[2017-04-21] Prof. Michael R. Lyu, CUHK, " Small Is Beautiful, or Big Is Better?”
Title: Small Is Beautiful, or Big Is Better?
Date: 2017-04-21 2:20pm-3:30pm
Location: R103, CSIE
Speaker: Prof. Michael R. Lyu, Chinese University of Hong Kong
Hosted by: Prof. Ming Ouhyoung
Models are mathematical abstraction of real world systems, which should be made precise and concise, as Einstein’s aphorism puts it: “A
formula should be as simple as possible, but not simpler.” The traditional modeling efforts have therefore been emphasizing “small is beautiful.” However, upon arrival of the Big Data era, the current
wisdom seems to suggest “the bigger, the better.” Big Data is characterized by 4 Vs: volume, variety, velocity, and veracity, which posts enormous challenges in modeling, processing, and analyzing the massively available data in order to generate value. So is small beautiful, or big better?
Dr. Michael R. Lyu is currently a Professor in the Computer Science and Engineering department of the Chinese University of Hong Kong. He worked at the Jet Propulsion Laboratory as a Technical Staff Member from 1988 to 1990. From 1990 to 1992 he was with the Electrical and Computer Engineering Department at the University of Iowa as an Assistant Professor. From 1992 to 1995, he was a Member of the Technical Staff in the Applied Research Area of the Bell Communications Research, Bellcore. From 1995 to 1997 he was a research Member of the Technical Staff at Bell Laboratories, which was first part of AT&T, and later became part of Lucent Technologies.
Dr. Lyu's research interests include software engineering, dependable computing, distributed systems, cloud computing, mobile networking, big data, and machine learning. He has participated in more than 30 industrial projects in these areas, and helped to develop many commercial systems and software tools. He has been frequently invited as a keynote or tutorial speaker to conferences and workshops in U.S., Europe, and Asia.
Dr. Lyu received his B.S. in Electrical Engineering from National Taiwan University in 1981, his M.S. in Computer Science from University of California, Santa Barbara, in 1985, and his Ph.D. in Computer Science from University of California, Los Angeles in 1988.