ID 2413: Depression Detection Through Facial Analysis – EmpkinS D02

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This project utilizes cutting-edge technology to detect depression at its early stages. We use facial behavior analysis software to extract facial attributes, which are then used to train models for depression detection. Our methodology is built upon the EmpkinS D02 dataset. By integrating advanced facial analysis with machine learning techniques, our project aims to facilitate the identification and intervention of depression.



  • Collaborate on data collection, particularly being flexible on Mondays and Tuesdays
  • Conduct data processing using Face Reader software
  • 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