Latest News

Sep. 11th, 2023
Mr Yun Peng won the distinguished paper award in the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE 2023). Congratulations!
May. 14th, 2023
Six papers were accpeted by ICSE 2023! Congratulations to the authors!
Sep. 11th, 2023
Seven papers were accpeted by ASE 2023! Congratulations to the authors!
May. 26th, 2021
Prof. Lyu will give a keynote talk "Reliability-Driven AIOps for Cloud Resilience" at ICSE2021.
Sept. 30th, 2020
Prof. Lyu was awarded The 13th Guanghua Engineering Science and Technology Award
Jan. 14th, 2019
Prof. Lyu appears in The AI 2000 Most Influential Scholars Annual List
Oct. 28th, 2019
Prof. Lyu's paper “A coverage analysis tool for the effectiveness of software testing” was selected as one of the ISSRE 30-year most influential papers
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ARISE Lab at CUHK

ARISE (Automated Reliable Intelligent Software Engineering) Lab is led by Prof. Michael R. Lyu. We are mainly interested in four research areas of software engineering:

  • AIOps (Artificial Intelligence for IT Operations)
  • AIDev (Artificial Intelligence for Development)
  • RobustAI (Robust Artificial Intelligence)
  • NLP (Natural Language Processing)
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Research Areas of ARISE Lab

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AIDev

AIDev studies intersection at machine learning, static analysis, programming languages, and software engineering.

  • Type Inference
  • Code Representation Learning
  • Code Search
  • API Recommendation
  • API Misuse Detection
  • Vulnerability Detection
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AIOps

AIOps combines big data and machine learning to automate IT operations processes via data-driven approaches in large-scale systems.

  • Log/KPI/Alert/Trace Analysis
  • Incident & Tickets Management
  • Failure Diagnosis
  • Root Cause Localization
  • AIOps Knowledge Graph
  • Microservice & Serverless Computing
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RobustAI

RobustAI aims to understand and improve the trustworthiness and robustness of machine learning systems.

  • Deep Learning Model Testing
  • Adversarial Attack
  • Adversarial Defense
  • Robust training for CV & NLP
  • Deep Learning Model Interpretability
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NLP

Extract information and insights contained in natural languages. Enable a series of NLP applications.

  • Natural language semantics understanding
  • Meaningful natural language generation
  • Other NLP tasks: translation, question answering, model compression, etc.