Once every week while school is in session, EECS invites a distinguished researcher or practitioner in a computer science or electrical and computer engineering-related field to present their ideas and/or work. Talks are generally targeted to electrical engineering and computer science graduate students. This colloquium series is free and open to everyone.

Upcoming Colloquia

Designing Communication Receivers Using Machine Learning Techniques

Monday, November 20, 2017 - 4:00pm to 4:50pm
LPSC 125

Speaker Information

Brian M. Kurkoski
Associate Professor
Japan Advanced Institute of Science and Technology

Abstract

Your smartphone has many communications receivers, not only in its various wireless interfaces, but in the flash memory controller as well.  In fixed-precision VLSI receivers, reducing the number of bits used to represent messages will reduce power consumption and increase battery life. This presentation describes the design of fixed-precision receivers from an information theory perspective. This can be called "hardware-aware information theory" because the objective is to maximize mutual information (an information theory quantity) while minimizing the number of message bits (in the hardware implementation).  Results from machine learning play a key role, because quantization can be seen as classification.  Numerical results show that LDPC decoders based on the proposed max-LUT method can outperform belief-propagation decoders.

Speaker Bio

Brian M. Kurkoski is an Associate Professor at the Japan Advanced Institute of Science and Technology (JAIST) in Nomi, Japan. Born in Portland, Oregon, he received the B.S. degree from the California Institute of Technology in 1993, and then worked at two California startups. He received the M.S. and Ph.D. degrees from the University of California San Diego in 2000 and 2004, respectively. He received a JSPS Postdoctoral Fellowship from 2004 to 2006, while at the University of Electro-Communications in Tokyo, Japan, where he continued as Associate Professor from 2007 to 2012. He has been at JAIST since 2012. He was an associate editor for IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences from 2010 to 2014. He is chair of the Data Storage Technical Committee, a technical committee of the IEEE Communications Society for 2017–2018, and was secretary for 2013–2016.

Helping to improve the quality of software systems by inferring defects using static and dynamic analysis

Monday, November 27, 2017 - 4:00pm to 4:50pm
LPSC 125

Speaker Information

Iftekhar Ahmed
Oregon State University

Abstract

Software will always have bugs, and as software continues to become a more and more pervasive part of our lives, software failures will continue to affect more people than ever. In the absence of a major breakthrough in model checking or formal verification, improving and checking software quality requires a statistical approach; our confidence in our systems depends on our confidence in the exhaustiveness of our testing. As software systems get more complex, the task of exhaustive testing becomes more complex. In order to build less error prone systems, we therefore need to not only focus on quickly and efficiently identifying bugs through testing, but also on identifying factors associated with bugs in order to prevent them in the first place. Software development is a complex process that requires coordination between individuals and technology, and as we look to predict and prevent faults, we need to examine the effect that socio-technical factors have on code quality. In this talk, I present my research on identifying factors that are associated with software faults. I also present my work on improving the effectiveness of testing to automatically uncover bugs in complex real-world systems to build better quality software.

Speaker Bio

Iftekhar Ahmed is a Ph.D. candidate in Computer Science at Oregon State University doing research in Software Engineering, with a focus on combining testing, static analysis and machine learning approaches to help improve software quality under real-world conditions. His Ph.D. work on improving the effectiveness of mutation analysis for large-scale real-world systems has helped to identify a number of bugs in the Linux kernel. The improvements resulting from his work have been incorporated into the Linux mainline distribution with more than 2 Billion instances running worldwide from mobile phones to data centers. He is a two-time recipient of the IBM Ph.D.
fellowship, and his current research is funded by IBM. More info about him can be found at:
http://www.iftekharahmed.info

Past Colloquia

John Wager
Monday, November 6, 2017 - 4:00pm to 4:50pm
Danny Dig
Monday, October 16, 2017 - 4:00pm to 4:50pm
Sriraam Natarajan
Monday, October 9, 2017 - 4:00pm to 4:50pm
J.-C. Chiao
Monday, October 2, 2017 - 4:00pm to 4:50pm
Christopher Scaffidi
Monday, September 25, 2017 - 4:00pm to 4:50pm
John F. Wager
Monday, May 22, 2017 - 4:00pm to 4:50pm
Tuesday, May 16, 2017 - 11:30am to 12:30pm

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