first user of everything on this site.
ISRAEL CHEN received a Bachelor of Science in Computer Science, Bachelor of Applied Science in Supervision and Management, Master of Science in Software Engineering, and Master of Business Administration. He is currently pursuing a Master of Science in Computer Science with a specialization in artificial intelligence at the Georgia Institute of Technology, Atlanta, GA, USA.
What I am doing now
Publishing systematic reviews with IAMB.AI, and studying what changes when AI does more of the research.
IAMB.AI is an agentic AI platform for generating IEEE-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 IAMB.AI. 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.
IAMB.AI is invite-only while I dogfood it. Tell me what you want to research; the research cohort goes first.
