I am currently working toward my PhD in computer science at the University of Southern California. I am a member of the SoftArch research group under the supervision of Prof. Nenad Medvidovic. Before joining USC, I graduated from University of Tehran (Iran) with a bachelor's degree in computer engineering in 2019. My research interest lies at the intersection of Software Engineering, HCI, and Machine learning, and focuses on automated functional testing of mobile applications using UI understanding.
Saghar Talebipour
941 Bloom Walk, SAL 339
Los Angeles, CA 90089 US
(213) 465 9357
talebipo[at]usc[dot]edu
Doctor of Philosophy in Computer Science • Expected 2024
GPA: 4.0/4.0
Bachelor of Science in Computer Engineering• 2019
GPA: 18.06/20 (3.77/4.0)
Software Engineering Intern • May 2022 - Aug 2022
Revamped the indexing pipeline infrastructure for Snap search team resulting in increased resiliency and significant cost saving. Also, designed an intelligent scheduling service for execution of jobs responsible for building large size indices.
Research Assistant• May 2019 - Present
Conducting research at the intersection of software engineering , HCI, and machine learning focused on automated testing, and UI understanding. Please refer to Selected Projects and Publications sections for more information on my research projects and papers.
Software Engineering Intern• May 2017 - May 2018
Participated in implementing a hotel management system with more than 200 RESTful APIs. This system was the first cloud ERP solution in the tourism industry in Iran. Also, implemented the admin dashboard and reporting system for a reservation platform connecting hotels and travel agencies.
Built a framework for automatically generating usage-based UI tests by learning execution patterns from video recordings of apps by leveraging AI-assisted (computer vision and NLP) techniques using Python and Pytorch.
Built a cross-platform UI test transfer tool leveraging image feature detection and text embedding matching using Python. The tool achieved 76% accuracy and reduced manual effort needed for testing by more than half (55%).
AVGUST: A Tool for Generating Usage-Based Tests from Videos of App Executions S. Talebipour, H. Park, K. Baral, L. Yee, S. Khan, k. Moran, Y. Brun, N. Medvidovic, Y. Zhao In proceedings of the 45th International Conference on Software Engineering (ICSE 2023 - demo track). [PDF]
Avgust: automating usage-based test generation from videos of app executions (*Co-First-Authors) Y. Zhao*, S. Talebipour*, K. Baral, H. Park, L. Yee, S. Khan, Y. Brun, N. Medvidovic, k. Moran In proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2022). [PDF]
UI Test Migration Across Mobile Platforms S. Talebipour, Y. Zhao, L. Dojcilović, C. Li, N. Medvidović In proceedings 2021 36th IEEE/ACM International Conference on Automated Software Engineering (ASE 2021). [PDF]
Remote control of ios devices via accessibility features N Lukić, S Talebipour, N Medvidović. In proceedings of the 2020 ACM Workshop on Forming an Ecosystem Around Software Transformation (FEAST 2020).[PDF]
AirMochi: a tool for remotely controlling iOS devices N Lukić, S Talebipour, N Medvidović. In proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering (ASE 2020) . [PDF]
Databases: MySQL, MongoDB
Frameworks: Node.js, Spring, Hibernate, React
Technologies: Kubernetes, Elasticsearch, Kibana, AWS, MATLAB, Git
Testing: Appium, JUnit, Familiar with A/B testing