Fellows

Taylor Allen

Ph.D. student, Mechanical Engineering
Focus: Developing tools and techniques to improve the design of assistive technology

Taylor is a Mechanical Engineering Ph.D. student and a Graduate Research Assistant for the Rehabilitation Engineering and Applied Research (REAR) Lab, which serves to improve the quality of life for individuals with disabilities through innovative research and design​.

Taylor’s academic background, a B.S. in Biomedical Science and a M.S. in Mechanical Engineering, with her desire for product design makes her well-equipped to contribute to the REAR Lab’s mission and further develop her research and design experience.

“My research centers around improving the product development process when designing low-volume assistive technology (AT). In particular, I am trying to develop a tool that helps inform design decisions during low-volume AT design in order to remove some of the barriers companies encounter when trying to design and market these products. Many AT products, which have the potential to improve the lives of persons with disabilities, never make it to market and if they do, the rate of abandonment is very high. Design and commercialization barriers, including the breath of functional diversity of individuals with disabilities, a very small market size, insufficient stakeholder engagement, and the complexities of designing for low-volume production, preclude AT inventors from developing robust, affordable products. Utilizing optimization methods, utility theory, and other decision-based design techniques, I am developing a tool to offer AT developers that informs decision-making when evaluating whether to advance an AT functional prototype for commercialization.”

Mahsa Hedayati

Ph.D. student, Architecture
Focus: Advancing Thermal Comfort Prediction: A Machine Learning Framework for Energy Efficiency and Personalized Comfort Systems

Hedayati is a Ph.D. student in Building Science and Technology at Georgia Tech and is affiliated with the High Performance Building Lab (HPBL). With a background in architectural engineering, building technology, and environmental sustainability, she applies data-driven approaches to enhance thermal comfort, human thermophysiology, and energy efficiency in the built environment. Her expertise spans machine learning, optimization, and building performance analysis, bridging advanced computational methods with sustainable design. Through her research, she develops occupant-centric solutions that enhance thermal comfort, health, productivity, and overall well-being. Her work also supports the development of open-source tools and simulated environments, making these advancements accessible to researchers, practitioners, and the broader public.

“My research focuses on advancing Personalized Thermal Comfort Prediction using machine learning to optimize occupant comfort while reducing energy consumption. This model improves the accuracy of individualized comfort predictions by integrating diverse data sources—including physiological, environmental, and demographic factors. Additionally, my work explores Personal Comfort Systems (PCS), such as heated and cooled chairs, which allow users to control their immediate thermal environment, enhancing thermal comfort and reducing reliance on centralized heating and cooling. This research contributes to the broader goal of decarbonizing buildings and achieving net-zero emissions, addressing the critical challenge of climate change while improving occupant well-being.”

Madison Hales

Ph.D. student, Robotics
Focus: Sensory Pathways through Root Response to Environmental Stimuli and Growth in Soil

Jamila Khanfri

Ph.D. student, Mechanical Engineering
Focus: 3D Printing Processes for Metals for Standardization and Automation