Welcome! I am a PhD student in the Department of Electrical Engineering and Computer Science of Massachusetts Institute of Technology (MIT). I am very fortunate to be advised by Vinod Vaikuntanathan.
My research interests include Cryptography and Post - Quantum Cryptography, Computational Complexity Theory and Algorithms.
I joined the graduate program of MIT on September 2013 in the Theory of Computation group at CSAIL. I received a Master of Sience degree on February 2016 under the supervision of Ron Rivest. My phD research advisor is Vinod Vaikuntanathan and we are working on post-quantum cryptography.
Before MIT, I was an undergrad student at the Department of Applied Mathematical and Physical Sciences at National Technical University of Athens where I completed my Diploma Degree. During my time there, I was fortunate to work with Professor Antonios Symvonis.
Abstract. In the dynamic network model, the communication graph is assumed to be connected in every round but is otherwise arbitrary. We consider the related setting of p-partitioned dynamic networks, in which the communication graph in each round consists of at most p connected components. We explore the problem of k-agreement in this model for k≥p. We show that if the number of processes is unknown then it is impossible to achieve k-agreement for any k and any p≥2. Given an upper bound n on the number of processes, we provide algorithms achieving k-agreement in p(n−p) rounds for k=p and in O(n/ϵ) rounds for k=⌈(1+ϵ)p⌉.
Abstract. Occupational fraud affects many companies worldwide causing them economic loss and liability issues towards their customers and other involved entities. Detecting internal fraud in a company requires significant effort and, unfortunately cannot be entirely prevented. The internal auditors have to process a huge amount of data produced by diverse systems, which are in most cases in textual form, with little automated support. In this paper, we exploit the advantages of information visualization and present a system that aims to detect occupational fraud in systems which involve a pair of entities (e.g., an employee and a client) and periodic activity. The main visualization is based on a spiral system on which the events are drawn appropriately according to their time-stamp. Suspicious events are considered those which appear along the same radius or on close radii of the spiral. Before producing the visualization, the system ranks both involved entities according to the specifications of the internal auditor and generates a video file of the activity such that events with strong evidence of fraud appear first in the video. The system is also equipped with several different visualizations and mechanisms in order to meet the requirements of an internal fraud detection system.