SMST Seminar Series: Learning Patterns from User Interfaces to Automate Software Engineering Tasks

Wednesday, October 25, 2023 1 p.m. to 2 p.m.

In response to the growing complexity of software systems, the field of software engineering research has seen a recent focus on automating various development tasks in an attempt to facilitate or augment the abilities of engineers. Driving this line of work is a combination of deep learning techniques and the large amount of open-source data available in software repositories. In this talk, Dr. Kevin Moran will discuss his group’s research agenda in leveraging Deep Learning to build the next generation of automated developer tools.

Speaker Bio: Kevin Moran is an Assistant Professor of Computer Science and a member of the Cybersecurity & Privacy (CyberSP) Cluster at UCF. He directs the SAGE research group. He graduated with a B.A. in Physics from the College of the Holy Cross in 2013, an M.S. and Ph.D. from William & Mary in 2015 and 2018 respectively. His main research interest involves facilitating the processes of software engineering, security, and maintenance by building developer tools enhanced by machine learning. He has published over 30 papers at various software engineering and security conferences, and his research has been recognized with ACM SIGSOFT distinguished paper awards at ESEC/FSE 2019 and ICSE 2020, and a Best Paper Award at CODASPY’19. He was also recently recognized with the 2023 MOBILESoft Rising Star Award. More information is available at http://www.kpmoran.com.

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Partnership III Building: 233

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Speaker/Lecture/Seminar

Tags:

modeling and simulation Software Engineering User Interfaces Deep Learning Cybersecurity