ID 2414: Detecting Depression: Facial Feature Extraction with OpenFace in EmpkinS D02

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This project employs sophisticated techniques to detect depression in its early stages. By utilizing a specialized toolkit called OpenFace, we analyze facial action units and extract important features from the EmpkinS D02 dataset. These features are then used to train machine learning models to recognize signs of depression.



  • Collaborate on data collection, particularly being flexible on Mondays and Tuesdays
  • Conduct data processing using the OpenFace tool
  • Develop machine learning models for depression detection
  • Validate and optimize models through careful testing and analysis
  • Participate in regular team meetings to discuss progress, challenges, and next steps
  • Contribute to documentation and reports detailing project findings and methodologies



  • Experience in machine learning
  • Proficient in Python programming
  • Good command of the English language for effective communication
  • Ability to work independently and as part of a team, with good communication and organizational skills


In case you are interested, please send your CV and your transcript of records to:

Misha Sadeghi
Machine Learning and Data Analytics Lab



Misha Sadeghi, M. Sc.

Researcher & PhD Candidate