SRC Grand Finalists 2015
GRADUATE CATEGORY
First Place:
Lu Xiao - Drexel University
FSE 2014
Title of Submission: Detecting and Preventing the Architectural Roots of Bugs
Second Place:
Shupeng Sun - Carnegie Mellon University
ICCAD 2014
Title of Submission: Fast Statistical Analysis of Rare Circuit Failure Events in High-Dimensional Variation Space
Third Place:
Omid Abara - MIT
MobiCom 2014
Title of Submission: Clock Synchronization for Distributed Wireless Protocols at the Physical Layer
UNDERGRADUATE CATEGORY
First Place:
Thomas Effland - University of Buffalo
SIGCSE - 2014
Title of Submission: Focused Retrieval of University Course Descriptions from Highly Variable Sources
Second Place:
Mitchell Gordon - University of Rochester
ASSETS - 2014
Title of Submission: Web Accessibility Evaluation with the Crowd
Third Place:
Shannon N. Lubetich - Pomona College
Grace Hopper - 2014
Title of Submission: Eve Eat Dust Mop: Measuring Syntactic Development in Child Language with Natural Language Processing and Machine Learning
ACM Case Studies
Written by leading domain experts for software engineers, ACM Case Studies provide an in-depth look at how software teams overcome specific challenges by implementing new technologies, adopting new practices, or a combination of both. Often through first-hand accounts, these pieces explore what the challenges were, the tools and techniques that were used to combat them, and the solution that was achieved.
Why I Belong to ACM
Hear from Bryan Cantrill, vice president of engineering at Joyent, Ben Fried chief information officer at Google, and Theo Schlossnagle, OmniTI founder on why they are members of ACM.
Prediction-Serving Systems
ACM Queue’s “Research for Practice” is your number one resource for keeping up with emerging developments in the world of theory and applying them to the challenges you face on a daily basis. In this installment, Dan Crankshaw and Joey Gonzalez provide an overview of machine learning server systems. What happens when we wish to actually deploy a machine learning model to production, and how do we serve predictions with high accuracy and high computational efficiency? Dan and Joey’s curated research selection presents cutting-edge techniques spanning database-level integration, video processing, and prediction middleware. Given the explosion of interest in machine learning and its increasing impact on seemingly every application vertical, it's possible that systems such as these will become as commonplace as relational databases are today.
