Pooyan Jamshidi

Registered user since Tue 19 Sep 2017

Name:Pooyan Jamshidi
Bio:

Pooyan Jamshidi is an Assistant Professor in the Computer Science and Engineering Department at the University of South Carolina and a Visiting Researcher at Google. He directs the AISys Lab, where he—with his students, postdocs, and collaborators—designs theoretically principled AI algorithms and applies the algorithms to solve problems in computer systems, software engineering, robotics, self-adaptive and autonomous systems, on-device machine learning, cloud-based and serverless systems, big data analytics pipelines, and healthcare. He is, in particular, interested in causality, transfer learning, optimization, causal/deep representation learning, machine learning security, reinforcement learning, as well as several areas in computer systems research, including performance, configuration, computer architecture. Prior to his current position, he was a research associate at Carnegie Mellon University and Imperial College London. He received a Ph.D. in Computer Science at Dublin City University in 2014 and M.S. and B.S. degrees in Systems Engineering, Mathematics, and Computer Science from Amirkabir University in 2003 and 2006n respectively.

Country:United States
Affiliation:University of South Carolina
Research interests:Computer Systems, Machine Learning, Software Engineering

Contributions

ICSE 2024 Committee Member in Research Track within the Research Track-track
SEAMS 2023 Program Co-Chair in Organizing Committee
Program Co-Chair in Program Committee within the Research Track-track
ASE 2022 Committee Member in Program Committee within the Artifact Evaluation-track
ECSA 2022 Committee Member in Program Committee within the Research Papers-track
ICSE 2022 Author of On Debugging the Performance of Configurable Software Systems: Developer Needs and Tailored Tool Support within the Technical Track-track
Session Chair of BoF 3: Causal AI for Software (part of Birds of a Feather)
Committee Member in Program Committee within the NIER - New Ideas and Emerging Results-track
SEAMS 2022 Committee Member in Steering Committee within the SEAMS 2022-track
Committee Member in Program Committee within the SEAMS 2022-track
Social Media Chair in Organizing Committee within the SEAMS 2022-track
Session Chair of Learning (part of SEAMS 2022)
Ordinary PC member in Doctoral Symposium Committee within the SEAMS 2022-track
ASE 2021 Committee Member in Program Committee within the Artifact Evaluation-track
ECSA 2021 Ordinary PC member in Program Committee within the Research Papers-track
ICSE 2021 Author of Whence to Learn? Transferring Knowledge in Configurable Systems using BEETLE within the Journal-First Papers-track
Author of White-Box Analysis over Machine Learning: Modeling Performance of Configurable Systems within the Technical Track-track
SEAMS 2021 Session Chair of Session 6: Uncertainty and Fairness (part of SEAMS 2021)
Committee Member in Program Committee within the SEAMS 2021-track
ASE 2020 Speaker of Machine Learning meets Software Performance: Optimization, Transfer Learning, and Counterfactual Causal Inference within the Tutorials-track
ECSA 2020 Author of VisArch: Visualization of Performance-based Architectural Refactorings within the Research Papers-track
Committee Member in Program Committee within the Research Papers-track
ICSE 2020 Session 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)
SEAMS 2020 Committee Member in Program Committee within the SEAMS 2020-track
Session Chair of Session 1: AI, Machine Learning and Statistics (part of SEAMS 2020)
ICGSE 2020 Committee Member in Program Committee
SEAMS 2019 Program 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
ICGSE 2019 Author of Understanding Similarities and Differences in Software Development Practices Across Domains within the ICGSE 2019 Research Papers-track
ESEC/FSE 2018 Author of Learning to Sample: Exploiting Similarities Across Environments to Learn Performance Models for Configurable Systems within the Research Papers-track
SEAMS 2018 Committee Member in Program Committee within the SEAMS 2018-track
TechDebt 2018 Author of Evaluating Domain-Specific Metric Thresholds: An Empirical Study within the TechDebt 2018-track