World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
34
Citations
9789
World Ranking
11905
National Ranking
4855

Overview

Patrick Lucey is affiliated with Stats Perform in the United States and focuses their research primarily within the fields of Computer Science and Economics, Econometrics and Finance. Their work spans several interdisciplinary subfields including Artificial Intelligence, Economics and Econometrics, Signal Processing, Computer Vision and Pattern Recognition, and Biomedical Engineering.

Their research topics include:

  • Sports Analytics and Performance
  • Time Series Analysis and Forecasting
  • Anomaly Detection Techniques and Applications
  • Natural Language Processing Techniques
  • Video Analysis and Summarization
  • Semantic Web and Ontologies
  • Sports Dynamics and Biomechanics

Patrick Lucey has contributed to a number of publications, with notable papers as follows:

  • Characterizing Multi-Agent Team Behavior from Partial Team Tracings: Evidence from the English Premier League, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • You Cannot Do That Ben Stokes: Dynamically Predicting Shot Type in Cricket Using a Personalized Deep Neural Network, 2021, arXiv (Cornell University)
  • Event2Tracking: Reconstructing Multi-Agent Soccer Trajectories Using Long-Term Multimodal Context, 2025, Proceedings of the AAAI Conference on Artificial Intelligence

They frequently publish in venues such as the Proceedings of the AAAI Conference on Artificial Intelligence and arXiv (Cornell University).

Patrick Lucey collaborates with several co-authors, including:

  • Alina Bialkowski
  • Peter Carr
  • Eric Foote
  • Iain Matthews
  • H. R. Hughes

Best Publications

  • The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression

    Patrick Lucey;Jeffrey F. Cohn;Takeo Kanade;Jason Saragih

  • Painful data: The UNBC-McMaster shoulder pain expression archive database

    Patrick Lucey;Jeffrey F. Cohn;Kenneth M. Prkachin;Patricia E. Solomon

  • Automatically Detecting Pain in Video Through Facial Action Units

    P Lucey;J F Cohn;I Matthews;S Lucey

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

    Alina Bialkowski;Patrick Lucey;Peter Carr;Yisong Yue

  • Painful monitoring: Automatic pain monitoring using the UNBC-McMaster shoulder pain expression archive database

    Patrick Lucey;Jeffrey F. Cohn;Kenneth M. Prkachin;Patricia E. Solomon

  • A Database for Person Re-Identification in Multi-Camera Surveillance Networks

    Alina Bialkowski;Simon Denman;Sridha Sridharan;Clinton Fookes

  • "Quality vs Quantity": Improved Shot Prediction in Soccer using Strategic Features from Spatiotemporal Data

    Patrick Lucey;Alina Bialkowski;Mathew Monfort;Peter Carr

  • Person-independent facial expression detection using Constrained Local Models

    Sien. W. Chew;Patrick Lucey;Simon Lucey;Jason Saragih

  • Automated Facial Expression Recognition System

    Andrew Ryan;Jeffery F. Cohn;Simon Lucey;Jason Saragih

  • Coordinated multi-agent imitation learning

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

  • Not All Passes Are Created Equal: Objectively Measuring the Risk and Reward of Passes in Soccer from Tracking Data

    Paul Power;Hector Ruiz;Xinyu Wei;Patrick Lucey

  • Assessing team strategy using spatiotemporal data

    Patrick Lucey;Dean Oliver;Peter Carr;Joe Roth

  • Automatically detecting pain using facial actions

    Patrick Lucey;Jeffrey Cohn;Simon Lucey;Iain Matthews

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

    Yisong Yue;Patrick Lucey;Peter Carr;Alina Bialkowski

  • Representing and Discovering Adversarial Team Behaviors Using Player Roles

    Patrick Lucey;Alina Bialkowski;Peter Carr;Stuart Morgan

  • Identifying team style in soccer using formations learned from spatiotemporal tracking data

    Alina Bialkowski;Patrick J. Lucey;Peter Carr;Yisong Yue

  • Large-Scale Analysis of Formations in Soccer

    Xinyu Wei;Long Sha;Patrick Lucey;Stuart Morgan

  • In the Pursuit of Effective Affective Computing: The Relationship Between Features and Registration

    S. W. Chew;P. Lucey;S. Lucey;J. Saragih

  • DATA-DRIVEN GHOSTING USING DEEP IMITATION LEARNING

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

  • How to get an open shot: analyzing team movement in basketball using tracking data

    Patrick Lucey;Alina Bialkowski;Peter Carr;Yisong Yue

  • Win at home and draw away: automatic formation analysis highlighting the differences in home and away team behaviors

    Alina Bialkowski;Patrick Lucey;Peter Carr;Yisong Yue

Frequent Co-Authors

Sridha Sridharan
Sridha Sridharan Queensland University of Technology
Iain Matthews
Iain Matthews University of East Anglia
Yisong Yue
Yisong Yue California Institute of Technology
Simon Lucey
Simon Lucey University of Adelaide
Jeffrey F. Cohn
Jeffrey F. Cohn University of Pittsburgh
Clinton Fookes
Clinton Fookes Queensland University of Technology
Gerasimos Potamianos
Gerasimos Potamianos University Of Thessaly
Kenneth M. Prkachin
Kenneth M. Prkachin University of Northern British Columbia
Yaser Sheikh
Yaser Sheikh Facebook (United States)
Simon Denman
Simon Denman Queensland University of Technology

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