Heng Li

Registered user since Sat 30 Jan 2021

Name:Heng Li
Bio:

Heng Li is an Assistant Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montreal, Montreal, Canada, where he leads the Maintenance, Operations and Observation of Software with intelligencE (MOOSE) lab. He obtained his Ph.D. from the School of Computing, Queen’s University (Canada), M.Sc. from Fudan University (China), and B.Eng. from Sun Yat-sen University (China). He also worked in industry for multiple years as a software engineer at Synopsys and as a software performance engineer at BlackBerry. His research interests lie within Software Engineering, in particular, software monitoring and observability, intelligent operations of software systems, software log mining, software performance engineering, and mining software repositories.

Country:Canada
Affiliation:Polytechnique Montréal
Personal website:https://www.hengli.org/
Research interests:Software Engineering, Software Analytics, Software Observability, Log Analytics, Performance Engineering, AIOps

Contributions

Q-SE 2022 Author of Understanding Quantum Software Engineering Challenges An Empirical Study on Stack Exchange Forums and GitHub Issues within the Q-SE 2022-track
EASE 2022 Author of Studying the Practices of Deploying Machine Learning Projects on Docker within the Research-track
MSR 2022 Committee Member in Data Showcase Committee within the Data and Tool Showcase Track-track
ASE 2022 Committee Member in Program Committee within the Artifact Evaluation-track
ASE 2021 Committee Member in Program Committee within the NIER track-track
Committee Member in Program Committee within the Late Breaking Results-track
Committee Member in Program Committee within the Artifact Evaluation-track
ESEC/FSE 2021 Author of A Qualitative Study of the Benefits and Costs of Logging from Developers' Perspectives: A Journal First Presentation Proposal within the Journal First-track
Author of Predicting Node Failures in an Ultra-large-scale Cloud Computing Platform: an AIOps Solution: A Journal First Presentation Proposal within the Journal First-track
Committee Member in Program Committee within the Artifacts-track
ICSE 2022 Author of Assisting Example-based API Misuse Detection via Complementary Artificial Examples within the Journal-First Papers-track
ICSE 2021 Author of DeepLV: Suggesting Log Levels Using Ordinal Based Neural Networks within the Technical Track-track
Author of Using black-box performance models to detect performance regressions under varying workloads: an empirical study within the Journal-First Papers-track