CMU Silicon Valley welcomes Armand Makowski

Date/Time: April 5, 2016, 1:30 pm (PT) / 4:30 pm (ET) 

Location: CMU Silicon Valley Campus: Bldg 23, Rm 118

Open to Carnegie Mellon students, faculty, and staff only

Degree distributions in large networks: A little theory and a counterexample

In random graph models, the degree distribution of individual nodes should be contrasted with the degree distribution of the graph, i.e., the usual fractions of nodes with given degree. A general framework is introduced to discuss conditions under which these two degree distributions coincide asymptotically. Somewhat surprisingly, we show that this assumption may fail to hold, even in strongly homogeneous random networks. This counterexample can be found in the class of random threshold graphs. An interesting implication of this finding is that random threshold graphs cannot be used as a substitute for the Barab\'asi-Albert model, a claim made in the literature. This is joint work with graduate student Siddarth Pal (UMD/ECE).

Armand M. Makowski received the Licence en Sciences Mathematiques from the Universite Libre de Bruxelles in 1975, the M.S. degree in Engineering-Systems Science from U.C.L.A. in 1976 and the Ph.D. degree in Applied Mathematics from the University of Kentucky in 1981. In August 1981, he joined the faculty of the Electrical Engineering Department at the University of Maryland College Park, where he is Professor of Electrical and Computer Engineering. He has held a joint appointment with the Institute for Systems Research since its establishment in 1985.

Prof. Makowski was a C.R.B. Fellow of the Belgian-American Educational Foundation (BAEF) for the academic year 1975-76; he is also a 1984 recipient of the NSF Presidential Young Investigator Award. He became an IEEE Fellow in 2006, and received a Lady Davis Trust Fellowship in Fall 2014. His research interests lie in applying advanced methods from the theory of stochastic processes to the modeling, design and performance evaluation of engineering systems, with particular emphasis on communication systems and networks.