Sitemap
A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
Pages
Posts
Hello, world: writing math and code
Published:
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portfolio
EurekaClaw
Lead development of the EurekaClaw project: designed the frontend interface, coordinated open-source community contributions, and maintained the codebase for research and public use.
Web World Models (WWM)
A framework that generates unlimited context via LLMs in text/code environments without data storage. Collaboration with Princeton AI Lab.
TENG++: Boundary-Enhanced PINNs
Extended the Time-Evolving Natural Gradient framework with Dirichlet boundary constraints in Physics-Informed Neural Networks.
Predicting Text from Intracranial Neural Signals
CNN-Transformer decoder with RoPE embeddings for intracortical speech-to-text, achieving CER reduction from 0.234 to 0.1636.
Deep RL Algorithms in Cryptocurrency Trading
Off-policy actor-critic agents (DDPG, TD3, SAC) for ETH trading, with SAC achieving best returns.
publications
Web World Models
Published in arXiv preprint, 2025
A Web World Model framework that generates unlimited context via LLMs in text/code environments without data storage.
Recommended citation: Web World Models. arXiv:2512.23676, 2025.
Download Paper
TENG++: Time-Evolving Natural Gradient for Boundary-Enhanced PINNs
Published in arXiv preprint, 2025
Extended the TENG framework with Dirichlet boundary constraints in Physics-Informed Neural Networks.
Recommended citation: TENG++: Time-Evolving Natural Gradient for Boundary-Enhanced PINNs. arXiv:2512.15771, 2025.
Download Paper
Hallucination Detection and Evaluation of Large Language Models
Published in arXiv preprint, 2025
Built a KnowHalu-style hallucination evaluation pipeline with accelerated judging and improved summarization detection.
Recommended citation: Hallucination Detection and Evaluation of Large Language Models. arXiv:2512.22416, 2025.
Download Paper
talks
teaching
Reader: CS 51A, ECE 131A, CS M146
Reader, UCLA, 2023
Reader for the following courses at UCLA:
- CS 51A: Logic Design of Digital Systems
- ECE 131A: Probability Theory
- CS M146: Machine Learning
ENGR 96A: Machine Learning With Python
Learning Assistant, UCLA, Engineering, 2023
Learning Assistant for ENGR 96A: Machine Learning With Python, taught by Prof. Jacob Schmidt (Sep 2023 – Jun 2024).
ECE 132B: Data Communications and Telecommunication Networks
Teaching Assistant, UCLA, Electrical and Computer Engineering, 2025
Teaching Assistant for ECE 132B: Data Communications and Telecommunication Networks, taught by Prof. Izhak Rubin (Jan 2025 – Apr 2025).
ECE 241: Stochastic Process
Teaching Assistant, UCLA, Electrical and Computer Engineering, 2025
Teaching Assistant for ECE 241: Stochastic Process, taught by Prof. Lin Yang (Jan 2025 – Apr 2025).