Human-centered AI-nerd
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Hi, I'm Rong 👋 I build AI agents and backend systems during my school work and intern. Currently studying MTech in software engineering at NUS in Singapore, after B.S. in computer science at KAIST. Nowadays, I'm using AI to explore unfamiliar fields, connect ideas, and turn real-world problems into practical solutions. I’m curious about what one person can learn, create, and accomplish with AI. These days, I'm building a coding agent from scratch, exploring reproducible quantitative research with TickWitness, and developing Lumen Next an auto-research agent. I enjoy learning about new domains, identifying meaningful problems, and using AI to turn ideas into something useful. |
Featured work |
Local Codex & Claude Code activity. Tokens include cached input; weekly averages use the last 28 days. Web chats and other devices are outside this snapshot. Counting method ↗
- Does Failure Feedback Direct Agent Self-Modification? · arXiv, Oct 2026
When does failure feedback help an agent repair itself, and does the improvement transfer? - Decomposition Buys Integrity, Not Yield · arXiv, Sep 2026
The trade-off between smaller contexts and information lost across task decomposition. - Prefix Sharing Is a Sorting Problem · arXiv, Sep 2026 · Code
Ordering reusable prompt chunks to reduce prefill computation.
- Label Adaptivity in Best-of-n Budget Selection · Zenodo, Oct 2026
Adaptive versus non-adaptive labelling under a limited correctness-label budget. - From Pointwise Queries to Population Probabilities: A Sharp Preservation Threshold · Zenodo, Sep 2026
When a restricted query interface preserves the difficulty of an inference problem. - Sharp Limits on Time-Reversal Detection in Binary Hidden Markov Models · Zenodo, Sep 2026
Sharp sample-complexity limits for detecting the direction of time.
All works above are preprints. Research notes & full records ↗


