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2024-25:summer [2024/04/11 00:25] – [Chat Bots in LMS for Easy Course Navigation] baljko2024-25:summer [2024/04/16 00:15] – baljko
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 ---- ----
  
 +==== LLM4SE (Large Language Models for Software Engineering) ====
  
 +**[added 2024-04-15]**
 +
 +**Course:**  EECS4070/EECS4080
 +
 +**Supervisor:** Zhen Ming (Jack) Jiang
 +
 +**Supervisor's email address:** zmjiang@yorku.ca
 +
 +**Project Description:** 
 +Software engineering data (e.g., source code repositories and bug databases) contain a wealth of information about a project's status and history. With the recent advances of large language models (e.g., GPT and BERT) as well as their applications (e.g., ChatGPT or GitHub Copilot), many software engineering tasks can be automated or optimized. In this project, the student(s) will explore and investigate various software engineering applications which can benefit from the use of LLMs.
 +
 +**Required skills or prerequisites:**  
 +  * Major in Computer Science/Software Engineering/Computer Engineering
 +  * Third year and up
 +  * At least B+ for EECS 3311
 +  * Proficient in Python and Java-based programming
 +
 +**Recommended skills or prerequisites:**
 +Some knowledge in AI would be preferred but not required
 +
 +**Instructions:**
 +Send c.v. and unofficial transcript to the supervisor.
 +
 +----
 +
 +==== FMOps ====
 +
 +**[added 2024-04-15]**
 +
 +**Course:**  EECS4070/EECS4080
 +
 +**Supervisor:** Zhen Ming (Jack) Jiang
 +
 +**Supervisor's email address:** zmjiang@yorku.ca
 +
 +**Project Description:** 
 +Artificial Intelligence is gaining rapid popularity in both research and practice, due to the recent advances in machine learning (ML) research and development. Many ML applications (e.g., Tesla’s autonomous vehicle and Apple’s Siri) are already being used widely in people’s everyday lives. McKinsey recently estimated that ML applications have the potential to create between $3.5 and $5.8 trillion in value annually. Foundation models are large AI models trained on a vast quantity of data at scale. FMs can be used to power a wide range of downstream tasks (e.g., chat bots, code assistants, tutors, etc.). However, there remain many challenges in efficiently training, deploying and monitoring such FM infrastructure. In addition, there is a lack of tools and processes to further develop applications or services on top of such FMs. The goal of this project is to develop engineering tools and best practices to support effectively operationalizing FMs.
 +
 +**Required skills or prerequisites:**  
 +  * Major in Computer Science/Software Engineering/Computer Engineering
 +  * Third year and up
 +  * At least B+ for EECS 3311
 +  * Proficient in Python and Java-based programming
 +
 +**Recommended skills or prerequisites:**
 +Some knowledge in AI would be preferred but not required
 +
 +**Instructions:**
 +Send c.v. and unofficial transcript to the supervisor.
 +
 +==== Machine Learning for Engineering Dependable Systems ====
 +
 +**[added 2024-04-14]**
 +
 +**Course:**  EECS4070/EECS4080
 +
 +**Supervisor:**  Hamzeh Khazaei
 +
 +**Supervisor's email address:** hkh@yorku.ca
 +
 +**Project Description:** 
 +In this research, we plan to examine the application of large language models (LLMs) in designing more dependable software systems. Dependability in this context refers to the overall trustworthiness of the software, which includes aspects such as performance (how well the system operates under varying conditions and workloads), reliability (the system's ability to function properly and consistently over time), and security (resiliency against malicious attacks and its ability to protect data and maintain privacy). One of these aspects will be addressed in this research. This has not yet been finalized as it depends on the applicant. We believe LLMs have great potential in designing intelligent adaptive large-scale computing systems. These models can process vast amounts of data, learn from it, and make decisions or predictions, which is essential for systems that require a high degree of autonomy, such as cyber-physical systems and machine-learning systems that often need to operate and maintain themselves automatically due to their scale and complexity.
 +
 +**Required skills or prerequisites:**  
 +  * Good programming skills. 
 +  * Good grades in System and ML courses.
 +
 +**Recommended skills or prerequisites:**
 +Interested in the intersection of machine learning and systems. Interested in building large-scale systems.
 +
 +**Instructions:**
 +Please send your CV and transcripts to the supervisor.
 +
 +
 +==== Visualizing the debugger for first-year computer science students ====
 +**[added 2024-04-15]**
 +
 +**Course:**  EECS4080
 +
 +**Supervisor:**  Meiying Qin
 +
 +**Supervisor's email address:** mqin@yorku.ca
 +
 +**Project Description:**  
 +Debugging is one of the most important skills for computer science students. However, first-year students are usually not comfortable with working with a debugger. In order to help ease the process for first-year students, we plan to write an application that can visualize the process by animating the variable manipulated, either on a screen or using virtual reality/augmented reality. In this project, you will have the opportunity to gain hands-on experience in both designing and implementing a software application. You will gain experience in animation or virtual reality.
 +
 +**Required skills or prerequisites:**  
 +  * Proficient in Python (as you will write a visualized debugger for students learning Python)
 +  * Strong learning ability (You will be expected to learn VR/AR programming if we decide to use NR/AR)
 +
 +**Recommended skills or prerequisites:**
 +Experience with virtual reality/augmented reality or animation
 +
 +**Instructions:**
 +Please send your c.v. and transcript to the project supervisor.
 +If available, please also send your e-portfolio (e.g., GitHub, or other links) of your previous projects.
 +
 +----
 +
 +==== Sims for University Life ====
 +
 +**[added 2024-04-15]**
 +
 +**Course:**  EECS4080
 +
 +**Supervisor:**  Meiying Qin
 +
 +**Supervisor's email address:** mqin@yorku.ca
 +
 +**Project Description:**  
 +One of the biggest challenges that first-year students face is the transition from high school to university. This is expected to be more pronounced once the York Markham campus opens as all courses will use the flipped-class model. In this model, students are required to be more active in learning and preview the content before each class in order to stay on track. In order to assist first-year students in making a smoother transition even before school starts, we plan to release a game that simulates the life of a computer science student at the Markham campus to provide students with a preview of university life. In this project, you'll have the opportunity to gain hands-on experience in both designing and implementing a game.
 +
 +**Required skills or prerequisites:**  
 +
 +  * Strong software engineering skills;
 +  * The game will either be on Android or a web-based game. So you will need to have some experience in either Java or web development;
 +  * an interest in helping first-year students and suggesting game components based on your own experience.
 +
 +**Recommended skills or prerequisites:**
 +Experience with graphical user interface or game design.
 +
 +**Instructions:**
 +Please send your c.v. and transcript to the project supervisor.
 +If available, please also send your e-portfolio (e.g., GitHub, or other links) of your previous projects.
 +
 +----
 +==== Robots Tutors in First Year Programming Courses ====
 +
 +**[added (partially) 2024-04-15]**
 +
 +**Course:**  EECS4080
 +
 +**Supervisor:**  Meiying Qin
 +
 +**Supervisor's email address:** mqin@yorku.ca
 +
 +**Project Description:** 
 +
 +//project description is being updated//
 +
 +----
 +
 +==== Designing Privacy-preserving Systems ====
 +**[added 2024-04-15]**
 +
 +**Course:**  EECS4080 or EECS4480
 +
 +**Supervisor:**  Yan Shvartzshnaider 
 +
 +**Supervisor's email address:**  rhythm.lab@yorku.ca
 +
 +**Project Description:** 
 +Modern sociotechnical systems share and collect vast amounts of information. These systems violate users’ privacy by ignoring the context in which the information is shared and failing to incorporate contextual information norms.
 +
 +Using techniques in natural language processing, machine learning, network, and data analysis, this project is set to explore the privacy implications of mobile apps, online platforms, and other systems in different social contexts/settings.
 +
 +To tackle this challenge, the project will operationalize a cutting-edge privacy theory and methodologies to conduct an analysis of existing technologies and design privacy-enhancing tools.
 +
 +Students will help analyze information handling practices of online services and design privacy-enhancing tools. 
 +
 +Specific tasks include: comprehensive literature review of existing methodologies and tools, analysis of privacy policies and regulations, visualization of information collection practices, and design of a web-based interface for analyzing extracted privacy statements to identify vague, misleading, or incomplete privacy statements.
 +
 +For prior project, see [[https://wiki.eecs.yorku.ca/course_archive/2021-22/F/4080_4088_4090_4480_4070/4088_presentation_schedule|this link]]
 +
 +**Required skills or prerequisites:**
 +Good programming and data analysis skills overall, and experience in using Jupyter and/or R for data analysis.  Ability to work independently. 
 +Interest in usable privacy, critical analysis of privacy policies and privacy related regulation.
 +
 +**Recommended skills or prerequisites:**
 +Experience with Machine Learning, Natural Language Processing techniques, HCI design. 
 +Students with diverse backgrounds, including in technical fields, social sciences and humanities are encouraged to apply.
 +
 +**Instructions:**
 +Please fill in [[https://forms.gle/oVVg6hEConSNf9p28|this form]]
 +
 +----
 +==== Designing Privacy-preserving  Virtual Reality Systems ====
 +
 +**[added 2024-04-15]**
 +
 +**Course:**  EECS4080 or EECS4480
 +
 +**Supervisor:**  Yan Shvartzshnaider 
 +
 +**Supervisor's email address:** rhythm.lab@yorku.ca
 +
 +**Project Description:** 
 +Designing a privacy-preserving VR experience requires adhering to contextual integrity of users’ data . This involves accounting for different modes of interaction and ensuring robustness to accommodate the evolving privacy norms associated with future VR adaptations.
 +
 +To tackle this challenge, the project will operationalize a cutting-edge privacy theory and methodologies to develop mechanisms  that ensure that information flows in accordance with users’ expectations and established societal norms in VR settings.
 +
 +Students will help analyze information handling practices of VR applications and design tools to enhance privacy of VR users.
 +
 +Specific tasks include conducting a comprehensive literature review of existing methodologies and tools, performing a dynamic analysis of data practices in VR applications, and checking for compliance with existing regulations and privacy policies.
 +
 +For reference, see these papers:
 +  * https://arxiv.org/pdf/2303.13684.pdf
 +  *https://www.usenix.org/conference/usenixsecurity22/presentation/trimananda
 +
 +**Required skills or prerequisites:**  
 +  *  Good programming skills (experience with coding in Unity is a plus)
 +  *   Interest in usable privacy, critical analysis of privacy policies, and knowledge of privacy-related regulations
 +  *   Ability to work independently
 +
 +**Recommended skills or prerequisites:**
 +  *   Experience with data analysis using Jupyter and/or R
 +  *   Familiarity with HCI design
 +
 +
 +
 +----
 +==== Mnemonic-Based Serious Games ====
 +
 +**[added 2024-04-15]**
 +
 +**Course:**  EECS4080
 +
 +**Supervisor:**  Professor Kiemute Oyibo
 +
 +**Supervisor's email address:** koyibo@yorku.ca
 +
 +**Project Description:** 
 +Many courses in Social Science, Health Science, and Computer Science that require memorization are becoming more and more challenging for many college and university students, especially with the ever-increasing volume of textbooks and course materials due to the growing body of knowledge. In courses, such as psychology, biology, and Human-Computer Interaction (HCI) that are memorization intensive, students are often overwhelmed by the lengthy course materials, readings, and the uphill challenge to retain and recall most of the content taught in class. Given the many challenges that most students face in higher education, including having to work to help pay for their university education, they often lack sufficient time to read and properly understand the taught material. Hence, there is a need to find effective ways to support student learning. We argue that serious games can be utilized to support student learning in memory-intensive courses to increase content comprehension and retention. Serious games are interactive applications that use game elements for education purposes rather than entertainment. They are increasingly being used in the education domain to support student learning. In this project, we aim to design, implement, and evaluate a mnemonic-based serious game to help students learn and retain taught material easily in memorization-intensive courses individually and collaboratively.
 +
 +Duties and Responsibilities: Requirements gathering and analysis, prototyping, application programming and evaluation, data analysis, report writing and presentation.
 +
 +**Required skills or prerequisites:**  
 +  * Prototyping with tools such as Figma and programming on the mobile platform (e.g., Android, cross-platform).
 +  * Software Engineering; LE/EECS 4441 3.00 – Human-Computer Interaction, LE/EECS 3461 3.00 – User Interfaces
 +  * Ability to work independently as well as in a team.
 +
 +**Instructions:**
 +
 +Contact professor at email above.
 +
 +----
 ==== Strengthening the Security of Autograders ==== ==== Strengthening the Security of Autograders ====
 +
 +**[revised 2024-03-15, added 2024-04-11]**
  
 **Course:**  EECS4480/EECS4080 **Course:**  EECS4480/EECS4080
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 Unit testing platforms like Java's JUnit and Python's unittest provide a simple interface for evaluating the correctness of individual functions in a large project. These platforms can also be used in an academic environment to automatically test student-submitted code in programming assignments and generate a grade based on if these tests pass or fail. However, given that these platforms were originally developed for running code that is expected to be trusted, this practice can lead to a potential risk if students are able to provide code that causes the test to pass without resulting in the expected value (see https://www.seas.upenn.edu/~hanbangw/blog/hack-gs/). While most modern autograding platforms introduce security practices to avoid this kind of code from receiving a valid grade, some vulnerabilities still exist. Unit testing platforms like Java's JUnit and Python's unittest provide a simple interface for evaluating the correctness of individual functions in a large project. These platforms can also be used in an academic environment to automatically test student-submitted code in programming assignments and generate a grade based on if these tests pass or fail. However, given that these platforms were originally developed for running code that is expected to be trusted, this practice can lead to a potential risk if students are able to provide code that causes the test to pass without resulting in the expected value (see https://www.seas.upenn.edu/~hanbangw/blog/hack-gs/). While most modern autograding platforms introduce security practices to avoid this kind of code from receiving a valid grade, some vulnerabilities still exist.
  
-For this project you will strengthen the security of an autograder process for either Python or Java code for the PrairieLearn platform. You will start by creating possible attack vectors in the form of code that is expected to cause the autograder to pass a test without actually returning the expected results. Examples of attack vectors include code that saves or outputs well-formatted values that are interpreted by the autograder as a success, code that is able to identify secret information from the autograder code, and/or code that crashes the original autograder process. Then you will implement safeguards that ensure student-submitted code is unable to bypass container sandbox limitations, and that ensure that malicious student code does not result in a successful grade.+For this project you will strengthen the security of an autograder process for either **C,** Python or Java code for the PrairieLearn platform. You will start by creating possible attack vectors in the form of code that is expected to cause the autograder to pass a test without actually returning the expected results. Examples of attack vectors include code that saves or outputs well-formatted values that are interpreted by the autograder as a success, code that is able to identify secret information from the autograder code, and/or code that crashes the original autograder process. Then you will implement safeguards that ensure student-submitted code is unable to bypass container sandbox limitations, and that ensure that malicious student code does not result in a successful grade.
  
 You will work in coordination with the supervisor and the PrairieLearn developer community to brainstorm possible strategies and guidelines. Your final deliverable will be a pull request to the PrairieLearn codebase with the proposed fix. You will work in coordination with the supervisor and the PrairieLearn developer community to brainstorm possible strategies and guidelines. Your final deliverable will be a pull request to the PrairieLearn codebase with the proposed fix.
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   * To work on autograder for Python code, you must have completed EECS 1015 (or a similar course) with an A/A+. Must have solid programming skills in Python, including the use of unit testing.   * To work on autograder for Python code, you must have completed EECS 1015 (or a similar course) with an A/A+. Must have solid programming skills in Python, including the use of unit testing.
   * To work on autograder for Java code, you must have completed EECS2030 (or a similar course) with an A/A+.  Must have solid programming skills in Java, including the use of unit testing    * To work on autograder for Java code, you must have completed EECS2030 (or a similar course) with an A/A+.  Must have solid programming skills in Java, including the use of unit testing 
 +  * **To work on autograder for C code, you must have completed EECS 2031 (or a similar course) with an A/A+. Must have solid programming skills in C, preferably including the use of unit testing (though experience with unit testing in other languages is acceptable).**
   * Must be able to work independently and have good communication skills.   * Must be able to work independently and have good communication skills.
  
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 **Instructions:** **Instructions:**
 Additional information about PrairieLearn can be found here: https://prairielearn.readthedocs.io/en/latest/. A sample PrairieLearn assessment that includes Python autograded questions can be found here: https://us.prairielearn.com/pl/course_instance/136606/assessment/2351069. Please submit a brief description of your experience with the skills listed above. Additional information about PrairieLearn can be found here: https://prairielearn.readthedocs.io/en/latest/. A sample PrairieLearn assessment that includes Python autograded questions can be found here: https://us.prairielearn.com/pl/course_instance/136606/assessment/2351069. Please submit a brief description of your experience with the skills listed above.
 +----
 ==== Chat Bots in LMS for Easy Course Navigation ==== ==== Chat Bots in LMS for Easy Course Navigation ====
 +
 +**[added 2024-04-11]**
  
 **Course:**  EECS4080 **Course:**  EECS4080
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 Please send your c.v., transcript, and Statement of Interest in the project to the project supervisor. Please send your c.v., transcript, and Statement of Interest in the project to the project supervisor.
  
 +----
 ==== Autograders for C and Linux Programs in Undergraduate Courses ==== ==== Autograders for C and Linux Programs in Undergraduate Courses ====
 +
 +**[added 2024-04-11]**
  
 **Course:**  EECS4080 **Course:**  EECS4080
2024-25/summer.txt · Last modified: 2024/04/16 00:31 by baljko