[ugrads] Fwd: Can you share with students and faculty please?

Gladys Collins collinsg at iit.edu
Fri Jul 27 10:35:21 CDT 2018

---------- Forwarded message ----------
From: Dawn DeBartolo <debartolo at iit.edu>
Date: Fri, Jul 27, 2018 at 9:45 AM
Subject: Can you share with students and faculty please?

The 4th International Conference on Big Data Computing and Communications
(BIGCOM) is to be held at the MTCC Auditorium, Illinois Tech on August 7-9.
Computer scientists from all over the world are coming here to share their
most cutting-edge researches in various areas ranging from deep learning
and artificial intelligence to cybersecurity and blockchain. All the
Illinois Tech faculty and students are welcome to attend the conference to
gain insights, network with researchers, and enjoy free food and beverage.
For more details about the conference, please take a look at the attached
Keynote 1

*Title:* Scalable Algorithms in the Age of Big Data, Network Sciences, and
Machine Learning

*Speaker:* Shang-Hua Teng

*Abstract:* In the age of network sciences and machine learning, efficient
algorithms are now in higher demand more than ever before. Big Data
fundamentally challenges the classical notion of efficient algorithms:
Algorithms that used to be considered efficient, according to
polynomial-time characterization, may no longer be adequate for solving
today's problems. It is not just desirable, but essential, that efficient
algorithms should be scalable. In other words, their complexity should be
nearly linear or sub-linear with respect to the problem size. Thus,
scalability, not just polynomial-time computability, should be elevated as
the central complexity notion for characterizing efficient computation.
Using several basic tasks in network analysis, social influence modeling,
machine learning, and optimization as examples - in this talk - I will
highlight a family of fundamental algorithmic techniques for designing
provably-good scalable algorithms.

*Speaker Biography:* Shang-Hua Teng is the University Professor and Seeley
G. Mudd Professor of Computer Science and Mathematics at the University of
Southern California. He has twice won the prestigious Godel Prize in
theoretical computer science, first in 2008, for developing the theory of
smoothed analysis, and then in 2015, for designing the groundbreaking
nearly-linear time Laplacian solver for network systems. Citing him as,
"one of the most original theoretical computer scientists in the world",
the Simons Foundation named Teng a 2014 Simons Investigator, for pursuing
long-term curiosity-driven fundamental research. Prior to joining USC in
2009, he was a professor at Boston University. He has also taught at MIT,
the University of Minnesota, and the University of Illinois at
Urbana-Champaign. He has worked at Xerox PARC, NASA Ames Research Center,
Intel Corporation, IBM Almaden Research Center, Akamai Technologies,
Microsoft Research Redmond, Microsoft Research New England and Microsoft
Research Asia. Teng is a Fellow of the Association for Computing Machinery
(ACM), as well as an Alfred P. Sloan fellow.

Keynote 2

*Title:* Reliability and efficiency problems in cloud and data-processing

*Speaker:* Shan Lu

*Abstract:* Cloud and data-processing systems are pervasive nowadays. High
reliability and efficiency of these systems are crucial and yet difficult
to achieve. This talk will discuss a variety of unique reliability and
efficiency problems in programming cloud infrastructure and data-processing
software systems. We will first look at empirical studies that help
understand these real-world problems, and then discuss techniques that help
tackle these problems.

*Speaker Biography:*  Shan Lu is an Associate Professor in the Department
of Computer Science at the University of Chicago. She received her Ph.D. at
University of Illinois, Urbana-Champaign, in 2008. She was the Clare Boothe
Luce Assistant Professor of Computer Sciences at University of Wisconsin,
Madison, from 2009 to 2014. Her research focuses on software reliability
and efficiency, particularly detecting, diagnosing, and fixing functional
and performance bugs in large software systems. Shan has won Alfred P.
Sloan Research Fellow in 2014, Distinguished Alumni Educator Award from
Department of Computer Science at the University of Illinois in 2013, and
NSF Career Award in 2010. Her co-authored papers won Google Scholar Classic
Paper 2017, Best Paper Awards at USENIX OSDI 2016 and USENIX FAST 2013,
ACM-SIGSOFT Distinguished Paper Awards at ICSE 2015 and FSE 2014, an
ACM-SIGPLAN Research Highlight Award at PLDI 2011, and an IEEE Micro Top
Picks in ASPLOS 2006. Shan is also a member of the informal ASPLOS Hall of
Fame. Shan currently serves as the Vice Chair of ACM-SIGOPS (2015--) and
the Associate Editor for IEEE Computer Architecture Letters. She also
served as the technical program co-chair for USENIX Annual Technical
Conference in 2015 and ACM Asia-Pacific Systems Workshop in 2018.

[image: image.png]

Peng-Jun Wan, Chair
Kevin Jin, Jianwei Qian, Local Arrangement Chairs
Attachments area

*Dawn DeBartolo*

*Administrative Associate*

*Computer Science Department*

*Stuart Building, Room 236C*

*10 West 31st Street*
*Chicago, Illinois  60616*
*Illinois Institute of Technology*

*debartolo at iit.edu <debartolo at iit.edu>*
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