Ashkan got his master degree  in industrial engineering in 2018 and after that did another master's in MBA. He has started his adventure as a joint Ph.D. student in mid-2019 with the close collaboration of STADUIS/ESAT lab of KU Leuven.

He is currently working on a federated learning framework to apply this framework in multiple sclerosis using real-world data. He believes in FAIR data. As "Accessibility" is one of these FAIR data principles, He aims to launch infrastructure and framework that learns from other data sources without sacrificing privacy in real-world data. He believes we already pass the centralized data silos era for big data research, and we have to come up with ideas to know how to share data, of course, by taking into account all the ethical and legal challenges.

His other research interest is machine learning, specifically artificial neural networks, BlockChain, and DevOps, with a keen interest in containerization.