Working with

Farid Musavian is a Deep Learning Research Engineer currently based at Halmstad University in Sweden. He is currently working on representation learning for Electronic Health Records (EHR) using Graph Transformer models. He also is working on Anomaly detection in multivariate time series in order to perform Surveillance of disease outbreaks using health counselling data linked with registers. His special interest is working on representation learning, reinforcement learning and generative models.

Before his current position, Musavian worked at Skoltech's "MobileRobotics" lab in Skolkovo Institute of Science and Technology (Skoltech) in Moscow as a Deep Learning Research Engineer. There, he led projects on trajectory prediction for autonomous vehicles and global indoor image localization. His industrial and academic projects often intersected, enhancing his practical experience in the field. In his Research Intern position, in “Tensor Networks and Deep Learning for Applications in Data Mining” lab, he has worked on several problems, ranging from apply graph neural networks on Brain Computer Interfaces, to randomised models on tensor decompositions.

Musavian earned his Master of Science in Mathematics and Computer Science from the Skolkovo Institute of Science and Technology (Skoltech) in Moscow, Russia at 2020. His studies focused on deep learning, machine learning, and their applications in data analysis and digital signal processing, setting the foundation for his career in research.