[CPCC] Distinguished Seminar by Prof. Georgios Giannakis on Thu Feb 26

hamidj hamidj at uci.edu
Sun Feb 8 20:59:08 PST 2015


Title: Learning Tools for Big Data Analytics

Speaker: Georgios Giannakis

Date: Thu. Feb. 26, 2015

Time: 11:00 AM

Venue: Harut Barsamian Colloquia (Engineering Hall 2430)

ABSTRACT

We live in an era of data deluge. Pervasive sensors collect massive 
amounts of information on every bit of our lives, churning out enormous 
streams of raw data in various formats. Mining information from 
unprecedented volumes of data promises to limit the spread of epidemics 
and diseases, identify trends in financial markets, learn the dynamics 
of emergent social-computational systems, and also protect critical 
infrastructure including the smart grid and the Internet’s backbone 
network. While Big Data can be definitely perceived as a big blessing, 
big challenges also arise with large-scale datasets. The sheer volume of 
data makes it often impossible to run analytics using a central 
processor and storage, and distributed processing with parallelized 
multi-processors is preferred while the data themselves are stored in 
the cloud. As many sources continuously generate data in real time, 
analytics must often be performed “on-the-fly” and without an 
opportunity to revisit past entries. Due to their disparate origins, 
massive datasets are noisy, incomplete, prone to outliers, and 
vulnerable to cyber-attacks. These effects are amplified if the 
acquisition and transportation cost per datum is driven to a minimum. 
Overall, Big Data present challenges in which resources such as time, 
space, and energy, are intertwined in complex ways with data resources. 
Given these challenges, ample signal processing opportunities arise. 
This seminar outlines ongoing research in novel models applicable to a 
wide range of Big Data analytics problems, as well as algorithms to 
handle the practical challenges, while revealing fundamental limits and 
insights on the mathematical trade-offs involved.

SPEAKER'S BIOGRAPHY

Georgios B. Giannakis (Fellow’97) received his Diploma in Electrical 
Engr. from the Ntl. Tech. Univ. of Athens, Greece, 1981. From 1982 to 
1986 he was with the Univ. of Southern California (USC), where he 
received his MSc. in Electrical Engineering, 1983, MSc. in Mathematics, 
1986, and Ph.D. in Electrical Engr., 1986. Since 1999 he has been a 
professor with the Univ. of Minnesota, where he now holds an ADC Chair 
in Wireless Telecommunications in the ECE Department, and serves as 
director of the Digital Technology Center. His general interests span 
the areas of communications, networking and statistical signal 
processing – subjects on which he has published more than 375 journal 
papers, 625 conference papers, 20 book chapters, two edited books and 
two research monographs (h-index 111). Current research focuses on big 
data analytics, wireless cognitive radios, network science with 
applications to social, brain, and power networks with renewables.. He 
is the (co-) inventor of 22 patents issued, and the (co-) recipient of 8 
best paper awards from the IEEE Signal Processing (SP) and 
Communications Societies, including the G. Marconi Prize Paper Award in 
Wireless Communications. He also received Technical Achievement Awards 
from the SP Society (2000), from EURASIP (2005), a Young Faculty 
Teaching Award, the G. W. Taylor Award for Distinguished Research from 
the University of Minnesota, and the IEEE Fourier Technical Field Award 
(2015). He is a Fellow of EURASIP, and has served the IEEE in a number 
of posts, including that of a Distinguished Lecturer for the IEEE-SP 
Society.


More information about the CPCC mailing list