My research interests and experiences have focused on bio- inspired fluidic lens, which is a lens that can change its curvature just like the crystalline lens of the human eye. The curvature tuning capability allows for a theoretical limit of 300 diopters of tuning without having any moving lenses. With this key feature, the lens can be made very small but yet has a tremendous amount of tuning capability. This is very different from traditional optical lenses, which are made out of rigid material where the curvature cannot change. Hence, the only way for traditional optical systems to change its power is by changing the location of the lenses. This forces the traditional optics to be much larger, much longer, and much bigger with limited functionality. With bio-inspired fluidic lenses, the lenses are much smaller and compact with more optical function. My main contribution is in developing the fabrication process for the fluidic lens and the optical design techniques that will improve the image quality. With only one single fluidic lens, I designed a miniature optical system that can function as a regular camera, micro-mode camera, or even a microscope. With two fluidic lenses, I designed a miniature optical zoom camera that has very large optical zoom (17 mm total track and >4X optical zoom). The working distance can be as short as 2 cm, which is difficult to design with traditional lens technology. The unique functions of the optical systems are made possible with the unique function of bio-inspired fluidic zoom lens. Finally, the unique technology of this optical device has particular interest in biomedical applications, such as minimally invasive surgery, retinal camera, etc. Several functions of biomedical applications are demonstrated. Most importantly, a demonstration gallbladder removal surgery was performed solely relying on the images acquires with the miniature zoom lens developed with fluidic lenses

Shared micromobility – the shared use of bicycles, scooters, or other low-speed modes – is an innovative transportation strategy growing across the United States that includes various service models such as docked, dockless, and e-bike service models. This research focuses on understanding how docked bikesharing and dockless e-bikesharing models complement and compete with respect to user travel behaviors. To inform our analysis, we used two datasets from February 2018 of Ford GoBike (docked) and JUMP (dockless electric) bikesharing trips in San Francisco. We employed three methodological approaches: 1) travel behavior analysis, 2) discrete choice analysis with a destination choice model, and 3) geospatial suitability analysis based on the Spatial Temporal Economic Physiological Social (STEPS) to Transportation Equity framework. We found that dockless e-bikesharing trips were longer in distance and duration than docked trips. The average JUMP trip was about a third longer in distance and about twice as long in duration than the average GoBike trip. JUMP users were far less sensitive to estimated total elevation gain than were GoBike users, making trips with total elevation gain about three times larger than those of GoBike users, on average. The JUMP system achieved greater usage rates than GoBike, with 0.8 more daily trips per bike and 2.3 more miles traveled on each bike per day, on average. The destination choice model results suggest that JUMP users traveled to lower-density destinations, and GoBike users were largely traveling to dense employment areas. Bike rack density was a significant positive factor for JUMP users. The location of GoBike docking stations may attract users and/or be well-placed to the destination preferences of users. The STEPS-based bikeability analysis revealed opportunities for the expansion of both bikesharing systems in areas of the city where high-job density and bike facility availability converge with older resident populations.