You can find out more about Pavlo Tertychnyi’s PhD thesis here.  Money laundering represents a substantial risk to global financial systems, allowing criminals to conceal the illegitimate origins of funds and integrate them into the lawful economy. Its repercussions extend beyond financial ramifications, encompassing the destabilization of financial systems, threats to national security, and the erosion […]

Together with colleagues from the UK and Sweden, the  UT Institute of Computer Science is organizing the first international workshop on the Testing of Automated Driving Systems (TestADS). The workshop takes place in Toronto, Canada, as part of the 17th IEEE International Conference on Software Testing, Verification and Validation (ICST’24). The TestADS workshop aims to […]

With the development of Online Social Media (OSM) platforms like Twitter and Facebook, the way individuals connect and exchange information has changed dramatically. These platforms have, however, also led to the problem of misinformation, which can quickly spread on a global scale, and once it has been disseminated, it can be hard to stop. It […]

Introduction: Privacy-preserving computation is a crucial discipline that protects the privacy of confidential data while facilitating secure analysis. In graph problems, secure multiparty computation (SMC) presents a promising approach to performing these functionalities. This article delves into the notable advancements in privacy-preserving parallel algorithms recently introduced in a Ph.D. thesis. By integrating graph algorithms with […]

Jaak Vilo, Kallol Roy Algorithmics (MTAT.03.238) is an obligatory course in the Computer Science MSc curriculum. As such it is intended to remind everyone of the foundations of algorithms and data structures but also to go beyond and teach some more advanced concepts (like succinct data structures, for example).  The course aims at linking different […]

We are living in a world in which data is not just getting bigger; it is also getting more and more interconnected. Large graph analytics is a useful tool for gaining insights from large volumes of interconnected data and has applications in various fields such as social media, biology, and telecommunications. An example of the […]