World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
52
Citations
16907
World Ranking
4968
National Ranking
296

Overview

Michel Valstar is a researcher affiliated with the University of Nottingham in the United Kingdom. Their work lies primarily at the intersection of psychology and computer science, reflecting an interdisciplinary approach to understanding human behavior through computational methods.

Valstar's research covers extensive topics including emotion and mood recognition, face recognition and analysis, speech and audio processing, and mental health research. The scientist has also contributed to fields involving neonatal respiratory health and music and audio processing. Their main fields of study span:

  • Psychology
  • Computer Science

With a focus on specialized subfields, Valstar's research portfolio includes areas such as experimental and cognitive psychology, computer vision and pattern recognition, signal processing, cognitive neuroscience, and social psychology. These subfields underpin a large fraction of their publication record and research efforts.

Their recent publications demonstrate a strong emphasis on affective computing and machine learning methods to analyze facial and behavioral data. Notable papers include:

  • "Spectral Representation of Behaviour Primitives for Depression Analysis" (2020, IEEE Transactions on Affective Computing)
  • "Self-Supervised Learning of Person-Specific Facial Dynamics for Automatic Personality Recognition" (2021, IEEE Transactions on Affective Computing)
  • "eXplainable Cooperative Machine Learning with NOVA" (2020, KI - Künstliche Intelligenz)
  • "Learning Person-Specific Cognition From Facial Reactions for Automatic Personality Recognition" (2022, IEEE Transactions on Affective Computing)
  • "COLD Fusion: Calibrated and Ordinal Latent Distribution Fusion for Uncertainty-Aware Multimodal Emotion Recognition" (2023, IEEE Transactions on Pattern Analysis and Machine Intelligence)

Valstar frequently publishes in venues that cater to interdisciplinary research spanning artificial intelligence, pattern recognition, and psychological science. Prominent venues for their work include:

  • arXiv (Cornell University)
  • IEEE Transactions on Affective Computing
  • Pediatric Research
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • KI - Künstliche Intelligenz

Collaborative research is a significant aspect of Valstar's work, with repeated co-authorships reflecting established partnerships. Frequent collaborators include:

  • Mani Kumar Tellamekala
  • Siyang Song
  • Björn W. Schuller
  • Elisabeth André
  • Timo Giesbrecht

Overall, Michel Valstar's research integrates psychological theory and computational techniques, focusing on the analysis of facial expressions, emotions, and personal cognitive states using machine learning and signal processing methodologies.

Best Publications

  • The Visual Object Tracking VOT2016 Challenge Results

    Matej Kristan;Aleš Leonardis;Jiři Matas;Michael Felsberg

  • Web-based database for facial expression analysis

    M. Pantic;M. Valstar;R. Rademaker;L. Maat

  • The SEMAINE Database: Annotated Multimodal Records of Emotionally Colored Conversations between a Person and a Limited Agent

    G. McKeown;M. Valstar;R. Cowie;M. Pantic

  • AVEC 2016: Depression, Mood, and Emotion Recognition Workshop and Challenge

    Michel Valstar;Jonathan Gratch;Björn Schuller;Fabien Ringeval

  • AVEC 2013: the continuous audio/visual emotion and depression recognition challenge

    Michel Valstar;Björn Schuller;Kirsty Smith;Florian Eyben

  • AVEC 2014: 3D Dimensional Affect and Depression Recognition Challenge

    Michel Valstar;Björn Schuller;Kirsty Smith;Timur Almaev

  • Fully Automatic Facial Action Unit Detection and Temporal Analysis

    M. Valstar;M. Pantic

  • The first facial expression recognition and analysis challenge

    Michel F. Valstar;Bihan Jiang;Marc Mehu;Maja Pantic

  • Facial point detection using boosted regression and graph models

    Michel Valstar;Brais Martinez;Xavier Binefa;Maja Pantic

  • Fully Automatic Recognition of the Temporal Phases of Facial Actions

    M. F. Valstar;M. Pantic

  • Meta-Analysis of the First Facial Expression Recognition Challenge

    M. F. Valstar;M. Mehu;Bihan Jiang;M. Pantic

  • The SEMAINE corpus of emotionally coloured character interactions

    Gary McKeown;Michel F. Valstar;Roderick Cowie;Maja Pantic

  • AVEC 2011-the first international audio/visual emotion challenge

    Björn Schuller;Michel Valstar;Florian Eyben;Gary McKeown

  • Automatic Analysis of Facial Actions: A Survey

    Brais Martinez;Michel F. Valstar;Bihan Jiang;Maja Pantic

  • AVEC 2012: the continuous audio/visual emotion challenge

    Björn Schuller;Michel Valster;Florian Eyben;Roddy Cowie

  • FERA 2015 - second Facial Expression Recognition and Analysis challenge

    Michel F. Valstar;Timur Almaev;Jeffrey M. Girard;Gary McKeown

  • AVEC 2017: Real-life Depression, and Affect Recognition Workshop and Challenge

    Fabien Ringeval;Björn Schuller;Michel Valstar;Jonathan Gratch

  • Action unit detection using sparse appearance descriptors in space-time video volumes

    Bihan Jiang;Michel F. Valstar;Maja Pantic

  • AVEC 2019 Workshop and Challenge: State-of-Mind, Detecting Depression with AI, and Cross-Cultural Affect Recognition

    Fabien Ringeval;Björn Schuller;Michel Valstar;Nicholas Cummins

  • How to distinguish posed from spontaneous smiles using geometric features

    Michel F. Valstar;Hatice Gunes;Maja Pantic

Frequent Co-Authors

Maja Pantic
Maja Pantic Imperial College London
Björn Schuller
Björn Schuller Imperial College London
Roddy Cowie
Roddy Cowie Queen's University Belfast
Fabien Ringeval
Fabien Ringeval Grenoble Alpes University
Georgios Tzimiropoulos
Georgios Tzimiropoulos Queen Mary University of London
Jonathan Gratch
Jonathan Gratch University of Southern California
Linlin Shen
Linlin Shen Shenzhen University
Florian Eyben
Florian Eyben Technical University of Munich
Catherine Pelachaud
Catherine Pelachaud Sorbonne University
Jeffrey F. Cohn
Jeffrey F. Cohn University of Pittsburgh

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