Research topics

My research focuses on developing intelligent computational models to understand, recognize and predict human behavior combining Machine Learning and Signal Processing. With my students and collaborators, I am currently working on the following topics:

  • Affect and behavior modeling from verbal and non-verbal cues

(speech and multimodal emotion analysis, head motion modeling)

  • Pedestrian and crowd behavior understanding

(crowd flow and density estimation, trajectory forecasting)

  • Activity recognition and forecasting

(drivers' activity monitoring, action forecasting using graph deep learning)

PhD students

Research support

  • PI: Multimodal Learning for In-Car Driver Activity Monitoring. Ford University Research Program. 2021 - 2023.

  • PI: Crossmodal Biometric Matching. Warwick RDF Award. 2019.

  • PI: Application-aware Image Quality Assessment. Indian Space Research Organization. 2016 - 2018.

  • CoI: Holistic Scene Understanding. Samsung Research. 2017 - 2018.

  • PI: NVIDIA Academic GPU Grant. 2017.

Demos/Talks