Graduate Students have a variety of research opportunities available to them. For additional information, contact Professor A. Banihashemi, the Associate Chair of Graduate Studies.
MASc and PhD Students
Students enrolled in the MASc and PhD programs typically engage in research with their supervisor. In addition to formal supervisor based research opportunities, students may also consider fellowships and other projects included below. Many faculty members will list projects via their personal websites which can be found here: Systems and Computer Engineering Faculty, Cross-Appointed Faculty, and Adjucts.
- Fellowships
Ericsson-Carleton 5G Fellowships
A number of fellowships offered by Ericsson are available to outstanding graduate students at both MASc and PhD levels. In addition to attractive financial support, these fellowships provide excellent opportunities to collaborate with Ericsson on a variety of interesting projects. Whether you are already a graduate student at the SCE Department or still considering our gradate programs, you can apply to the Ericsson-Carleton 5G Fellowships from here. For further information, you can contact your supervisor or the Associate Chair for Graduate Studies (gchair@sce.carleton.ca).
- 2022-2023 Research Projects
-
| Project |
Machine Learning applied to Network Management |
| Supervisor |
Dr. B. Esfandiari |
| Website |
https://carleton.ca/nmai/ |
| Student Category |
MASc/PhD |
| Project Description |
The goal of the project is to apply machine learning techniques to logs of network management traces, and to extract rules that can automate some of the more repetitive tasks of a human operator. The provided data may need to be cleaned and pre-processed in order to be usable by a machine learning algorithm. The choice of the algorithm is up to you, but needs to be justified given the nature of the data. Relevant metrics should be used to assess the performance of your algorithm. |
| Pre-requisite |
students must have taken, and excelled at, one of the machine learning or pattern classification courses offered in the program. |
| Project |
Ultrasound imaging and measurements for biomedical applications |
| Supervisor |
Dr. Yuu Ono |
| Website |
www.sce.carleton.ca/faculty/ono |
| Student Category |
MASc/PhD |
| Project Description |
R&D on ultrasonic sensors, methods, system and signal processing for tissue characterization, biomedical monitoring and diagnosis. The projects include (but not limited to): muscle monitoring and characterization, cardiovascular monitoring including artery diameter tracking and measurement, ultrasound elastography. |
| Project |
Multiple Projects |
| Supervisor |
Dr. Jason Jaskolka |
| Website |
https://carleton.ca/cybersea/positions-available/ |
| Student Category |
MASc/PhD |
| Project Description |
The Cyber Security Evaluation and Assurance (CyberSEA) research lab is looking for suitable candidates with research interests and background in one or more of the following areas, including but not limited to, cyber security evaluation and assurance, threat modeling, security-by-design, and formal methods and data-driven approaches for software and security engineering.
Please see the above project inventory for more details. |
| Project |
Resource Management on BigData Processing Platforms |
| Supervisor |
Dr. S. Majumdar |
| Website |
www.sce.carleton.ca/faculty/majumdar.html |
| Student Category |
MASc/PhD |
| Project Description |
Research on various issues underlying allocation and scheduling is underway. The focus of attention is parallel processing systems including MapReduce/Hadoop, Spark and specialized stream processing platforms. |
| Project |
Machine learning for biomedical informatics |
| Supervisor |
Dr. J. Green |
| Website |
www.sce.carleton.ca/faculty/green |
| Student Category |
MASc/PhD |
| Project Description |
The cuBIC lab has several ongoing projects applying machine learning to problems in biomedical informatics. These include both medical informatics (e.g. patient monitoring in the NICU) and bioinformatics (e.g. protein/RNA analysis). |
MEng Students
MEng students have the opportunity to engage in a course based project with a faculty member in the Department of Systems and Computer Engineering. In this course, MEng students collaborate with a professor to conduct an engineering study, analysis, and/or design project. Learn more about MEng Projects.
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