Chrysanthi Kosyfaki

About Me

I am a postdoctoral fellow in the Department of Computer Science and Engineering at Hong Kong University of Science and Technology. Previously, I was a postdoctoral research associate at the University of Hong Kong. I obtained my Ph.D. degree from University of Ioannina, Computer Science and Engineering Department, working with Prof. Nikos Mamoulis.

Research Interests

My research interests are in the area of graph analytics with a focus on a new class of networks called Temporal Interaction Networks (TINs). In these networks, a quantity (flow) transfers from one vertex to another within a time window. TINs can model dynamic systems where entities exchange quantities, such as financial transactions, transportation flows, or communication data. Over the past few years, I have been developing efficient solutions to optimize classical problems (e.g., max-flow computation) by introducing the temporal dimension.

Currently, I am working on provenance tracking for streaming systems, where understanding how outputs are derived from inputs is critical for debugging, auditing, and explainability. I am developing how-much provenance, a new model that reports how much data each source contributed to an output, or to all outputs of a sink within a time window, without tracking individual tuples. I am also interested in exploring downstream provenance, which reverses the direction of traditional provenance. It starts from a problematic source and identifies how many outputs that source fed, over an interval of production and along a processing path.