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FBIT project summaries

Supervisors  

Andrew Hogue

Miguel V. Martin Bill Kapralos Pejman Mirza-Babaei Amirali Salehi-Abari
Khalil El-Khatib Shahram S. Heydari Karthik Sankaranarayanan Ana Duff Amir Rastpour
Serena Sohrab Alvaro Uribe Quevedo Samaneh Mazaheri Stephen Marsh Loutfouz Zaman


 

 
 
 
 
 
 
 
Supervisor name:  Andrew Hogue, PhD

Project title:
  Virtual Materiality: Advancing Art with Simulation

Summary of research project:  One of the major challenges being explored is how we can enhance the user experience in Virtual Reality for traditional artists (for example sculptors and painters) and define interfaces that mimic the real artist processes more closely. To do so, this project explores a hybrid volumetric and particle-based real-time fluid dynamic simulation that unifies the data representation between virtual paint and virtual clay. To increase the realism of the simulation, we must ensure that our underlying representation of the paint medium expresses both the dynamic properties (e.g. movement) as well as the static properties of fluids (e.g.translucency, colour mixing, texture, thickness).

Student responsibilities/tasks:  Students will be involved in working with our team of artists and programmers to develop a methodology for scientifically acquiring empirical data on how real clay deforms under specific forces and aiding Masters student researchers in developing software and models for utilizing this data in Virtual Reality simulation.

Student qualifications required (e.g. courses completed, minimum grades, etc.):

  • Students should have a good grasp of computer graphics techniques and a knowledge of C++/C# programming is preferred.
  • Familiarity with Virtual Reality developing in Unity or Unreal is preferred.
  • Students must be able to work as a team and be independently curious.

 Expected training/skills to be received by the student:

  • Unity or Unreal Development
  • C#/C++ Programming Knowledge

Award available:  Ontario Tech STAR Award or NSERC USRA 


Supervisor name:  Miguel V. Martin, PhD
Project title:  Artificial Intelligence for Systems Authentication

Summary of research project:  This project studies several aspects of computer security that artificial intelligence (AI) can help approach. Conversely, the project also considers securing AI systems. For example, we’ll study the use of AI in estimating password strength more accurately than existing conventional meters, or use AI to improve the way passwords are assigned to users, or the security of automatic speech recognition (ASR) systems including popular APIs such as IBM, Amazon, Google services, or Tesla. The successful student will learn machine learning techniques to enable AI, as well as understanding computer security concepts and current problems in this area that are of interest to the research community.

Student responsibilities/tasks:  The Undergraduate Research Award student will be responsible for developing a set of tools to enable password strength meters (PSM) based on artificial intelligence (AI), and will lay the basis to test such PSMs with human participants to determine their usability. Alternatively, the student will work on techniques to secure automatic speech recognition (ASR) systems. Prof. Martin will help the student conduct security analyses of these systems.

Student qualifications required (e.g. courses completed, minimum grades, etc.):

  • 3rd or 4th year is preferred.
  • Has taken at least one course on machine learning.
  • Knows, or feels confident learning Python.
  • Excellent verbal and written communication skills.
  • Excellent interpersonal skills.

Expected training/skills to be received by the student:

The successful student will learn machine learning techniques to enable AI. This includes Python skills for data science, Scikit-Learn, TensorFlow with Keras, and other machine learning libraries and tools. 

The successful student will also achieve a thorough understanding of state-of-the-art computer security concepts as well as current problems in this area that are of interest to the research community at large. 

Award available:  Ontario Tech STAR Award or NSERC USRA


Supervisor name:  Bill Kapralos, PhD

Project title:
  Virtual simulations and serious games for medical education

Summary of research project:  Substance use disorder (i.e., addiction) can be defined as a dependence on a legal (e.g., alcohol and nicotine) or illegal drug (e.g., opioids, cocaine, marijuana and heroin) or medication. Exposure to such cues produces powerful physiological responses and intense cravings for the substance, resulting in relapse. Exposure therapy has been applied to treating phobias and anxiety, and has been applied to treating substance use disorder. This project will involve the development of a unique game-based virtual reality addiction management framework (VRAMF) that will allow those without a strong technical/programming background to develop VR games designed for the treatment of substance use.

Student responsibilities/tasks: 

  • Conduct background research on the topic of interest to determine what has been done previously.
  • Software development.
  • Prepare a report of the work completed.

Student qualifications required (e.g. courses completed, minimum grades, etc.):

Background in programming (ideally Unity) is an asset although not necessary if the student has a 3D modeling/animation experience/background.

Expected training/skills to be received by the student:

  • Ability to conduct a literature review and summarize the resulting findings.
  • Experience in Unity development and/or 3D modeling/animation.
  • Ability to prepare a final report summarizing the work conducted over the summer.
  • Experience working within an interdisciplinary team.

Award available:  Ontario Tech STAR Award or NSERC USRA


Supervisor name:  Pejman Mirza-Babaei, PhD
Project title:  Exploring Artificial Intelligence (AI) for Automated Playtesting

Summary of research project:  While playtesting with human participants is an integral part of games user research methodology, it is a resource-intensive process with significant time, labour, and equipment requirements. UXR Lab is exploring the development and evaluation of an automated testing tool leveraging AI models of player behaviour. This objective seeks to further investigate the potential of AI playtesting approach as a supplement to expert evaluation techniques practised by researchers in the game industry.

Student responsibilities/tasks: 

  • Coordinate and conduct interviews (online) with researchers in the game industry.
  • Develop and test our current Unity-based prototype (PathOS).

Student qualifications required (e.g. courses completed, minimum grades, etc.):

  • Ideal for 3rd year or 4th year students in the game development program.
  • Must have experience (expert level) with Unity game engine.
  • C-GPA above 3.0.

Expected training/skills to be received by the student:

  • Conducting and analysing expert interviews.
  • Expanding Unity skills. 

Award available:  Ontario Tech STAR Award or NSERC USRA


Supervisor name:  Amirali Salehi-Abari, PhD
Project title:  Deep Learning for Recommender Systems in Privacy and Security Domains

Summary of research project:  Recommender systems are prevalent in our day-to-day life. They intelligently recommend desirable options to us (e.g., books on Amazon, movies on Netflix, etc.), which are consistent with our own taste or preferences. However, little attention is given to the development and design of recommendation systems that assist users in making reliable privacy and security decisions that have a high-impact on users’ lives. Our research mission is to design and develop AI algorithms, technologies, and systems that pave the way for the development of recommendation systems for high-impact privacy and security decisions.

Student responsibilities/tasks:  The candidate is expected to review the relevant research literature along with other team members. The candidate also will be heavily involved in development of the AI technologies and will co-author the consequent paper written from his involvement in this project. This project provides a unique opportunity to the student for fostering their knowledge in AI and computer security and privacy.

Student qualifications required (e.g. courses completed, minimum grades, etc.):

  • Have practical experience in programming.
  • Be an excellent communicator.
  • For technical knowledge/experience, the applicant is expected to have valuable skills in:
    • Web development
    • Python
    • Database
  • Familiarity with deep learning libraries (e.g., TensorFlow, Pytorch, etc) is an asset but not a requirement.

 Expected training/skills to be received by the student:

  • Artificial Intelligence
  • Conducting research

Award available:  Ontario Tech STAR Award or NSERC USRA


Supervisor name:  Khalil El-Khatib, PhD
Project title:  Evaluation of Intrusion Detection Systems for Drones

Summary of research project:  The Drone technology has seen a sharp increase in the last few years, with successful deployments in various sectors including defense, surveillance, transportation and energy, to list a few. However, with the heavy reliance on wireless protocols and hostile operating environments, drones face a large threat landscape. Previously, we have developed an intelligent intrusion detection system (IDS) to enable drones to identify attacks. Forensic analysis is also an ongoing challenge with drones. Initial tests show promising results, but additional tests in various conditions is still required.

Student responsibilities/tasks: 

  • Set up different security testing environments.
  • Perform security evaluations of different security products under various conditions.
  • Evaluate and communicate findings with the rest of the team.

Student qualifications required (e.g. courses completed, minimum grades, etc.):

  • Strong understanding of security testing.
  • Strong understanding of networking technologies.
  • Strong oral and written communication skills.
  • Team work. 

Expected training/skills to be received by the student:

  • Setting up of different security testing conditions for drones.
  • Running rigorous security testing.
  • Analysis and communication of test results.

Award available:  Ontario Tech STAR Award or NSERC USRA


Supervisor name:  Shahram S. Heydari, PhD
Project title:  Programmable Networks

Summary of research project:  The main objective of this research project is to investigate the usability and performance of programmable and protocol-independent packet processing, a new concept for implementing network functions in software-defined and programmable networks. This research will include:

  • Setting up a development environment for programmable networks.
  • Deploy and compare the performance of various network functions such as congestion control, load balancing, network slicing and security attack mitigation in a programmable network vis-à-vis traditional network functions.
  • Provide insights into the potential usage of this technology for implementing novel network functions.

Student responsibilities/tasks: 

  • Researching currently available tools, software and hardware for a programmable network environment.
  • Design and implementation of a development/emulation environment for programmable networks, focusing on P4 as the starting point.
  • Researching and/or developing P4 software modules for various network functions.
  • Preparing reports and presentations with regard to project activities.

Student qualifications required (e.g. courses completed, minimum grades, etc.):

  • A 2nd year (and up) student in the Bachelor of Information Technology, Bachelor of Computer Science, or Bachelor of Software Engineering is preferred.
  • The student should have experience in programming, Linux operating system and networking (either through coursework or hands-on experience).
  • The student should be motivated, self-directed, and passionate about new technologies.

Expected training/skills to be received by the student:

  • P4 network programming language.
  • Software-defined network and virtual networking environment.
  • Linux system development and integration.

Award available:  Ontario Tech STAR Award or NSERC USRA


Supervisor name:  Karthik Sankaranarayanan, PhD
Project title:  Machine Learning for Outage Scheduling and Continuous Monitoring

Summary of research project:  Outage scheduling and continuous monitoring are important processes in power generation firms. Due to security concerns, manual reporting and updating are the status quo. This project will look into the use of new technologies such as machine learning to better schedule such critical processes. The research objectives include an in-depth study on current literature, technologies used, and how machine learning algorithms can be used as a decision-support tool.

Student responsibilities/tasks: 

  • Literature review on outage scheduling.
  • Literature review on continuous monitoring.
  • Technologies used in the industry (i.e. power generation, utility companies).
  • What machine learning algorithms are currently being used.
  • Preparing a case study.

Student qualifications required (e.g. courses completed, minimum grades, etc.):

  • Student from the engineering program (Nuclear Engineering preferred).
  • Knowledge of calculus and programming is required.
  • The student should have completed at-least one scientific communication course(required).

Expected training/skills to be received by the student:

  • Training to read scientific literature, analyze, and find research gaps.
  • Scientific report writing and presentation skills.
  • Machine Learning algorithms, its uses, and coding in python (and its libraries)
  • Interdisciplinary work environment (i.e. how to work in a team comprising of individuals from diverse backgrounds).
  • Project Management.

Award available:  Ontario Tech STAR Award or NSERC USRA


Supervisor name:  Ana Duff, PhD
Project title:  Academic and professional motivators of undergraduate business students in relation to sustainable development goals

Summary of research project:  This project will investigate what motivates students entering undergraduate business programs in relation to their understanding of sustainability, how they define it and what level of significance they assign to it. It will also explore how these views compare to views of graduating business students, particularly how the views of students on sustainability at the end of their undergraduate studies were informed by their studies, their values, experiences and ideals. Having a better understanding of these questions would help inform educators and academics as they adapt and strengthen the educational experience offered in undergraduate and potentially graduate business programs.

Student responsibilities/tasks: 

  • Researches and collects data as directed by project supervisor.
  • Interprets, synthesizes and analyzes data.
  • Reports on status of research activities.
  • Plans and modifies research techniques and procedures.
  • Writes and edits materials for reports and presentation.
  • Meets with faculty supervisor on weekly basis to maintain ongoing communication regarding the quality of student’s performance.
  • Performs other related duties as required.

Student qualifications required (e.g. courses completed, minimum grades, etc.):

  • Proficiency in Microsoft Excel.
  • Ability to work independently, to apply logical critical analysis and to problem-solve technical and methodological issues arising during research.
  • Strong organizational, interpersonal and communication skills.
  • Access to a personal computer, internet connection, microphone and web camera.

 Expected training/skills to be received by the student:

  • Data collection: identifying useful data and critically evaluating quality of datasets for errors or problems.
  • Data management: organizing data, assessing methods to clean data, identifying outliers and anomalies, cleaning data.
  • Data evaluation: applying data analysis tools and techniques, conducting exploratory analysis, identifying discrepancies within data.
  • Data presentation: creating meaningful tables and charts to visually present data, converting data to actionable information.

Award available:  Ontario Tech STAR Award


Supervisor name:  Amir Rastpour, PhD
Project title:  Age Guessing: A game to introduce fundamental statistical concepts

Summary of research project:  This project provides great experience for a student who enjoys programming and wants to publish an academic paper. For my Statistics course, I have developed a game that is played during the first class to help students understand what type of statistical tools they will learn and how practical these tools can be in daily life. Currently, this game is played in a semi-automatic manner and requires various manual adjustments that have to be implemented by the instructor. The goal of this research project is to fully automate the game and to make it available online for other instructors. After developing the game, its educational impacts and values will be presented in an academic paper.

Student responsibilities/tasks:  The student will program the game using Google Apps Script, which is the programming language for Google Sheets. If the student is comfortable with another programming language, it can also be considered as a potential tool. After developing the game, the student will be involved with preparing an academic paper about the positive impacts of the game on students' learning experience. The student will be involved with all publication steps.

Student qualifications required (e.g. courses completed, minimum grades, etc.):

  • The student needs to:
    • Have a solid mathematical background.
    • Have obtained a B+ in the following courses: Math Analysis for Business (BUSI 1916) and Statistics (BUSI 1450), or in similar courses.
    • Demonstrate a good skill set in programming with Google Apps Scripts, or other programming languages.

Expected training/skills to be received by the student:

The student will:

  • Learn and apply a useful and thought-after programming skill and will apply this skill to a real programming project.
  • Learn effective writing and communication skills, which are always valuable in the job market.
  • Have the unique opportunity of going through the steps of an academic publication.

Award available:  Ontario Tech STAR Award or NSERC USRA


Supervisor name:  Serena Sohrab, PhD
Project title:  The Impact of Infertility on Women's Careers

Summary of research project:  The purpose of this project is to understand the impact of infertility treatments on women's work and career trajectories. The specific objectives of this study are to:

  1. Examine how infertility affects the day to day work experience of those pursuing treatment while working.
  2. Investigate how this experience influences career decisions.

To better understand the context of this research, students should read the following article:https://hbr.org/2020/11/employers-its-time-to-talk-about-infertility.

Student responsibilities/tasks:  The student will have the opportunity to engage in a wide range of activities such as:

  • Data collection from secondary sources.
  • Preparing documents for the research ethics board.
  • Analysis of qualitative and quantitative data.
  • Writing up research summaries.

Student qualifications required (e.g. courses completed, minimum grades, etc.):

  • Completed two years of studies in the commerce program, any other social sciences programs, or health sciences.
  • A willingness to learn and grow is required.
  • Knowledge of research methods, statistics and Microsoft excel would be an asset.

Expected training/skills to be received by the student:

The student will learn:

  • About the process of academic research.
  • How to translate academic research for practitioners.
  • To analyze qualitative data.
  • How to summarize research findings.

Award available:  Ontario Tech STAR Award


Supervisor name:  Alvaro Uribe Quevedo, PhD
Project title:  Customizing VR actions through physical and physiological metrics

Summary of research project:  Vitual reality continues growing in popularity, thus increasing the importance of customizable experiences tailored to each user. Recent research in this field has seen the use of physiological measurements and high-end displays that don’t translate to consumers. Although such advances have increased the understanding of the importance of such metrics for better understanding the user experience, there is still a gap between high-, mid- and low-end virtual reality devices. This project focuses on exploring physical and physiological user metrics captured through open source and consumer-level devices with the goal of prototyping an interactive scenario that changes based on the user inputs.

Student responsibilities/tasks:  The student is responsible for conducting a literature review on consumer-level technologies, open electronics sensors, assessment, applications and trends, developing virtual reality scene with basic human interactions such as pick and place objects where grasping is performed employing controllers or hand tracking with 3D user interaction methods. The student will document all progression employing IEEE double column format.

Student qualifications required (e.g. courses completed, minimum grades, etc.):

  • Skills: Unity game engine (C# and C++). Desirable: WebGL, OpenXR, Oculus SDK, SteamVR.
  • Courses completed: Game Engine Design and Implementation. Desired: Industrial Design for Game Hardware, Emerging Tech, Serious Games, HCI, Games User Research.
  • Good written and oral communication skills, group work, leadership, autonomy.

Expected training/skills to be received by the student:

The student will get advisory associated with how to conduct a literature review, conduct a systemic design for the interactive scene in virtual reality, experimental design, design process, scientific writing, capturing and processing user metrics, VR development.

Additionally, the student will develop interdisciplinary skills working in a team of graduate students and practice oral presentations in scientific format to communicate and share the development progress.

Award eligibility:  Ontario Tech STAR Award or NSERC USRA 


Supervisor name:  Samaneh Mazaheri, PhD
Project title:  Evaluating the usefulness of an Artificial Intelligence (AI) technique to support and improve breast cancer screening practice

Summary of research project:  AI is a potential innovative tool to automatically and accurately detect and classify different masses in mammography images.

This study aims to provide evidence for future larger prospective studies to evaluate the ability of a new deep learning algorithm for mass detection in mammograms. You Only Look Once (YOLO) is a recently developed deep learning algorithm that combines object detection and classification tasks into a single step. 

By evaluating the ability of the YOLO AI algorithm to accurately perform mass detection, important early information on the usefulness of this technique to support and improve breast cancer screening practice will be obtained.

Student responsibilities/tasks:  Implementing YOLO algorithm for a publicly available mammography dataset to compare the result with previous research and publish a paper.

Student qualifications required (e.g. courses completed, minimum grades, etc.):

  • Courses completed: Object-oriented programming + Machine learning + Statistics & Probability.
  • Skills required: Python programming.

Expected training/skills to be received by the student:

  • Guidance in implementation.
  • Guidance in documenting the result and writing/publishing the paper.

Award available:  Ontario Tech STAR Award


Supervisor name:  Stephen Marsh, PhD
Project title:  Publicly Private Spaces

Summary of research project:  This project will develop tools to help people in public spaces negotiate about their privacy needs with both the space itself and the people in it. This requires instrumenting the space and providing tools to people (either smartphones or personal privacy devices) and creating applications for the negotiation. We'll be using Raspberry Pis, iOS devices and potentially other Internet of Things devices.

Student responsibilities/tasks: 

  • Creating a virtual proof of concept (video of scenario)
  • Potentially some electronics work (with Raspberry Pi)
  • Developing for iOS, iPadOS, Mac (universal binary)
  • Developing for Raspberry Pi
  • Testing

Student qualifications required (e.g. courses completed, minimum grades, etc.):

  • Development will require knowledge of Swift, Xcode (the student use an M1 Mac) and Linux development.
  • The research is not course specific, although Gaming and CS students would be at an advantage.
  • If programming courses done, at least a GPA of 3.3.

Expected training/skills to be received by the student:

  • Privacy Enhancing Technologies, what they are, how they work, what Public Privacy is.
  • Writing research reports (we will be writing a paper based on this work).
  • Integrating Trust and Security into personal devices.

Award available:  Ontario Tech STAR Award or NSERC USRA


Supervisor name:  Loutfouz Zaman, PhD
Project title:  Development of an augmented reality (AR) environment for teaching how to play the Handpan

Summary of research project:  We will be developing an AR environment for teaching how to play the Handpan. A VR version has already been developed in Unity. Hand tracking has been incorporated using the Leap Motion Controller. The goal of this project is to improve and modernize the environment by adding AR features and improving the interaction.

Student responsibilities/tasks: 

The responsibilities of the award recipient will be to:

  • Add an ability to display the user’s real hands, arms and body using cameras and green screen in an AR setup.
  • Improve the interaction with the Handpan by implementing support for a VR glove such as CaptoGlove.
  • Assist the principal investigator (PI) with applying for research ethics approval for conducting a user study on this setup.

Student qualifications required (e.g. courses completed, minimum grades, etc.):

  • Proficiency in Unity Development.
  • Willingness to learn:
    • The principles of interaction design and HCI.
    • How to conduct usability evaluations using qualitative and quantitative methods.
    • How to perform basic statistical analysis (E.g., ANOVA and non-parametric tests) and visualize the data in the R programming language.

Expected training/skills to be received by the student:

  • Developing AR and VR in Unity.
  • Principles of interaction design and HCI.
  • Quantitative and qualitative research methods.
  • Preparing reports for publication.
  • Basics of statistical analysis and R programming language (once the project gets to the evaluation stage).

Award availability:  Ontario Tech STAR Award or NSERC USRA