Hi, I’m Oloff
Graduate student in Computer Science at the University of British Columbia
About Me
Hi, I’m Oloff
I am an MSc. student in Computer Science at the University of British Columbia supervised by Dongwook Yoon. Currently, I am part of the Multimodal User Experience lab within Imager, as well as the Designing for People (DFP) research cluster. My interests are in human-computer interaction, AI, and software engineering. Within these areas, my main focus is human-AI collaboration, particularly in designing creativity support tools which augment human capabilities by leveraging AI.
I am passionate about designing, building, and evaluating user-oriented solutions. I have diverse experience as a full-stack developer, both in research and in the commercial space. In my free time, I enjoy tennis and nature photography. In any project I take on, I am always looking to learn and build my skillset.
Core Skills
- Vue.js
- Nuxt.js
- TypeScript
- Node.js
- Canvas
- PHPUnit
- JUnit
- JAX-RS
- Swing
- Azure Cognitive Services
- NUnit
- MySQL
- MS SQL Server
Other Tools
Projects
Motivating COVID-19 Misinformation Acknowledgment on Instagram
We tackled the problem of COVID-19 misinformation spreading on Instagram by increasing acknowledgement and reporting. This project was completed as part of the UBC CPSC 554K HCI project course. Many Instagram users, particularly young adults,
experience reluctance to report misinformation they have encountered on the platform. Previous studies have shown that Instagram significantly contributes to propagating false information among communities. We conducted a survey of Instagram users to investigate current user behaviour when encountering misinformation and identify the axes of motivation for reporting. Based on the survey results, we generated a set of user personas representing types of users with different reporting behaviour patterns. We then developed a prototype which uses nudging to encourage misinformation reporting. Four prototypes were refined and merged across several rounds of user evaluations to ensure that the resulting prototype is lightweight and enables reporting without taking users out of their common Instagram workflows. See our prototype in Figma. We ultimately presented our work in the DFP Design Showcase. See more details about the project here as well as our presentation video.
Collaborators: Abiramy Kuganesan (MSc, Computer Science, UBC), Hannah Elbaggari (MSc, Computer Science, UBC), Eleanor Ren (MLIS, iSchool, UBC) and Jin Wen (PhD, Psychology, UBC)
Faculty consultant: Dr. Luanne Sinnamon (iSchool, UBC)
Golf swing predictor
We developed a deep learning system which performs golf swing prediction using data from a wrist-mounted motion sensor to estimate both swing type and distance. This project was completed as part of UBC 554X: Signal Processing and Machine Learning. Unlike existing technologies which are complex and expensive, our approach provides swing classification based on data from a relatively simple tri-axial accelerometer and gyroscope mounted to the user’s wrist. Our hardware was constructed using readily available components (i.e., a Raspberry Pi, sensor module, and a portable power bank) which allowed for rapid deployment and training data collection. Ten-fold cross-validation showed promising results for two prediction approaches: 1) a multi-class SVM for predicting shot type and 2) a convolutional neural network (CNN) which estimates both shot type and distance. Check out our project repository and a brief demo of our system by Austin.
Collaborators: Austin Beauchamp (MSc, Computer Science, UBC) and Mark Ma (MSc, Computer Science, UBC).
Zoom-phobia
This project examined the problem of anxiety among students in online video-mediated learning environments (e.g., Zoom classes). My team investigated this issue as part of UBC CPSC 544 (DFP core HCI course). After conducting a survey of graduate students participating in online classes, we found that learners experience heightened self-awareness while using video conferencing software for online learning. This issue is particularly prevalent in small group discussions. Self-awareness contributes to distraction and inhibits participation in course discussions. Thinking about these concerns, we created a low-fidelity prototype which leverages familiar metaphors of interaction (e.g., holding the microphone) to help overcome communication barriers imposed by online video communication. Our design was evaluated through a cognitive walkthrough. Based on the walkthrough results, we then created a medium fidelity prototype called Pentagon. It includes 3 main features which are design to address specific causes of anxiety. 1) “chime-in” and “speaker queue” turn taking feature, 2) in-app collaboration in notebook-like environment, 3) and personalized avatars. See our prototype demo.
Collaborators: Jessica Wilkins (MLIS, iSchool, UBC), Atieh Razavi Yekta (PhD, OSOT, UBC), Anika Sayara (PhD, CS, UBC) and Syed Ishtiaque Ahmad (MSc, CS, UBC)
DiScribe
An automated transcription and speaker recognition solution with WebEx meeting integration. The DiScribe bot processes Webex meeting invitations and dials in autonomously. At meeting completion, the bot produces a meeting minutes text output where each speaker is identified. The meeting minutes are emailed to each participant. Additionally, DiScribe provides access to meeting minutes for previous meetings via a web UI. See the project wiki for more details
Olofflaw.ca
Website for Oloff Biermann, Family Lawyer. Utilizes a responsive design. Supports client appointment scheduling and business info lookup, including Google Maps integration and descriptions of services. Also provides access to the latest client feedback and examples of successful previous cases.
RESTful-p2p
A distributed file sharing system with a supporting REST API. Users can share an unlimited number of files via a simple GUI. Uses a centralized index system that accepts client requests to share files and then records this data. Clients can also request particular files to download, and will be matched with other clients which are sharing those files. Thus, a connection between clients can be established, if any clients are sharing the requested file.
Tutorial platform with EML parser
An online learning system with tutorials and quizzes. Uses an educational markup language (EML), an XML-based language which holds tutorial and quiz info. The EML parser produces HTML which is accepted by the browser. See the project repo for more info.
Canvas slideshow
An HTML Canvas progressive web application (PWA) which supports various transition effects. These effects include manual advance, automatic advance, and randomization. Preloads images that are specified in a JSON file on the server side to avoid delays in image loading when transitioning to a new image. See the project repo for more info.