School of Mathematical Sciences

Staff and student profiles menu

Staff and student profiles

The Complex Systems and Networks group at the School of Mathematical Sciences is a very active hub that addresses research in complexity science and network theory, in collaboration with other top research groups worldwide (MIT, Cambridge, Oxford, Harvard, Northeastern, Catania, Barcelona, Paris, etc) and with industrial stakeholders. The group is formed by faculty members, postdoctoral research associated, and PhD graduate students.

Some of our networks research specialists include:

Professor David Arrowsmith
Prof. Arrowsmith's main area of research has been  dynamical systems. More recently, he  has been involved with research programmes on complex networks in telecommunications, power grids, and infrastructure supplies. He has published over 60 articles and 5 books (including 2 translations).  In the last decade he has been supported by the EPSRC  on packet traffic in networks (Joint  with University of York, 2003-2005), and was Principal Investigator of an EPSRC project RAVEN - Resilience, Adaptability, and Vulnerability of complex Energy Networks,  2010-2013.  He was also  coordinator for an EU Pathfinder research project, MANMADE, on the criticality of energy infrastructure networks in Europe 2006-2009.  He is currently involved in the co-supervising a PhD project with the School of Medicine and Dentistry at QMUL on the network analysis of trauma response, 2011-2014. He is a member of the EPSRC Strategic Advisory Team for Mathematical Sciences, 2011-2014;  Chair of HoDoMS (Heads of Departments of Mathematical Sciences UK) 2011-2014; member of the LMS Research Committee, 2011-2014; member of the QAA Subject Benchmark Review (Mathematics, Statistics and Operational Research), 2014; Member of the Joint Mathematical Council Executive, 2014-2015, proposed Education Secretary of the IMA, proposed for 2015-2017.

Dr Ginestra Bianconi
Dr Bianconi is interested in statistical mechanics, complex networks and to interdisciplinary applications to complex biological, social and technological systems. In particular she is working on critical phenomena on networks, on their off-equilibrium dynamical properties, on the interplay between their global and local structure and on the quantification of their complexity by entropy measures. The results of her work include the mathematical treatment of condensation off- equilibrium transitions that explain the winner-takes-all phenomena observed in the World-Wide-Web as well as in models of ecology and evolution. The aim of her current research is a formulation of an information theory of complex networks, the characterization of temporal social networks and the study of classical and quantum phenomena on single and interacting networks.

Dr Lucas LacasaDr Lacasa
Dr Lacasa
has broad interests in complexity science, where he addresses both theoretical and applied problems by using tools from statistical physics, nonlinear dynamics, stochastic processes and network science. He introduced the concept of visibility algorithms, accurate transformations mapping time series to networks, as a novel tool for graph-theoretical time series analysis, which he has successfully applied to classic series classification problems, such as the chaos/noise or the reversible/irreversible identification. He is currently interested in developing a general network-based theory of signals and their underlying dynamics under this approach. Other research interests include the application of statistical physics, dynamical systems and networks to interdisciplinary problems: the onset of phase transitions and criticality in combinatoric systems, the emergence of collective behaviour in social or biological systems, or the description of dynamics running in top of networks are a few examples.

Professor Vito LatoraProfessor Latora
Prof. Latora
is interested in complex systems, nonlinear dynamics and statistical mechanics. He has contributed with a series of mathematical models and empirical studies to understand the structure and dynamics of complex networks. In particular, he has pioneered works on the efficient behavior of weighted networks, on cascading failures, and on spatial networks. He is currently focusing on time-varying networks, and on interacting and biased random walks, epidemic spreading, and emergence of synchronization in complex networks. He is actively working on various applications of complex networks theory to neuroscience, biology, social sciences, and to the study of urban systems. He is a coauthor of a review article on the structure and dynamics of complex networks.

 

MSc students

Quote by Mr. Harvie Kwan Chiu (MSc Network Science student 2015-2016):
"My time at Queen Mary, University of London has been the most fast and exhilarating year of my academic background. Regardless of the intensity, determination, and commitment needed at this level, I have gained valuable experiences, growth, and last but not least, friends. I feel I made the right decision studying the Master of Science in Network Science as it combines my enjoyment of mathematics, yet focusing on a specialised discipline. As I made the transition to masters, it was so refreshing to see the amount of time and dedication the supervisors and advisers spent with their students. The way that lecturers and supervisors would always offer a helping hand to give their support, combined with the niche modules studied, I believe makes the MSc Network Science such a great programme within the School of Mathematics. Throughout the year, students will learn that the MSc Network Science is a close-knit programme and the experiences and friends that one gains will be monumental. Overall, I enjoyed this masters programme as it has allowed to focus in the underlying mathematical concepts, analysis, and modelling of complex networks, yet gain important transferable skills in computing and data analysis. If students wish to focus or specialise in a field of mathematics, I highly recommend them to study this programme."