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FBIT project summaries

Supervisors  

Shahram Shah HeydariAna DuffAmirali Salehi-AbariKhalil El-KhatibAlvaro QuevedoBill KapralosLoutfouz ZamanPejman Mirza-BabaeiKarthik SankaranarayananMiguel V. MartinJulie ThorpeGabby ReschAmir Rastpour 

 

Supervisor name: Shahram Shah Heydari
Project title: Building a AI-enabled Polymorphic Cyberattack Tool

Summary of research project: Polymorphic attacks are a category of cyberattacks in which the attacker changes the type and profile of the attack based on the response from the defence system, normally an IDS (Intrusion Detection System). Such attacks can be built by using deep learning artificial intelligence (AI) techniques. In order to develop mitigation techniques against such attacks, it is important to build toolkits for generating them in a simulation environment. The objective of this research project is to develop such an attack toolkit and analyze its performance in a simulation environment. 

Student responsibilities/tasks:

Student Researcher will be responsible for:

  • Integrating the available codes to build the attack generation environment
  • Develop code and scripts as needed
  • Conduct performance analysis based on the simulation scenarios
  • Document the code and the results
  • Prepare and present a final report on the results.

Student qualifications required:

  • Preferably should have finished the second or third year in an IT, or Computer and Data Science, or Software Engineering program. (Other programs are accepted if have a strong resume with regard to the other requirements).
  • Strong background in coding and/or scripting (Python)
  • Knowledge of cybersecurity and machine learning is preferred

Expected training/skills to be received by the Student:

  • Cybersecurity testing
  • Machine Learning and AI
  • Software development and integration

Length of award: 16 weeks

Available Award: Ontario Tech STAR Award or NSERC USRA

 

Supervisor name: Ana Duff
Project title: Increasing Student Problem-solving Capacity and Communication Skills in Mathematics

Summary of research project: This Project will focus on the development of methodology and tools that can be implemented with first year undergraduate students to strengthen their problem-solving skills. Many students enter undergraduate studies with simplistic view and experience in problem-solving and struggle with the complexities they face at the university. The Project will explore the validity of methodology that focuses on breaking the problem down in a systematic way, following the principle of ‘just-in-time-information’ and aiming to reduce the cost of ‘mental clutter’ in the problem-solving process. The Project will mainly focus on problem-solving in mathematics, but is also applicable in other disciplines.

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 Project Supervisor on weekly basis to maintain ongoing communication regarding the quality of Student’s performance
  • Performs other related duties as required.

Student qualifications required:

  • Demonstrated problem-solving capacity in mathematics
  • Ability to work independently
  • Ability 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

Length of award: 12 weeks

Available Award: Ontario Tech STAR Award

 

Supervisor name: Amirali Salehi-Abari
Project title: Graph Neural Networks for Recommender Systems

Summary of research project: Recommender systems are prevalent in our day-to-day life. They intelligently recommend desirable options to us (e.g., books in Amazon, movies in Netflix, etc.), which are consistent to our own taste or preferences.  Several recent developments have been made in applying deep learning in recommender systems. Of important and promising direction is utilizing graph neural networks for empowering recommender systems with graph-structured side information (e.g., social networks). Our goal is to develop effective deep learning algorithms for large-scale recommender systems in the presence of graph-structured side information. 

Student responsibilities/tasks:

  • The Student is expected to review the relevant research literature along with other team members.
  • The Student also will be heavily involved in development of the Artificial Intelligence (AI) technologies and will co-author the consequent paper written from their involvement in this Project.
  • This Project provides a unique opportunity to the candidate for fostering their knowledge in AI.

Student qualifications required:

  • The Student should have operational knowledge of programming and be an excellent communicator, and team worker.
  • For technical knowledge/experience, the Student is expected to have valuable skills in (1) Python and (2) and deep learning libraries (e.g., TensorFlow, Pytorch, etc). The familiarity with PyG is an asset but not a requirement.

Expected training/skills to be received by the Student:

  • Deep Learning
  • Graph Neural Networks

Length of award: 16 weeks

Available Award: Ontario Tech STAR Award or NSERC USRA

 

Supervisor name: Khalil El-Khatib
Project title: Security Testing for Connected and Autonomous Vehicles

Summary of research project: Connected and Autonomous Vehicles (CAVs) are disrupting the automotive and transportation industry and introducing rapid technological evolution. The benefits and possibilities with connected and autonomous vehicles is plentiful, however it is not without risk. The speed of innovation and adoption of CAV technologies must be complemented by comprehensive and robust testing to ensure the safety of the vehicles' passengers and data. In this project, we address the concern of cybersecurity testing for CAVs. The focus will be on two types of CAV: drones and regular vehicles with communication and computation technologies.

Student responsibilities/tasks:

  • Student will be responsible for performing a literature review about recent security threats in connected and autonomous vehicles, and develop test cases to evaluate the vulnerability of device under test.
  • Student will be responsible for collecting and analyzing data from experiments.

Student qualifications required:

  • Strong IT networking and security skills.
  • Strong knowledge of programming languages (C and Python)
  • Finished 3rd year undergraduate degree
  • Strong written and oral communication skills

Expected training/skills to be received by the Student:

  • Perform literature review
  • Analysis and evaluation of security threats
  • Set up of security testing environment

Length of award: 16 weeks

Available Award: Ontario Tech STAR Award or NSERC USRA

 

Supervisor name: Alvaro Quevedo
Project title: Collaborative Virtual Reality Sandbox for Pick and Place Tasks

Summary of research project: Virtual Reality (VR) has becoming widely adopted in recent years due to its affordability and availability in the form of standalone headsets. Off-the-shelf VR headsets are being used in educational, training, and health care settings to provide immersive and engaging experiences. The democratization of VR technologies presents additional challenges in terms of content creation. This Research Project focuses on prototyping a collaborative VR sandbox for pick and place tasks that accounts for quantitative and qualitative user data to facilitate scene creation for educational purposes.

Student responsibilities/tasks:

As a Student working in this project, you will be responsible for:

  • Conducting a literature review
  • Familiarize with human factors in VR and 3D user interfaces best practices
  • Current research, and practice
  • Write weekly reports in scientific format
  • Regularly meet with the project lead
  • Participate in regular meetings with the project lead research team
  • Develop a VR application using the Unity game engine in a modular manner.

Student qualifications required:

The ideal candidate should possess the following:

  • Good programming skills in C++ and C#
  • Understanding of 3D asset creation and integration with Unity
  • Experience with Unity, WebXR, virtual reality, networking, and game engines
  • Good communication skills both in written and oral form
  • Passionate about immersive technologies.

Expected training/skills to be received by the Student:

  • Through the URA program, the Student will receive training in the scientific method, scientific writing, scientific thinking
  • The Student will receive hands-on experience with virtual reality, networking, human factors in immersive technologies, and collaborative immersive experiences.
  • The Student will familiarize with various testing and assessment methods for improving VR experiences.

Length of award: 16 weeks

Available Award: Ontario Tech STAR Award or NSERC USRA

 

Supervisor name: Bill Kapralos
Project title: Developing virtual reality-based serious games for psychomotor skills development

Summary of research project: Although the use of virtual learning environments (VLEs) and serious games in particular, are rapidly becoming more wide-spread across a wide variety of applications including medical education, most applications are still focused on cognitive skill development typically ignoring psychomotor skills altogether. This work will focus on developing VLEs for medical education that focus on psychomotor skills using consumer level hardware such as haptic data gloves and haptic devices. This may involve, for example, simulating a surgical drill during a knee replacement surgery using a data glove.

Student responsibilities/tasks:

  • The Project will involve design and development of virtual reality-based applications and therefore, students should have prior programming knowledge with a preference for Unity game engine development.
  • Knowledge in 3D modeling/animation is an asset but not required.

Student qualifications required:

  • Programming knowledge and experience
  • Unity game engine experience and knowledge
  • 3D modeling and animation experience/knowledge is an asset but not required
  • Prior game design knowledge/experience is an asset but not required.

Expected training/skills to be received by the Student:

  • Programming (Unity game engine).
  • Working in an interdisciplinary team that may include other students, faculty members, and medical experts.
  • Knowledge in the design and development of virtual learning environments (serious games/virtual simulations).
  • Possible 3D modeling and animation practice

Length of award: 16 weeks

Available Award: Ontario Tech STAR Award or NSERC USRA

 

Supervisor name: Loutfouz Zaman
Project title: Evaluation of a Mixed Reality Handpan Instrument

Summary of research project: We have built an environment for playing handpan using mixed reality, which employs a VR helmet, a hand tracker, an instrument tracker, and a number of interfaces for visualizing notes that need to be played at the right moment, inspired by Guitar Hero. The goal of this Project is to evaluate the sense of presence when playing music using this setup.  The qualifying Student will conduct a comparative user study to analyze different variations of the virtual handpan setup with human participants. In this project, we will be working jointly with a researcher in game VR from the University of Waterloo.

Student responsibilities/tasks:

  • The Student will re-configure the setup for running the study and will perform the evaluation under the supervision of the faculty member.

Student qualifications required:

  • Unity development skills are a must.
  • Experience with Arduino would be helpful, but not required.
  • Experience with designing quantitative experiments and analysis using the R programming language is helpful, although not required, as the Student will get an opportunity to learn these skills from the faculty member and/or graduate research assistants.

Expected training/skills to be received by the Student:

  • The Student will learn how to design and conduct an HCI experiment
  • The Student will learn how to analyze and interpret the results using statistics and the R environment, and how to document them in a research paper
  • The Student will learn how to configure an existing Unity VR project for a study

Length of award: 12 weeks

Available Award: Ontario Tech STAR Award or NSERC USRA

 

Supervisor name: Pejman Mirza-Babaei
Project title: Assess the Impact of Gestural Control on Player Experience in VR

Summary of research project: This research will focus on designing and evaluating prototypes of gestural control schemes for a commercial VR game, informed by a review of existing solutions found in other VR games and interactive media. In particular, we will examine how the congruence of game controls with real-world gestures affects usability and UX. For instance, in-game actions which mimic natural movements (e.g., players picking up objects) may be more understandable or enjoyable to interact with. More broadly, this work applies to the body of knowledge in game interaction design for VR, and our understanding of how players communicate their intent in games.

Student responsibilities/tasks:

The Student responsibilities/tasks will include:

  • An analytical review of motion controls and navigation systems in existing VR applications and games
  • Develop and evaluation of game prototypes, focused on how gestural controls affect player experience.

Student qualifications required:

  • 3rd/4th year students in game development or computer science
  • Unity and C++
  • Interest in digital game development and interaction design
  • CGPA +3.5

Expected training/skills to be received by the Student:

  • Interaction design
  • Games User Research
  • Applied Research (baseline/background research, presentation)

Length of award: 16 weeks

Available Award: Ontario Tech STAR Award or NSERC USRA

 

Supervisor name: Karthik Sankaranarayanan
Project title: Methods for Assessing Nuclear Plant System Information Relationships

Summary of research project: Information collection, storage and retrieval of information for decision-making is a crucial process. A typical power plant contains many systems, components and real-time information on the state of the system. Research needs to be conducted in two key areas.  One is semantic search technologies that can transform the Terabytes of information into more suitable metadata and thus improved search functionality.  The other is the transformation of system information into Multi-level Flow Modelling (MFM) formats such that more detailed assessment of system performance can be obtained. Research into the above types of technologies needs to be done to maintain top performance of the system.

Student responsibilities/tasks:

The successful applicant will perform the following activities:

  • Thorough literature review of techniques currently in use
  • Creation of some simple MFM models for basic systems
  • Testing of simple tools for semantic search
  • Writing a summer research report

Student qualifications required:

  • Student with an engineering background.
  • Python programming skills.
  • Basic understanding of semantic search algorithms.
  • At least one course in modelling and simulation (for example, ESNS 2140U Problem Solving, Modelling and Simulation)

Expected training/skills to be received by the Student:

  • Problem definition and requirement analysis
  • Algorithm development & Programming
  • Scientific report writing
  • Communication (i.e. both oral and written communication)

Length of award: 16 weeks

Available Award: Ontario Tech STAR Award or NSERC USRA

 

Supervisor name: Miguel V. Martin
Project title: Leveraging Artificial Intelligence for Strengthening Password-Based Authentication Systems

Summary of research project: Passwords are one of the most popular authentication methods despite their well-known usability issues such as the trade-off between memorability and guessability, and password reuse across accounts. Artificial Intelligence, in the modality of Natural Language Processing (NLP), is a promising tool that can help to strengthen password systems. The objectives are as follows: (1) Design and test an NLP-based password generator capable of achieving a better trade-off between memorability and guessability; (2) Design and test a robust password strength meter (PSM) using NLP techniques, improving the performance of current PSMs.

Student responsibilities/tasks:

  • The successful Student will contribute to the design of a novel password generator, and will develop a prototype that will be tested in terms of the memorability of the generated passwords.
  • In addition, the successful Student will contribute to the design of a new password strength meter (PSM) that harnesses the power of state-of-the art language models, and will then test its performance against other PSMs used within in the research community.

Student qualifications required:

  • Excellent communication skills, verbal and written.
  • Knowledge of and experience in machine learning.
  • Knowledge of Python programming for machine learning.
  • Being within the last two years of their bachelor’s degree.

Expected training/skills to be received by the Student:

  • Deep understanding of the state-of-the-art in passwords research.
  • Workable understanding of language models of artificial intelligence.
  • Deep understanding of password strength meters and their capabilities.
  • Master a set of machine learning libraries for Python.
  • Testing prototypes and comparing their performance against state-of-the-art.

Length of award: 12 weeks

Available Award: Ontario Tech STAR Award or NSERC USRA

 

Supervisor name: Julie Thorpe
Project title: Secure Use of Password Managers

Summary of research project: Password managers are considered a useful solution the problem of remembering unique passwords across a multitude of accounts. However, their adoption is not widespread. Recent literature suggests that even when people adopt password managers, they are often not using the password generation features and still reusing some passwords. This Project aims to design and evaluate novel user interface enhancements for password managers, as well as awareness tools to increase secure use of password managers.

Student responsibilities/tasks:

  • Designing new user interfaces
  • Web programming of prototypes
  • Database design
  • Writing analysis scripts
  • Running user studies to collect Data
  • Analyzing results
  • Writing
  • Reading relevant papers
  • Participating in meetings

Student qualifications required:

  • Web programming course (Min. grade of B+)
  • General programming course (Min. grade of B+)

Expected training/skills to be received by the Student:

  • Software design and development
  • Security knowledge
  • Research methods

Length of award: 16 weeks

Available Award: Ontario Tech STAR Award or NSERC USRA

  

Supervisor name: Gabby Resch
Project title: Planning and Control of Actions in Unmediated, Augmented, and Virtual Environments

Summary of research project: The purpose of this specific research project is to examine the impact that perception shifts have on 3D object interaction in unmediated, augmented, and virtual reality conditions by characterizing the behavioral changes that occur across these different environments. We are designing, implementing, and evaluating 3D interactions that allow comparative analysis of variations in users' behavioral shifts. We are also developing a framework for advancing the future design of interactive environments in the context of medical training, and have partnered with researchers at Toronto General Hospital to evaluate this work.

Student responsibilities/tasks:

  • The training of highly qualified personnel in the fields of HCI, digital media, and embodied cognition is an important objective of our research project.
  • The Student will assist with software implementation of the AR/VR environments using Unity 3D.
  • They will also assist with usability and technical testing, and will contribute to the project documentation and dissemination.

Student qualifications required:

  • Students should have experience with software commonly used in the development of games and immersive environments (e.g. Unity 3D), and will benefit from having used AR or VR devices (e.g. HoloLens, HTC Vive).
  • Students who have taken courses focused on game development, usability for games, or biomedical communication will be well-prepared.

Expected training/skills to be received by the Student:

  • The Student will learn how to develop experimental immersive AR and VR environments in Unity 3D.
  • The Student will work with a collaborative team made up of senior researchers from Ontario Tech, Georgia Tech, UofT, and Ryerson to prepare a SSHRC Insight-funded Research Project.
  • The Student will work with a team of researchers at Toronto General Hospital who have been pioneered methods for 3D printing heart phantoms as we implement anatomical models in AR and VR.
  • The Student will learn advanced 3D modelling skills, experiment design techniques, and, COVID restrictions permitting, data collection from an in-person study.
  • The Student will participate in the dissemination of research outputs. An undergraduate student URA recipient from 2020 was third author on a design paper that we submitted this week.

Length of award: 16 weeks

Available Award: Ontario Tech STAR Award or NSERC USRA

 

Supervisor name: Amir Rastpour
Project title: Developing a Game for Teaching Statistics

Summary of research project: I have developed a game that students use to learn statistics. This game is constructed based upon the concept of a "tree," with lower branches being related to simpler problems and the problem complexity increases when the user starts to climb to higher branches. Each branch consists of problems of the same complexity level and a student is not allowed to move higher unless they answer a certain number of questions correctly. While a student climbs the learning tree, the game randomly throws some questions from lower levels, to ensure the student has not forgotten those simpler concepts, and some questions from higher levels, to re-evaluate and make sure the current level is not boring for the student. Each question is accompanied by supplementary documents and media (like a short video), to make sure the student has access to appropriate learning sources at each level. This tree concept has been successfully used in language learning and I hope I can implement that for learning mathematical concepts in general, and statistics in particular.

Student responsibilities/tasks:

  • Literature review on tree-based learning concept
  • Programming the game using a programming language of preference

Student qualifications required:

  • Knowledge of Statistics and programming
  • Good writing and communication skills
  • High motivation and team-work skills

Expected training/skills to be received by the Student:

  • Implementation of a game for a real application
  • To conduct academic literature review and summarize findings
  • Breaking a real problem into smaller digestible problems and then combining the small answers to solve the original problem

Length of award: 16 weeks

Available Award: Ontario Tech STAR Award or NSERC USRA