Abstract
My technical capstone and STS research appear very different at first: one focuses on a student-built science printed circuit board for a NASA RockSat-X mission, while the other studies how social media platforms amplify misinformation through engagement-based algorithms. However, both projects center on the same sociotechnical concern: how systems collect, filter, transmit, and protect information. In the capstone, the information is temperature and pressure data gathered during a high-risk flight. In the STS project, the information is news and public knowledge circulating through algorithmic feeds. In both cases, reliable information depends not only on individual components or users, but on larger design choices, incentives, constraints, and accountability structures.
For my technical capstone, my team developed the Science (SCI) PCB for the HEDGE-2 mission. The board functions as the payload's data acquisition system during a NASA RockSat-X sounding rocket flight. Its purpose is to collect temperature, pressure, and housekeeping data as the payload reaches near-space altitudes and experiences the extreme conditions of hypersonic reentry. The SCI board uses a microcontroller, thermocouple converters, pressure sensor interfaces, memory buffering, and RS-485 communication to gather data and send it to the on-board computer. Because this is a one-shot mission, reliability is central. If the system fails during flight, there is no opportunity to repair it or repeat the measurement. The technical challenge is therefore not just making the board work, but designing a system that can preserve accurate information under physical stress, electrical noise, timing constraints, and integration challenges.
My STS research examines a different kind of information system. I study how engagement-based ranking systems on platforms such as TikTok, X, Instagram, and Facebook shape the spread of misinformation. These platforms do not simply display content neutrally. They rank and recommend posts based on clicks, comments, likes, shares, and watch time. Since these signals are tied to advertising revenue, platforms have incentives to promote content that keeps users active. This can make emotional or misleading content especially powerful. My research argues that misinformation is not only a user literacy problem or a moderation problem. It is also a design and business model problem because the systems that distribute information often reward the very content that makes misinformation spread.
Together, my technical and STS projects show why engineers need to think beyond whether a technology works. A system can function as designed and still create harmful outcomes if its incentives are poorly aligned. The SCI PCB must be designed around accuracy, reliability, and mission accountability because bad data would compromise the purpose of the flight. Social media platforms also need accountability, but their current structures often prioritize attention and profit over accuracy. My synthesis is that responsible engineering requires asking what a system is designed to preserve, what pressures it must withstand, and who is affected when information is distorted or lost.
