Data Intensive Software Analytics (DISA)
We conduct research on the development of intelligent software systems using machine learning and natural language processing that focus on addressing critical problems within technical, social, and organizational contexts of software development teams. As such, our research work often lies at the intersection of software engineering, data science, human computer interaction, and social science.
AI4SE: AI for Software Documentation and Dependability
Combine Machine Learning (ML), Natural Language Processing (NLP), and Software Engineering (SE) techniques to automatically analyze and improve software dependability (e.g., software security vulnerability analysis and detection), reliability (e.g., program repair), and documentation (e.g., software review and insight summarization, produce better quality software library documentation).
SE4AI: Software Engineering for Machine Learning Application
Improving the design, engineering, continuous integration, and maintenance by ensuring quality control (security, fairness/bias, explainability, robustness, drift and decay, etc.) of Machine Learning Software Application (MLSA) based on an incorporation of MLSA specific attributes into traditional software development life cycles (SDLC).
Using statistical, machine learning, and natural language processing techniques to analyze, synthesize, and fuse vast amount of software repository data (e.g., crowd-sourced/internal software forums, code repositories, issue tracking and code reviews) to derive active and passive insights that could be useful for various software teams and stakeholders.
- Junaed Younus Khan (MSc from Spring 2021)
Notes to Prospective Students
I have openings for multiple full-funded Masters and PhD student positions under my supervision at the ECE department of University of Calgary. Please feel free to send me your CV, along with your academic transcripts and a list of your publications (if any).
My students (whom I had the opportunity to co-supervise informally last year) have published/submitted in reputed journals. One of the work is recently featured in BBC news and interviewed by multiple news sites and blogs.
University of Calgary is among the top six ranked research universities in Canada. Calgary is the third largest city in Canada. Calgary is a vibrant and beautiful city, surrounded by mountains. Calgary has a multi-cultural population. Calgary is focusing extensively on data science skills to diversify its Economy towards a data-centric entrepreneur culture. This is a great time to be in Calgary and to be in Canada.
The students need to be self-motivated and hardworking. It’s ideal for the students to have good programming background, such as in Python, R, Java, etc. In addition, previous experience in machine learning will be considered as an asset. It’s important for the students to have good communication skills through wrteup and presentations.