Pooyan Jamshidi

Registered user since Tue 19 Sep 2017

Name: Pooyan Jamshidi

Bio: Pooyan Jamshidi is an Assistant Professor at the University of South Carolina. He directs the AISys Lab, where he investigates the development of novel algorithmic and theoretically principled methods for machine learning systems. Prior to his current position, he was a research associate at Carnegie Mellon University and Imperial College London, where he primarily worked on transfer learning for performance understanding of highly-configurable systems including robotics and big data systems. Pooyan’s general research interests are at the intersection of systems/software and machine learning. He received his Ph.D. in Computer Science at Dublin City University in 2014, and M.S. and B.S. degrees in Computer Science and Math from the Amirkabir University of Technology in 2003 and 2006 respectively.

Country: United States

Affiliation: University of South Carolina

Personal website: http://pooyanjamshidi.github.io

Research interests: Software Engineering, Systems, Machine Learning

Contributions

ECSA 2020Author of VisArch: Visualization of Performance-based Architectural Refactorings within the Research Track-track
Committee Member in Program Committee within the Research Track-track
ICGSE 2020Committee Member in Program Committee
SEAMS 2020Committee Member in Program Committee within the SEAMS 2020-track
Session Chair of Session 1: AI, Machine Learning and Statistics (part of SEAMS 2020)
ICGSE 2019Author of Understanding Similarities and Differences in Software Development Practices Across Domains within the ICGSE 2019 Research Papers-track
SEAMS 2019Program Committee in Program Committee within the SEAMS 2019-track
Author of Machine Learning Meets Quantitative Planning: Enabling Self-Adaptation in Autonomous Robots within the SEAMS 2019-track
ICSE 2020Session Chair of A11-Performance and Analysis (part of Paper Presentations)
Programme Committee in Program Committee within the Technical Papers-track
Session Chair of I5-Deep Learning Testing and Debugging (part of Paper Presentations)
TechDebt 2018Author of Evaluating Domain-Specific Metric Thresholds: An Empirical Study within the TechDebt 2018-track
SEAMS 2018Committee Member in Program Committee within the SEAMS 2018-track
ESEC/FSE 2018Author of Learning to Sample: Exploiting Similarities Across Environments to Learn Performance Models for Configurable Systems within the Research Papers-track