Pedram Kasebzadeh

Pedram Kasebzadeh's work experience begins in 2020 with a role as a Thesis Worker at ABB. During this time, they focused on improving detection reliability in radar-based safety applications by utilizing mathematical and statistical analysis and machine learning algorithms. Pedram proposed an innovative approach using a noise-based model for detection and also worked on image processing-based noise modeling using heatmaps of collected data. Since 2021, Pedram has been working as a Data Scientist at Annalect.

Pedram Kasebzadeh completed a Master of Science (MS) degree in Statistics and Machine Learning from Linköping University, starting in 2018 and finishing in 2020. Additionally, Pedram obtained several certifications, including "Marketing Science Professional" from Meta in August 2022, "Facebook Certified Marketing Developer" from Meta in November 2021, "Docker for Data Scientists" from LinkedIn in December 2020, "Power BI Data Modeling with DAX" from LinkedIn in September 2020, and several deep learning specializations from Coursera in July 2019, including "Deep learning specialization," "Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization," "Neural Networks and Deep Learning," "Sequence Models," and "Structuring Machine Learning Projects." However, no information is available about the completion date or institution for the "Convolutional Neural Networks" certification.