Ongoing Research Publications

Bioelectrical Impedance Embedded Fabrics to Mitigate Urinary Incontinence (2023) While urination is a fundamental, mandatory aspect of human life, not all individuals possess the ability to voluntarily urinate or feel the urge to urinate. Urinary incontinence arises from a multitude of factors including weight, age, medications, pregnancy, and the weakening of bladder or pelvic muscles. Essentially, incontinence truly can affect the average everyday user. Current state-of-the-art monitoring systems exhibit impressive proficiency in accurately tracking bladder movements. However, many products in the market often face limitations in terms of user accessibility and inclusivity. In response to this deficiency, our proposed solution aims to develop a non-invasive fabric-based device. Our wearable, utilizing bio-impedance analysis (BIA) sensing, will provide users with comprehensive updates and alerts concerning their urinary/bladder health while simultaneously notifying them of imminent or ongoing concerns.

Racial Bias in Social Media Algorithms: Its effect on culturally diverse users and creators (2022 – Ongoing) – A research project focused on monitoring how users and creators of culturally diverse backgrounds from differing socioeconomic backgrounds promote certain types of content. Also focuses on the way these creators and users can be subjected to unfair marketing and have various disadvantages in comparison to other non-minority users.

Conference Papers

Social Media Safety and Flagging Sensitive Posts (2022 - 2023) – This research project analyzes the shortcomings of content monitoring tools currently on the market and how they can be improved. Finally, this paper will present a solution for violence detection on social media using machine learning. Presented at the IEEE QRS on Security Systems (2022) Held in Guangzhou, China.

Booklet Papers

Securing Additive Manufacturing Digital 3D Models with Encryption Techniques (2022) The risk of unauthorized access to these design files is a major threat, as illegal access can lead to counterfeiting and sabotage. This is especially alarming because additive manufacturing technology makes it relatively easy for someone with little to no experience to create a copy of a product with the stolen design file. In order to help prevent this unauthorized access, it becomes paramount that important intellectual property is secured through encryption methods that cannot be decrypted without the required knowledge. This will result in design creators being able to identify IP theft by looking for any traces of their encryption methods in any suspicious designs. Our group researched and experimented with different encryption methods to safeguard several STL files and tested their effectiveness by attempting to decrypt them without prior knowledge.

Towards Automatic Classification of Privacy Policies (2021 - 2022) - Abstract accepted and presented at The 19th IEEE International Conference on Mobile Ad-Hoc and Smart Systems. The project focuses on the automating of classifying privacy policies, specifically utilizing machine learning techniques Social Media in Educational Settings & Knight Life Application (2021-2022) – An analysis and surveying of how social media has impacted students in undergraduate academia. Our research group curated an application in an attempt to connect students on campus in a technologically advanced way, specifically by modeling our application to Instagram’s layout.