Portrait of Xin Liu
Leadership

Xin Liu

Professor of Computer Science, UC Davis

Co-PI and Co-Lead of Use-Inspired and Foundational AI Cluster

LinkedIn↗liu@cs.ucdavis.edu↗Website↗

Xin Liu is a Computer Science Professor at the University of California, Davis. Before joining UC Davis, she was a postdoctoral research associate in the Coordinated Science Laboratory at UIUC. During 2012-2014, she took a leave of absence and was with Microsoft Research Asia.

Her current research interests fall in the general areas of machine learning algorithm development and machine learning applications in human and animal healthcare, food systems, and communication networks. Her research on networking includes cellular networks, cognitive radio networks, wireless sensor networks, network information theory, network security, and IoT systems.

Xin is an IEEE Fellow. She received the Computer Networks Journal Best Paper of Year award in 2003 for her work on opportunistic scheduling. In 2005, she received the NSF CAREER award for her research on Smart-Radio-Technology-Enabled Opportunistic Spectrum Utilization. She is a co-PI and AI cluster co-lead for AIFS.

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Project Involvement

Reduce Postharvest Spoilage
Year 4

AI-Enabled Models for Reducing Postharvest Food Spoilage

#Food Processing and Distribution
Diet Recommendation System
Year 4

Dietary Assistant Powered by Language Models and Knowledge Graphs

#Nutrition#Core AI Technologies
Year 3

AI-Enabled Models for Food Digestion and Nutrient Delivery

#Core AI Technologies#Food Processing and Distribution
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AIFS Publications

  • A thumbnail of the journal or conference cover of Special report: AI Institute for next generation food systems (AIFS)
    Journal Article ⏐ Comput. Electron. Agric. 2022

    Special Report: AI Institute for Next Generation Food Systems (AIFS)

    Tagkopoulos, Ilias,Steve Brown,Xin Liu,Qing Zhao,Tarek I Zohdi,Mason Earles,Nitin Nitin,Daniel Runcie,Danielle G Lemay,Aaron Smith,Pamela Ronald,Hao Feng,and Gabriel Youtsey
    DOI: 10.1016/j.compag.2022.106819
    Publication
  • A thumbnail of the journal or conference cover of Constrained Reinforcement Learning for Autonomous Farming: Challenges and Opportunities
    Workshop Article ⏐ AAAI Workshop AI Agric. Food Syst. 2023

    Constrained Reinforcement Learning for Autonomous Farming: Challenges and Opportunities

    Liu, Yongshuai,Taeyeong Choi,and Xin Liu
    Publication
  • A thumbnail of the journal or conference cover of Quantifying Causal Path-Specific Importance in Structural Causal Model
    Journal Article ⏐ Computation 2023

    Quantifying Causal Path-Specific Importance in Structural Causal Model

    Wang, Xiaoxiao,Minda Zhao,Fanyu Meng,Xin Liu,Zhaodan Kong,and Xin Chen
    DOI: 10.3390/computation11070133
    Publication
  • A thumbnail of the journal or conference cover of Duopoly Business Competition in Cross-Silo Federated Learning
    Journal Article ⏐ IEEE Trans. Netw. Sci. Eng. 2023

    Duopoly Business Competition in Cross-Silo Federated Learning

    Huang, Chao,Shuqi Ke,and Xin Liu
    DOI: 10.1109/TNSE.2023.3297880
  • A thumbnail of the journal or conference cover of When Federated Learning Meets Oligopoly Competition: Stability and Model Differentiation
    Journal Article ⏐ IEEE Internet Things J. 2024

    When Federated Learning Meets Oligopoly Competition: Stability and Model Differentiation

    Huang, Chao,Justin Dachille,and Xin Liu
    DOI: 10.1109/JIOT.2024.3400216
    Publication
  • A thumbnail of the journal or conference cover of Policy Learning with Constraints in Model-free Reinforcement Learning: A Survey
    Conference Article ⏐ IJCAI 2021

    Policy Learning with Constraints in Model-free Reinforcement Learning: A Survey

    Liu, Yongshuai,Avishai Halev,and Xin Liu
    DOI: 10.24963/ijcai.2021/614
  • A thumbnail of the journal or conference cover of CTS2: Time Series Smoothing with Constrained Reinforcement Learning
    Conference Article ⏐ ACML 2021

    CTS2: Time Series Smoothing with Constrained Reinforcement Learning

    Liu, Yongshuai,and Xin Liu
    Publication
  • A thumbnail of the journal or conference cover of Resource Allocation Method for Network Slicing Using Constrained Reinforcement Learning
    Conference Article ⏐ IFIP Network. Conf. 2021

    Resource Allocation Method for Network Slicing Using Constrained Reinforcement Learning

    Liu, Yongshuai,Jiaxin Ding,and Xin Liu
    DOI: 10.23919/IFIPNetworking52078.2021.9472202
  • A thumbnail of the journal or conference cover of FedTune: Automatic Tuning of Federated Learning Hyper-Parameters from System Perspective
    Conference Article ⏐ MILCOM 2022

    FedTune: Automatic Tuning of Federated Learning Hyper-Parameters From System Perspective

    Zhang, Huanle,Mi Zhang,Xin Liu,Prasant Mohapatra,and Michael DeLucia
    DOI: 10.1109/MILCOM55135.2022.10017717
    Publication
  • A thumbnail of the journal or conference cover of CLARA: A Constrained Reinforcement Learning Based Resource Allocation Framework for Network Slicing
    Conference Article ⏐ IEEE Trans. Big Data 2023

    CLARA: A Constrained Reinforcement Learning Based Resource Allocation Framework for Network Slicing

    Liu, Yongshuai,Jiaxin Ding,Zhi-Li Zhang,and Xin Liu
    DOI: 10.1109/BigData52589.2021.9671840
  • A thumbnail of the journal or conference cover of Accuracy-Privacy Trade-off in Deep Ensemble: A Membership Inference Perspective
    Conference Article ⏐ IEEE SP 2023

    Accuracy-Privacy Trade-off in Deep Ensemble: A Membership Inference Perspective

    Rezaei, Shahbaz,Zubair Shafiq,and Xin Liu
    DOI: 10.1109/SP46215.2023.10179463
  • A thumbnail of the journal or conference cover of DAVIS-Ag: A Synthetic Plant Dataset for Developing Domain-Inspired Active Vision in Agricultural Robots
    Conference Article ⏐ IROS 2024

    DAVIS-Ag: A Synthetic Plant Dataset for Developing Domain-Inspired Active Vision in Agricultural Robots

    Choi, Taeyeong,Dario Guevara,Zifei Cheng,Grisha Bandodkar,Chonghan Wang,Brian N Bailey,Mason Earles,and Xin Liu
  • A thumbnail of the journal or conference cover of Causal explanation for reinforcement learning: quantifying state and temporal importance
    Journal Article ⏐ APIN 2023

    Causal Explanation for Reinforcement Learning: Quantifying State and Temporal Importance

    Wang, Xiaoxiao,Fanyu Meng,Xin Liu,Zhaodan Kong,and Xin Chen
    DOI: 10.1007/s10489-023-04649-7
    Publication
  • A thumbnail of the journal or conference cover of Spectroscopy Approaches for Food Safety Applications: Improving Data Efficiency Using Active Learning and Semi-supervised Learning
    Journal Article ⏐ Front. Artif. Intell. 2022

    Spectroscopy Approaches for Food Safety Applications: Improving Data Efficiency Using Active Learning and Semi-supervised Learning

    Zhang, Huanle,Nicharee Wisuthiphaet,Hemiao Cui,Nitin Nitin,Xin Liu,and Qing Zhao
    DOI: 10.3389/frai.2022.863261
    Publication
  • A thumbnail of the journal or conference cover of Promoting Collaboration in Cross-Silo Federated Learning: Challenges and Opportunities
    Journal Article ⏐ IEEE Commun. Mag. 2023

    Promoting Collaboration in Cross-Silo Federated Learning: Challenges and Opportunities

    Huang, Chao,Ming Tang,Qian Ma,Jianwei Huang,and Xin Liu
    DOI: 10.1109/MCOM.005.2300467
    Publication