Yaoyao Liu

About

Yaoyao Liu is an assistant professor in the School of Information Sciences and the Coordinated Science Laboratory at the University of Illinois Urbana-Champaign. He is also affiliated with the Siebel School of Computing and Data Science and the Department of Electrical & Computer Engineering. His research lies at the intersection of computer vision and machine learning, with a special focus on building intelligent visual systems that are continual and data-efficient. His research interests include continual learning, few-shot learning, semi-supervised learning, generative models, 3D geometry models, and medical imaging.

Research topics

• Physics
• Electronic engineering
• Engineering
• Atmospheric sciences
• Geology
• Materials science
• Electrical engineering
• Optoelectronics
• Composite material
• Metallurgy

Selected publications

• Secrets of RLHF in Large Language Models Part II: Reward Modeling

  arXiv (Cornell University) · 2024-01-11 · 7 citations

  preprintOpen access

  Reinforcement Learning from Human Feedback (RLHF) has become a crucial technology for aligning language models with human values and intentions, enabling models to produce more helpful and harmless responses. Reward models are trained as proxies for human preferences to drive reinforcement learning optimization. While reward models are often considered central to achieving high performance, they face the following challenges in practical applications: (1) Incorrect and ambiguous preference pairs…

  PublisherOA PDFDOI

• A Transfer Learning Approach to Energy-Efficient Control of Small and Medium-Sized Commercial Buildings

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access1st authorCorresponding
  PublisherDOI

• Non-Obese Hepatic Steatosis Severity Prediction: Machine Learning Model Development and Validation (Preprint)

  Journal of Medical Internet Research · 2025-08-17

  articleOpen access

  <sec> <title>BACKGROUND</title> Non-obese individuals account for 40% of global steatotic liver disease (SLD) cases, yet lack dedicated targeted screening tools. Current ultrasound-based methods exhibit low detection rates for mild steatosis, delaying intervention. </sec> <sec> <title>OBJECTIVE</title> This study aimed to develop and validate a non-invasive, multi-class machine learning model using the Ultrasound Attenuation Parameter to predict hepatic steatosis severity grades (none/mild/moder…

  PublisherDOI

• Adaptive sparsening and smoothing of the treatment model for longitudinal causal inference using outcome-adaptive LASSO and marginal fused LASSO

  arXiv (Cornell University) · 2024-10-10

  preprintOpen access

  Causal variable selection in time-varying treatment settings is challenging due to evolving confounding effects. Existing methods mainly focus on time-fixed exposures and are not directly applicable to time-varying scenarios. We propose a novel two-step procedure for variable selection when modeling the treatment probability at each time point. We first introduce a novel approach to longitudinal confounder selection using a Longitudinal Outcome Adaptive LASSO (LOAL) that will data-adaptively sel…

  PublisherOA PDFDOI

• Online Heatmap Generation with Both High and Low Weights

  ACM eBooks · 2023-12-22

  book-chapterOpen access1st authorCorresponding

  Heatmap is a common geovisualization method that interpolates and visualizes a set of point observations on a map surface. Most of online web mapping libraries implement a one-pass heatmap algorithm using HTML5 canvas or WebGL for efficient heatmap generation. However, such implementation applies additive operations that accumulate the rendering of point weights on the map surface grid, making it inappropriate for visualizations that require the highlighting of both low and high weights. We intr…

  PublisherOA PDFDOI

Frequent coauthors

• Shaowen Wang

  University of Illinois Urbana-Champaign

  75 shared

• Anand Padmanabhan

  28 shared

• Wendy K. Tam Cho

  University of California, San Francisco

  22 shared

• Ian Gorton

  Northeastern University

  21 shared

• Hao Hu

  15 shared

• Jeff Terstriep

  National Center for Supercomputing Applications

  13 shared

• Hans H Stein

  University of Illinois Urbana-Champaign

  11 shared

• Liming Zhu

  Commonwealth Scientific and Industrial Research Organisation

  10 shared

Education

• ME, Computer Science

  Wuhan University

• PhD, Informatics

  University of Illinois at Urbana-Champaign

• BS, Computer Science

  Wuhan University

• MCS, Computer Science

  University of Iowa

Awards & honors

• Celebration of Excellence 2026
• Celebration of Excellence 2025
• Celebration of Excellence 2024
• Celebration of Excellence 2023
• Celebration of Excellence 2022

Similar researchers at University of Illinois Urbana-Champaign

• Jiawei Hanh-146
• Kaiyu Guanh-86
• ChengXiang Zhaih-83