WATERLOO | CHERITON SCHOOL OF COMPUTER SCIENCE
Undergraduate Research Fellowship
Christopher Vattheuer (University of Manitoba, upcoming URF in W21)
Describe your URF project. I am excited to work with Professor Abedi on a follow-up to the paper ‘WiFi Says “Hi” Back to Strangers!’. A serious and unpreventable security flaw affecting all existing WiFi devices has been discovered which could allow attackers to extract sensitive personal information from victims. I will be exploring the severity of this security weakness by researching an attack. The attack I explore will either be a battery-draining attack, which can allow an attacker to drain a victim’s device 35x faster or a WiFi sensing-based attack. In a WiFi sensing-based attack, attackers exploit Polite WiFi to extract physical information about users such as uncovering a victim’s gestures, breathing rate, and even keystroke information. While Polite WiFi creates many security threats, it can also be applied in a manner beneficial to society: Polite WiFi could allow for easier deployment of WiFi sensing applications, aiding in domains such as security and elderly care.
Tara Stojimirovic (University of Waterloo, upcoming URF in W21)
Describe your URF project. I will be working with Prof. Rafael Oliveira on the URF project. In computer science, error-correcting codes are used in data transmission. A lot of progress has been made in developing such codes with high rate and distance. A high rate means that the ratio of the size of the original data to the size of its encoding is large. More recently, there has been an interest in researching codes that are locally correctable. This allows for large amounts of data to be transmitted securely, while being able to accurately recover only smaller areas of interest without having to query the whole data package. To achieve such properties in a code, its rate and distance must suffer. The goal of the project is to investigate bounds on the rate of a code over fields of characteristic zero, while maintaining the locally-correctable property.
Ken Jen Lee (University of Waterloo, URF in W20)
Describe your URF project. I did a URF internship as my fifth co-op under Prof. Edith Law in the research field of HCI (Human-Computer Interaction) as part of the HCI Lab. The main project was Curiosity Notebook, an online platform where users learn by teaching a conversational agent. Curiosity Notebook contributes to existing literature on learning-by-teaching by investigating how we can design effective conversational agents in various embodiments (e.g. chatbots, physical robots) to support learning-by-teaching. Three separate research studies were carried out in parallel. The first is an observational study of teaching styles and behaviours by participants; the second on the effects of humour styles in the agent on participants’ perceptions and behaviors; the third on the use of reinforcement learning in physically embodied agents (i.e. NAO robots) to encourage teamwork within participant dyads when teaching. Other projects I assisted in studies the effectiveness of using comics and collaborative storytelling in an introductory computer science (CS) course. Particularly, can comics be used to introduce and reinforce CS concepts like loops and arrays? Are assignments where students create choose-your-own-adventure type stories effective in encouraging the application of CS concepts while allowing for creative freedom?
Describe your URF experience. URF, and research by extension, is cool because of it requires various skills. There were days when I am a full stack developer, learning about new frameworks and relying on Stack Overflow as one would. There were days when I dove deep into research and journal databases trying to learn about existing literature and understanding how to build on top of them. There were days when I spent the most time with NAO robots, programming and interfacing them to our application. Other times I was either meeting with my supervisor or discussing with other lab members on how to design the study, the interactions possible with our application and potential gaps we might have neglected. It was amazing to collaborate with other undergraduate and Masters, PhD and Postdoctoral students because as the least experienced person, I learned a lot. Other than that, I had many fun chats with other lab members and faculties during lunch and attended interesting seminars by graduate students on their work. After my URF ended, I continued to work on the projects, which eventually led to paper submissions and another internship under my supervisor.
What are some things that surprised you that you learned through the URF program? I would say the things that surprised me the most is how important flexibility, communication and networking are in research. Since research is a process of observing and framing problems and investigating them, there is so much flexibility needed to deal with unexpected events. For instance, we planned for in-person studies at a few local schools for the project. However, the lockdown meant that the entire study had to be modified to an online format. Everything from the timeline to the process of getting participants and administering the study had to change. Correspondingly, the application had to be tweaked quite a bit as well. The next surprising thing is communication. Often as interns you are given a relatively well-defined problem to work on. However, most research are ill-defined, hence requiring close collaborations with colleagues and supervisors to ensure everyone is on the same page. From discussing the research questions, to designing applications and carrying out studies; every stage requires effective communication and teamwork to be successful. Although I was used to working in pods from previous internships, this was certainly a step up. The third thing that surprised me was the importance of having a strong and growing network. Research often requires collaboration to effectively combine everyone’s expertise, which is especially true for HCI given its multidisciplinary nature. In my URF, I got to collaborate with a faculty from Psychology and really enjoyed the fresh perspectives that those in computer science and engineering might have been unaware of.
Tell us about some of your achievements from the URF internship. During the URF, I was fortunate enough to be involved in 2 workshop papers for workshops in ACM CHI 2020 and ACM/IEEE HRI 2020. I also presented one of the papers during a virtual CHI workshop with a colleague; it was a great experience discussing next-gen research with other graduate students and faculties in the workshop. I continued to work on my URF projects after the URF term, which eventually led to one co-author paper accepted in SIGCSE 2021, one lead author paper submitted to CSCW 2021 and two co-author papers submitted to CHI 2021 and IEEE ICRA 2021. Perhaps just as important, I got to know amazing researchers whom I can call friends during my internship.
What was the best part about your URF internship? URF allowed me to be part of the world of graduate students. This kind of first-hand experience was the best way to inform myself on whether or not I want to pursue graduate school or a career in research. I got to learn the backgrounds, current works and aspirations of other lab members; I got to see other members graduating and moving on to their next journey; I saw the unfiltered moments of joy and frustration that came with research. All these raised the curtains on what it is like to be a researcher or graduate student, and also what possible paths are available during and beyond graduate studies. Another part of URF that I thoroughly enjoyed was being able to be involved in every part of the research projects while having the guidance of more experienced colleagues who were always available to help.
Would you recommend the URF program to other students? I would recommend URF without a doubt, especially to any undergraduate student who dipped their toes in research through part-time involvements (e.g. URA) and would like to take the next step. Nothing is better than living like a graduate student to understand research and graduate school.