To prospective graduate students (2027 Fall Admission): The FSC group welcomes passionate and dedicated bright minds to join us in a stimulating and nurturing environment. Please follow the UTIAS admissions guidelines to apply for our graduate programs, and please specify our research field of “Aircraft Flight Systems and Control” in your application file so that your application will be screened. All reviewed applicants will be contacted individually by Professor Liu to follow up with an interview or to receive feedback. Students pursuing PhD programs will be considered with priority.
Prospective graduate students are also encouraged to check the FSC group’s research theme (link tbd) and recent research projects to align their research interests in the research statement of the application. Each graduate student in the MASc or PhD program will determine their individual research topics mutually by working together with Professor Liu upon enrolment. Sometimes, the FSC may post specific research topics here for the upcoming admission cycle.
To registered UTIAS M.Eng. Students: Are you an M.Eng. student searching for a meaningful project aligned with cutting-edge aerospace technologies? The FSC group routinely offers a number of project topics that align with the M.Eng. course project requirements and guidelines. The posted M.Eng. project topics are expected to be carried out in one semester. Interested M.Eng. students are encouraged to contact Professor Liu directly to inquire about these topics within the specified timeframe. The projects are assigned on a first-come, first-served basis.
MENG Project Topics (Winter/Summer of 2027)
The following project topics are available for registered (UTIAS) M.Eng. students. The inquiry/application deadlines are: January 15th (for the winter semester) and April 15th (for the summer semester). Please contact Professor Liu by email with your CV and up-to-date transcripts. Interested M.Eng. students from other departments/institutions, please contact Professor Liu directly.
[ME1]: Student Assistant Opportunity: Aviation, Flight Simulation & AI Research (supervisor: Professor Liu, collaborator: David Dunwoody)
A PhD research project at the University of Toronto Institute of Aerospace Studies (UTIAS) is seeking an undergraduate (4th-year thesis, or summer internship) or graduate student assistant (MENG project) to help build a data-collection tool for research on human–AI teaming in aviation.
The project explores whether AI can learn to assess and appropriately trust a pilot’s performance. You will help develop an X-Plane-based [airplane model] flight-simulation environment, capture flight data, and support an online approach for recruiting and validating virtual-pilot flights.
Who we’re looking for
Someone with an interest or background in aviation, flight simulators, data analysis, software development, or human–AI interaction. Familiarity with X-Plane or pilot training is helpful, but guidance and collaboration will be provided throughout the project.
Timeline
Development is planned for Fall 2026, followed by data collection in Winter 2027. The project is also possible for summer 2027.
To learn more or express interest, contact David Dunwoody, PhD Candidate, UTIAS: david.dunwoody@mail.utoronto.ca
[ME2]: Student Research Assistant Opportunity: Autonomous Drones for Vegetation Monitoring (supervisor: Professor Liu, collaborator: Enoch Lo)
A research project at the University of Toronto Institute for Aerospace Studies (UTIAS) is seeking an undergraduate student (4th-year thesis or summer internship) or graduate student (MEng project) to contribute to the development of an autonomous multi-UAV system for precision vegetation monitoring.
The AUTONOMA-SIF project brings together aerospace engineers and plant scientists to develop a system that can autonomously identify vegetation of interest and collect measurements of solar-induced fluorescence (SIF)—a faint optical signal emitted by plants that provides valuable information about photosynthetic activity and plant health.
The Project
The system uses a leader–follower UAV configuration. The leader UAV surveys a vegetation area using a multispectral camera and identifies potential regions of interest based on vegetation health indicators. A follower UAV then autonomously travels to selected locations to perform high-precision SIF measurements. The ultimate goal is to enable a drone system that can identify areas of interest, plan its own measurements, and collect SIF data with minimal human intervention.
What You Will Work On
The project offers several opportunities for students to contribute to different aspects of the system, including:
- LiDAR-based canopy height measurement: Develop methods to estimate vegetation canopy height and maintain a consistent distance between the sensing payload and the top of the canopy, improving measurement consistency and georeferencing.
- Learning-based vegetation assessment: Investigate machine-learning methods for identifying potential points of interest from vegetation health indices and imagery.
- Multi-UAV coordination: Contribute to the planning and coordination of the leader and follower UAVs during autonomous vegetation-monitoring missions.
Who We’re Looking For
We are looking for students interested in autonomous UAVs, computer vision, machine learning, remote sensing, or environmental monitoring.
Experience with Python, ROS/ROS 2, computer vision, machine learning, LiDAR, UAVs, or image processing is helpful. Students will work closely with researchers in aerospace engineering and plant physiology, with guidance provided throughout the project.
Timeline
Development is planned for Fall 2026 and Winter 2027, with opportunities for continued development and field testing in Summer 2027.
The project can be structured as a 4th-year thesis, summer research internship, MEng project, or other student research project, depending on the student’s program and availability. Interested students are encouraged to contact Enoch Lo, PhD Student, UTIAS: enoch.lo@mail.utoronto.ca
To undergraduate students: Are you an undergraduate student looking to gain hands-on research experience or seeking a thesis project that makes a real impact? The FSC group routinely offers a number of research topics that are custom-built for undergraduate students based on the group’s ongoing research project needs. The students will actively work with the FSC graduate students to carry out research tasks.
Undergraduate (summer 2026, 4th-year thesis 2026-27) Research Topics
The following research topics are available for UofT’s Engineering Science for all three streams: Aerospace, Robotics, and Machine Learning (or other engineering programs).
(No available opportunity is available at this time)
Interested students are encouraged to reach out early, as positions are limited and competitive.