Liu Leqi

Family Name: Liu 刘, Given Name: Leqi 乐

Email: sn.suodc.tuamocce@ unscramble


Welcome! I am a postdoctoral researcher at Princeton Language and Intelligence, currently working on understanding and building large language models. In Fall 2024, I will join McCombs School of Business as an assistant professor, and will be a core member of the Machine Learning Laboratory at the University of Texas at Austin.

I am in the process of building the HUman-centered MAchine INtelligence (HUMAIN) Lab. The mission of the lab is to build controllable machine intelligence that serves humanity safely. Currently, the three main research pillars for the lab are:

  1. Understand the foundations of state-of-the-art machine intelligence. The ultimate goal is to use this understanding to build next-generation machine intelligence. For example, we hope to study why the current transformer-based LLMs are so powerful and use the findings as inspiration to design the next-generation LLMs so that they are more factual and reliable.
  2. Propose principled frameworks for developing human-centered machine learning. Here, focusing on particular machine learning applications that interact with humans (e.g., personalized recommender systems and decision-support systems), we study principled ways to model human preferences and behaviors and incorporate these models into the machine learning pipeline. For more details, please refer to Chapter 1 of my Ph.D. thesis.
  3. Evaluate and mediate the societal and economic impacts of large-scale machine learning systems. Our focus here is on machine learning systems—recommender systems and LLMs—that have been deployed to interact with millions of people. In addition to evaluating the impacts of these systems, we hope to develop toolkits to facilitate the implementation of public policies for these systems.

I am looking for motivated students who share similar research interests to join the lab. Please check out the lab website before reaching out!

Past Experience: I obtained my Ph.D. from the Machine Learning Department at Carnegie Mellon University in 2023, where I was advised by Zachary Lipton. During my Ph.D., I interned at Google DeepMind London in Summer 2022, working on human-centered mechanism design, and at Apple Siri in Summer 2019. I was an Open Philanthropy AI Fellow from 2020 to 2023.

My Bachelor’s degrees are in Computer Science from Bryn Mawr College and Mathematics from Haverford College. During my undergrad, I spent a wonderful semester at AIT-Budapest in Spring 2016.