About Me
Hi, I’m Marlon Ward, a Human Factors Engineering student at Tufts University, passionate about creating intuitive, human-centered solutions across product design, technology, and finance. My work bridges usability research, interaction design, and applied data science, with interests spanning medical devices, sports ergonomics, automotive design, and quantitative finance.
I bring both technical and creative skills to my projects, with experience in Python, R, HTML/CSS, MATLAB, Figma, and data visualization tools. Whether I’m conducting usability tests, building interactive prototypes, or applying analytical models to complex problems, I take a research-driven approach that balances functionality, aesthetics, and user well-being.
Beyond my technical toolkit, I thrive in collaborative environments where I can apply design thinking, statistical analysis, and product development to solve meaningful challenges. With strong communication and leadership skills, I’m excited to contribute to teams that value innovation, whether in designing better user experiences or uncovering insights in data-driven projects.
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Research Interests
My research interests focus on the applied side of Human Factors Engineering, where design choices directly impact safety, usability, and decision-making. I am particularly interested in how human-centered systems can be applied across humanitarian technology, sports safety, and financial decision-making tools. My goal is to contribute to innovations that improve lives through accessible, data-driven, and thoughtfully designed solutions.
Human-Centered Design for Humanitarian Technology
As a lab member of the Migrant Compass Project at Tufts University’s IDEA Lab, I contributed to the development of a mobile platform that integrates real-time migration data with AI-driven guidance. The project sought to give vulnerable populations accessible and reliable tools for navigating emergencies and resource access. My work supported the application of engineering psychology principles to ensure the platform balanced usability, privacy, and cultural sensitivity.
I assisted in user research with migrant communities to identify accessibility needs and critical pain points. I also contributed to the Figma prototyping of features such as location-based emergency alerts and resource mapping. Working alongside a cross-functional team of developers, data scientists, and policy experts, I gained experience in collaborative design, privacy safeguards, and iterative testing to enhance trust and adoption in humanitarian contexts.
Human Factors in Sports Safety and Helmet Redesign
In my Human Factors in Product Design coursework, I conducted research on football helmet redesigns aimed at improving concussion prevention and player safety. The project examined the shortcomings of current helmet designs, particularly their limited protection against rotational forces and lack of real-time impact monitoring, and proposed solutions inspired by biomimicry and user-centered requirements.
I explored new helmet features such as a multi-layer composite shell, biomimetic inner padding, embedded impact sensors, and airbag-like deployment systems for neck stabilization. The design, called the BioShield Helmet, applied human factors requirements around comfort, fit, communication, and safety while addressing player resistance to adopting new technologies. This research demonstrated how applied ergonomics and system design can reduce long-term cognitive risks while improving usability for athletes.
Designing User-Centered Financial Decision Tools
Financial decision-making is often overwhelming for users due to the complexity of investment products, risk trade-offs, and information overload. My research interest in this area focuses on how human-centered design and behavioral insights can make financial tools more intuitive, transparent, and empowering.
I explore how streamlined information visualization, simplified workflows, and adaptive interfaces can help users at different levels of financial literacy better understand their options. By integrating AI-driven recommendations with clear explanations, these tools can build trust while reducing decision fatigue. This applied approach highlights how principles of Human Factors, from cognitive load management to usability testing, can transform wealth management platforms into systems that support confident, informed financial choices for all users.
