Research Positions

There are currently several ongoing research projects in the MuLab, and we will be able to accommodate 1-2 NSERC USRA students for the summer of 2023, depending on the topic.

Preliminary details on each of the projects are provided here, but please feel free to [reach out to Prof Muise] for more information.
Scope 1-2 students
Deadline February 10, 2023
Important Prior knowledge in any of the specific project areas is not required.
Note Currently, these positions are restricted to potential NSERC USRA students. This means that you must be a Canadian Citizen to apply. We hope to open them up more broadly later in the semester.

Dialogue Agents

Dialogue agents, chatbots, conversational agents, etc. It’s big business these days, but hard to scale. Research in the MuLab aims at improving this sub-area of AI through the use of planning techniques to generate large and complex dialogue agents that are verifiably correct and explainable – essential elements for any agent deployed in a business context. This project will involve building a core framework for dialogue agent design through the use of planning technology, and specifically pulling together several research threads into a compelling interface for dialogue agent design and analysis.

Learning Constraints for SAT/CSPs

SAT and CSP models are some of the world’s best solution techniques for highly complex and combinatoric problems. E.g., scheduling the shifts for an entire hospital. In this project, we will explore the idea of data-driven analysis of existing schedules, in order to infer which constraints may have been used to generate them. This flips the common problem of specifying constraints to solve problems on its head – we have the solutions, and want to know which constraints were used.

Model Acquisition

Model acquisition is the process of automatically learning a model from data. The MuLab has spearheaded an initiative to categorize and reproduce the state-of-the-art in model acquisition, the MAcq Project. This project will involve working with the MAcq team to reproduce and extend the state-of-the-art in model acquisition, and to contribute to the MAcq project through new techniques for analyzing acquired models.

Autonomous Agriculture

The MuLab, along with the Machine Intelligence & Biocomputing (MIB) Laboratory, are building a lab-scale platform for the exploration of autonomous agriculture. This will include sensors such as video feeds, nutrient detection, etc., and include actuators such as lighting, watering, etc. This project will involve working with the MIB lab and MuLab to prototype the initial software for the first iteration of the system being built in the winter term.

Epidemiological Modelling

The MuLab has ongoing research with the One Health Modelling Network for Emerging Infections (OMNI). This project will involve working with existing agent-based models of infectious disease spread, and extending them to include new functionality such as rapid geographic mirroring (connecting to location data), hierarchical abstractions, etc.

Application Procedure

To apply for the above project, please email Prof. Muise with the following details (there are several parts, but all of them should be brief):

  1. Your name and a bit of background about yourself.

  2. The project(s) name and expression of your interest in the area.

  3. Your (unofficial) Queen’s transcript.

  4. If you are Canadian (affects funding sources you may be eligible for).

  5. If you have taken CISC 204 with Prof Muise and completed a project, please provide a link to the project and briefly describe what your group did.

  6. (if available) A CV/Resume

  7. (if available) A link to any software/projects you’ve worked on (e.g., GitHub profile).

  8. At least one of the roles is reserved for a member of an underrepresented group (race/ethnicity, gender, sexual orientation, disability, etc.). Please self-identify what underrepresented/minority group(s) you belong to if you feel comfortable doing so and you would like to be considered for this position.

We will reach out to interested students and possibly interview if there is high demand for the project. If necessary, the interview process will involve a small coding exercise as well as meeting with Prof. Muise and/or Mu Lab members.