Mohammad Mavadati, PhD

Mohammad Mavadati, PhD, has a diverse work experience that spans several industries and roles. Mohammad is currently the Lead Computer Vision Scientist at Smart Eye, a position they have held since June 2021 following the company's acquisition of Affectiva. In this role, they collaborate with the Automotive - Cabin Monitoring System (CMS) team and the Media Analytics team to expand Smart Eye's capabilities in Facial Analysis and Emotion Recognition.

Prior to joining Smart Eye, Mohammad served as the Lead Computer Vision Scientist at Affectiva from 2015. In this role, they prioritized R&D initiatives, designed and developed new modeling techniques for Emotion Modeling and Annotations, and guided the Facial Annotation initiative at Affectiva.

Earlier in their career, Mohammad was a PhD Researcher at the Computer Vision Lab in the Electrical and Computer Engineering department of the University of Denver. Their research focused on Machine Learning and Computer Vision algorithms, specifically in the areas of Spontaneous Facial Expression Analysis and Robot Based Autism Intervention. During their time at the University of Denver, they authored 11 technical papers and published a novel publicly available database on facial expression analysis called DISFA.

Mohammad also gained practical experience through internships at TKO, where they worked on Computer Vision and Machine Learning projects, and at Nargan Amitis Energy Development (NAED), where they assisted with telecommunication and electrical services for oil and gas companies.

Mohammad also completed internships at Bistoon Petrochemical Company and saipa, where they gained experience in electrical engineering, automation, and instrumentation in the manufacturing industry.

Overall, Mohammad Mavadati, PhD, has a strong background in Computer Vision, Emotion Modeling, and Facial Analysis, and has made significant contributions to the field through their research, publications, and industry experience.

Mohammad Mavadati, PhD, has an extensive education history in the field of engineering. Mohammad began their educational journey at Shahrood University of Technology, where they completed their Bachelor of Science degree in Electrical and Electronics Engineering from 2003 to 2007.

After completing their undergraduate studies, Mohammad pursued further education at Yazd University. During their time there from 2007 to 2010, they earned their Master of Science degree in Electrical and Telecommunication Engineering.

To deepen their expertise, Mohammad then enrolled at the University of Denver, where they completed their Doctor of Philosophy (Ph.D.) degree in Electrical and Computer Engineering. Mohammad dedicated their studies to this field from 2010 to 2015.

Furthermore, Mohammad Mavadati obtained an additional certification. Mohammad is LICENCED in the Facial Action Coding System (FACS), which they completed through the Paul Ekman Group (PEG). The specific month and year of obtaining this certification were not provided.

In summary, Mohammad Mavadati, PhD, has a comprehensive education history with a Bachelor's degree in Electrical and Electronics Engineering, a Master's degree in Electrical and Telecommunication Engineering, and a Doctorate degree in Electrical and Computer Engineering. Additionally, they hold a certification in the Facial Action Coding System (FACS).