Current areas of research include:

  • Face recognition (plastic surgery, sketch, low resolution disguise, quality, kinect, kinship, newborns, aging, weight)
  • Fingerprint recognition (latent, simultaneous latent)
  • Iris recognition (aging, alcohol, surgery, disease, interoperability)
  • Large scale biometric system
  • Presentation attack detection (Anti-spoofing)
  • Soft biometrics
  • Multimodal fusion
  • Face CAPTCHA

    Machine Learning and Pattern Recognition
  • Deep learning
  • Dictionary Learning
  • Domain transfer learning
  • Incremental learning
  • Manifold/subspace learning

  • functional Magnetic Response Imaging
  • EEG

    Medical Image Processing
  • Mammography
  • Cell image classification


  • Special issue on Domain Adaptation for Visual Understanding with PR
  • Five papers accepted at IEEE International Conference on Biometrics: Theory, Applications and Systems, 2018. Find out more.
  • Dr. Richa Singh and Dr. Mayank Vatsa recently gave a tutorial on From Deep Unsupervised to Supervised Models for Face Analysis at 12th IEEE Conference on Automatic Face and Gesture Recognition, Washington DC
  • Dr. Mayank Vatsa and Dr. Richa Singh giving a tutorial on Deep Learning for Face Recognition at the 2017 International Joint Conference on Neural Networks - IJCNN being held at Anchorage, Alaska.
  • Dr. Richa Singh and Dr. Mayank Vatsa at Rutgers University for colloquium talk on unconstrained face recognition.
  • Dr. Mayank Vatsa and Dr. Richa Singh gave a talk on Deep Learning and Face Recognition at IBM TJ Watson Research Center, Yorktown, NY

  • ML-India recently interviewed Dr. Mayank Vatsa as part of their interview series