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

Before CMU, I graduated as valedictorian and summa cum laude (top 1%) from National Taiwan University with a bachelor’s degree in computer science. 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 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, 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 academics, I’m a big coffee geek and write blog posts exploring the more technical, scientific, and occasionally 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?