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Gail E. Kaiser is a Professor of Computer Science at Columbia University. She conducts research in software engineering and security from a systems perspective, focusing on program analysis and software testing. Her current work ranges across both static and dynamic program analysis techniques, and across source code and executable (bytecode/binaries) targets. She also investigates machine learning techniques to solving software engineering problems (AI4SE).
In the 1980s and 1990s, Kaiser investigated semantics-focused extensions to language-based editors and process-oriented team software development environments, forerunners to today’s IDEs and Continuous Integration, and in the late 1990s and early 2000s she investigated self-adaptation for the then-emerging cloud computing, particularly techniques for retrofitting legacy systems. Since then she has concentrated on testing and analysis. Beginning with her sabbatical at Columbia’s Center for Computational Learning Systems in 2005-2006, Kaiser and her former PhD student Chris Murphy were among the first to adapt software engineering testing techniques, particularly metamorphic testing, to finding bugs in machine learning software (SE4AI). Prof. Kaiser received her PhD from CMU and her ScB from MIT.
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