songlh AT ist DOT psu DOT edu
College of Information Sciences and Technology
The Pennsylvania State University
University Park, Pennsylvania 16802
I am an Assistant Professor of Information Sciences and Technology College at The Pennsylvania State University. |
My research interests span the areas of systems, security and software engineering. The goal of my research is to
help developers build more efficient, reliable and secure software systems.
I received my PhD from Wisconsin-Madison working with Prof. Shan Lu in 2015, my master in Institute of Computing |
Technology at Chinese Academy of Sciences in 2010, and my bachelor in School of Software Engineering at Huazhong
University of Science and Technology in 2007. Before joining PSU in August 2017, I spent 1.5 years at FireEye, Inc.
I am very lucky to work with outstanding students:
Tengfei Tu (Visiting Student from Beijing University of Posts and Telecommunications)
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Multiple RA and TA positions for Ph.D. and Master students starting Fall’18.
Looking for visiting scholars, visiting students, postdocs, and undergraduates at any time.
Fine-Grained Library Customization
Linhai Song and Xinyu Xing.
Performance Diagnosis for Inefficient Loops
Linhai Song and Shan Lu.
(A previous version appears as UChicago CS Technical Report TR-2016-06)
Learning from Big Malware
Linhai Song, Heqing Huang, Wu Zhou, Wenfei Wu, and Yiying Zhang.
What Change History Tells Us About Thread Synchronization
Rui Gu, Guoliang Jin, Linhai Song, Linjie Zhu, and Shan Lu.
COMP: Compiler Optimizations for Manycore Processors
Linhai Song, Min Feng, Nishkam Ravi, Yi Yang, and Srimat Chakradhar.
Best Paper Nomination
(Linhai did this work during his 2013 summer intern in NEC Laboratories America)
Statistical Debugging for Real-World Performance Problems
Linhai Song and Shan Lu.
(A previous version appears as UW-Madison CS Technical Report 1803)
Toddler: Detecting Performance Problems via Similar Memory-Access Patterns
Adrian Nistor, Linhai Song, Darko Marinov, and Shan Lu.
Understanding and Detecting Real-World Performance Bugs
Guoliang Jin*, Linhai Song*, Xiaoming Shi, Joel Scherpelz, and Shan Lu.
* both are leading authors.
Automated Atomicity-Violation Fixing
Guoliang Jin, Linhai Song, Wei Zhang, Shan Lu, and Ben Liblit.
ECON: An Approach to Extract Content from Web News Page
Yan Guo, Huifang Tang, Linhai Song, Yu Wang, and Guodong Ding.
Simultaneous Product Attribute Name and Value Extraction from Web Pages
Bo Wu, Xueqi Cheng, Yu Wang, Yan Guo, and Linhai Song.
Blog Post Extraction Using Title Finding
Linhai Song, Xueqi Cheng, Yan Guo, Bo Wu, and Yu Wang.
- ContentEx: A Framework for Automatic Content Extraction Programs
Linhai Song, Xueqi Cheng, Yan Guo, Yue Liu, and Guodong Ding.
- Performance Diagnosis for Inefficient Loops [slides]
In ICSE'2017 on MAY 25, 2017
- Learning from Big Malware [slides]
In APSys'2016 on AUG 05, 2016
- Statistical Debugging for Real-World Performance Problems [slides]
In OOPSLA'2014 on OCT 23, 2014
- Statistical Debugging for Performance Problems [slides]
In WISDOM Workshop II on May 6, 2014
- Understanding and Detecting Real-World Performance Bugs [slides]
In PLDI'2012 on July 11, 2012
MICRO 2014 Best Paper Runner Up
One of five papers selected from 273 MICRO 2014 submissions
SIGPLAN Research Highlights Award for our AFix paper
One of eight papers selected from all papers published in 13 ACM SIGPLAN conferences in 2011