22 Oct

IEEE Seminar by Professor Armand Makowski

On behalf of the IEEE joint VT/COM/IT Sweden Chapter Board, we are delighted to share with you the information about an IEEE Seminar by Professor Armand Makowski, University of Maryland, College Park, USA.

Time: Tuesday, August 27, 2019, at 16:45
Location: Lecture room Q2, floor 2, Malvinas väg 10 (Q-House),
KTH main campus, 114 28 Stockholm, Sweden. (Link to map)

Title: Degree distribution in large (homogeneous) networks: A little theory and a counterexample


In random graph models, the degree distribution of individual nodes should be contrasted with the (empirical) 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 when the number of nodes become unboundedly large.

Somewhat surprisingly, we show that this assumption may fail to hold, even in strongly homogeneous random networks. A 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 Barabasi-Albert model, a claim made in the literature.

This is joint work with graduate student Siddarth Pal (now at Raytheon BBN).


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 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. He is currently on leave with the National Science Foundation as Program Director with the Communication and Information Foundation (CISE/CCF/CIF). Armand 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 for the academic year 2014-2015. 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.

Presentation slides:  IEEE_Sweden_Armand_Makowski

08 Apr

ACCESS DLS event by Prof. Geoffrey Li

On behalf of the IEEE joint VT/COM/IT Sweden Chapter Board, we are delighted to forward the invitation and welcome you to an ACCESS Distinguished Lecture Series event by Prof. Geoffrey Li, Georgia Institute of Technology, USA.

Time: Thu April 11, 2019, at 15:00
Location: Lecture room V35, floor 5, Teknikringen 76, (Väg och vatten),
KTH main campus, 114 28 Stockholm, Sweden. (Link to map)
Local host site: https://www.kth.se/en/aktuellt/kalender/forelasningar-seminarier/access-distinguished-lecture-series-1.892868

Title: The Deep Learning in Physical Layer Communications

It has been demonstrated recently that deep learning (DL) has great potentials to break the bottleneck of communication systems. In this talk, we introduce our recent work in DL in physical layer communications. DL can improve the performance of each individual (traditional) block in communication systems or jointly optimize the whole transmitter or receiver. Therefore, we can categorize the applications of DL in physical layer communications into with and without block processing structures.

For DL based communication systems with block structures, we present joint channel estimation and signal detection based on a fully connected deep neural network, model-drive DL for signal detection, and some experimental results. For those without block structures, we provide our recent endeavors in developing end-to-end learning communication systems. At the end of the talk, we provide some potential research topics in the area.

For any further questions, please go to the local host site to find contact information.

Dr. Geoffrey Li is a Professor with the School of Electrical and Computer Engineering at Georgia Institute of Technology. He was with AT&T Labs – Research for five years before joining Georgia Tech in 2000. His general research interests include statistical signal processing and machine learning for wireless communications.
In these areas, he has published around 500 referred journal and conference papers in addition to over 40 granted patents. His publications have cited by 35,000 times and Thomson Reuters almost every year since 2001 have listed him as the World’s Most Influential Scientific Mind, also known as a Highly-Cited Researcher. He has been an IEEE Fellow since 2006.