World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
55
Citations
9266
World Ranking
4402
National Ranking
2054

Overview

Yisong Yue is affiliated with the California Institute of Technology in the United States. The primary fields of study encompass Computer Science and Engineering, with significant contributions in subfields such as Artificial Intelligence, Control and Systems Engineering, Molecular Biology, Computer Vision and Pattern Recognition, and Biomedical Engineering.

The research work focuses on topics including Reinforcement Learning in Robotics, Machine Learning and Algorithms, Advanced Control Systems Optimization, Fault Detection and Control Systems, Robotic Path Planning Algorithms, Advanced Bandit Algorithms Research, and Formal Methods in Verification.

Yisong Yue has published extensively in several venues. Frequent publication venues include arXiv (Cornell University), bioRxiv (Cold Spring Harbor Laboratory), IEEE Robotics and Automation Letters, Cell Systems, and The Caltech Institute Archives (California Institute of Technology).

Among recent papers, notable works include:

  • "Informed training set design enables efficient machine learning-assisted directed protein evolution," 2021, Cell Systems
  • "Neural-Fly enables rapid learning for agile flight in strong winds," 2022, Science Robotics
  • "Using deep reinforcement learning to reveal how the brain encodes abstract state-space representations in high-dimensional environments," 2020, Neuron
  • "Neural-Swarm2: Planning and Control of Heterogeneous Multirotor Swarms Using Learned Interactions," 2021, IEEE Transactions on Robotics
  • "An Efficient Simulation-Based Approach to Ambulance Fleet Allocation and Dynamic Redeployment," 2021, Proceedings of the AAAI Conference on Artificial Intelligence

Yisong Yue's frequent coauthors include Aaron D. Ames, Soon-Jo Chung, Guanya Shi, Frances H. Arnold, and Victor D. Dorobantu.

Best Publications

  • A support vector method for optimizing average precision

    Yisong Yue;Thomas Finley;Filip Radlinski;Thorsten Joachims

  • The K-armed dueling bandits problem

    Yisong Yue;Josef Broder;Robert Kleinberg;Thorsten Joachims

  • Interactively optimizing information retrieval systems as a dueling bandits problem

    Yisong Yue;Thorsten Joachims

  • A deep learning approach for generalized speech animation

    Sarah Taylor;Taehwan Kim;Yisong Yue;Moshe Mahler

  • Neural Lander: Stable Drone Landing Control Using Learned Dynamics

    Guanya Shi;Xichen Shi;Michael O'Connell;Rose Yu

  • Multi-Level Structured Models for Document-Level Sentiment Classification

    Ainur Yessenalina;Yisong Yue;Claire Cardie

  • Large-scale validation and analysis of interleaved search evaluation

    Olivier Chapelle;Thorsten Joachims;Filip Radlinski;Yisong Yue

  • Beyond position bias: examining result attractiveness as a source of presentation bias in clickthrough data

    Yisong Yue;Rajan Patel;Hein Roehrig

  • Predicting diverse subsets using structural SVMs

    Yisong Yue;Thorsten Joachims

  • Reliable Real-Time Seismic Signal/Noise Discrimination With Machine Learning

    Men‐Andrin Meier;Zachary E. Ross;Anshul Ramachandran;Ashwin Balakrishna

  • PhaseLink: A Deep Learning Approach to Seismic Phase Association

    Zachary E. Ross;Yisong Yue;Men-Andrin Meier;Egill Hauksson

  • Large-Scale Analysis of Soccer Matches Using Spatiotemporal Tracking Data

    Alina Bialkowski;Patrick Lucey;Peter Carr;Yisong Yue

  • Informed training set design enables efficient machine learning-assisted directed protein evolution.

    Bruce J. Wittmann;Yisong Yue;Frances H. Arnold

  • Linear Submodular Bandits and their Application to Diversified Retrieval

    Yisong Yue;Carlos Guestrin

  • Learning for Safety-Critical Control with Control Barrier Functions

    Andrew J. Taylor;Andrew Singletary;Yisong Yue;Aaron D. Ames

  • Predicting structured objects with support vector machines

    Thorsten Joachims;Thomas Hofmann;Yisong Yue;Chun-Nam Yu

  • Batch Policy Learning under Constraints

    Hoang Minh Le;Cameron Voloshin;Yisong Yue

  • Coordinated multi-agent imitation learning

    Hoang M. Le;Yisong Yue;Peter Carr;Patrick Lucey

  • Long-term Forecasting using Tensor-Train RNNs

    Rose Yu;Stephan Zheng;Anima Anandkumar;Yisong Yue

  • Learning Fine-Grained Spatial Models for Dynamic Sports Play Prediction

    Yisong Yue;Patrick Lucey;Peter Carr;Alina Bialkowski

  • Beat the Mean Bandit

    Yisong Yue;Thorsten Joachims

  • Interactively Optimizing Information Retrieval Systemsas a Dueling Bandits Problem

    Yisong Yue;Thorsten Joachims

Frequent Co-Authors

Anima Anandkumar
Anima Anandkumar Nvidia (United Kingdom)
Soon-Jo Chung
Soon-Jo Chung California Institute of Technology
Aaron D. Ames
Aaron D. Ames California Institute of Technology
Patrick Lucey
Patrick Lucey Stats Perform
Pietro Perona
Pietro Perona California Institute of Technology
Thorsten Joachims
Thorsten Joachims Cornell University
Iain Matthews
Iain Matthews University of East Anglia
Swarat Chaudhuri
Swarat Chaudhuri The University of Texas at Austin
Zachary E. Ross
Zachary E. Ross California Institute of Technology
Markus Meister
Markus Meister California Institute of Technology

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