Vladimir Vlassov

Vladimir Vlassov is a full Professor in Computer Systems at KTH. His research interests include Machine Learning, Data-intensive computing, Cloud computing, Distributed computing, and Autonomic computing.

His research focuses on scalable deep learning, NLP/NLU, data-intensive computing and stream processing, Cloud-based services and applications, and large-scale distributed systems.

He has participated in several European projects on data-intensive computing (Big Data), Cloud computing, P2P, autonomic computing, and multi-core systems. He has also participated in several research projects funded by Swedish funding agencies and NSF USA. Recently, he was a principal investigator in the H2020 project "ExtremeEarth: From Copernicus Big Data to Extreme Earth Analytics" (http://earthanalytics.eu/) and one of the coordinators of the Erasmus Mundus Joint Doctorate in Distributed Computing (EMJD-DC). His past research projects are presented on his home page.

Currently, he is a principal investigator in the project "ALEC2 - Adaptive Level of Effective and Continuous Care to Common Mental Health Disorders," which aims to develop an AI-supported system for online cognitive behavioral therapy (iCBT) using AI technologies, namely NLP, NLU, DL, and LLM, to automatically diagnose, predict, and monitor mental health conditions to support patients toward full recovery.

[See  also my homepage for more details.]

Topics for Master Degree Projects