Soft skills training: (A) How to prepare and give powerful presentations, (B) How to write a research paper. - Guest Lecturer (Fall, 2016) at the "Security, Privacy, and Intelligence on the Internet" course, CS dept., University of Crete
HY- 533 : Security, Privacy and Intelligence on the Internet is a seminar course in the area of Computer Networks, taught by Prof. Xenofontas Dimitropoulos.
Adding to the technical skills taught in the course, one of the course’s objective is that students are able to work together in teams and communicate effectively, both in writing and orally.
Guest lectures:
Soft skills training: (A) Powerful Presentations. by Pavlos Sermpezis
get the slides here:
Soft skills training: (B) How to write a research paper. by Pavlos Sermpezis
get the slides here:
Winter School on Complex Networks - Lab Responsible (January 2014 and January 2015)
Development of the Practical Session on "Complex Network Analysis for Mobility Modeling"
The Winter School on Complex Networks 2014 was an one-week school about the fundamentals and ongoing research activities on network science, organized at Inria Sophia-Antipolis, and targeted to Master and PhD students .
- Description: The lecture and the practical session of the course "Complex Network Analysis for Mobility Modeling" were focused on modeling mobility traces as complex graphs, complex network analysis and routing protocols design based on certain mobility/graph characteristics.
Network Modeling - Teaching Assistant (Fall, 2011 - 2014)
Network Modeling is a course taught, as a part of Eurecom's Master Program, by Prof. Thrasyvoulos Spyropoulos.
- Description: The course teaches how to analyze (a) the structure of large networks (e.g. online social networks like Facebook or Twitter, p2p networks like Skype or BitTorrent, wireless mesh and sensor networks, etc.), and (b) the performance of dynamic processes over these networks (e.g. routing, broadcasting, searching, virus spread).
- Analytic and algorithmic tools: Stochastic processes, Markov Chains, queueing theory, complex network models and analysis, network epidemics, random walks on graphs, sampling.
- Lab: Practical examples of how complex network theory is applied to real networks. Analysis of real networks datasets in order to reveal their structure and characteristics.