Hi, I’m Hao-Yung Weng, an MSML (Master’s in Machine Learning) student at the Machine Learning Department, Carnegie Mellon University’s School of Computer Science. I’m also affiliated with the Robotics Institute, in Auton Lab, advised by Prof. Artur Dubrawski. My research focuses on natural language and speech processing, as well as large language models (LLMs). Lately, I’ve been working on LLM personalization and federated learning, aiming to enhance model adaptability while preserving privacy—a crucial challenge in deploying AI at scale.

Before joining CMU, I graduated as valedictorian and summa cum laude (top 1%) from National Taiwan University with a bachelor’s degree in computer science. While there, I had the privilege of working with Professor Yun-Nung Chen on natural language processing and transfer learning, and with Professor Hung-yi Lee on speech processing and parameter-efficient fine-tuning.

I have gained diverse industry experience. At Google, I developed a bug triage system that streamlined vendor collaboration under the Joint Development Manufacturer (JDM) model, cutting issue resolution time by 25%. At WorldQuant, as a quantitative research intern, I built mathematical models to predict equity market movements and implemented novel, profitable trading strategies.

In 2023, I was honored as one of Taiwan’s Outstanding Youth by the Ministry of Education.

Outside of my academic work, I’m a big coffee geek and write blog posts exploring the more technical, scientific, and probably nerdy sides of coffee brewing, like this one, where I evaluate Wet WDT, a technique that’s essentially stirring coffee with—well—acupuncture needles.

Cheers! Take care. Maybe give my favorite post-rock band a listen?