2025 Summer Undergraduate Research Fellows
The 2025 SURF program was funded by a generous private donor and the UC Davis Office of Research.
Vikram BhatMajor: Cognitive ScienceMentors: Dr. Jesus Barajas and Weijing WangVikram researched San Francisco's traffic safety progress over the last 10 years. This involved reviewing policy documents and statistically analyzing project distributions with equity characteristics. |
Jeremy ElvanderMajor: Data Science and Geographic Information Systems (GIS)Mentor: Dr. Aaron RabinowitzJeremy worked to design and implement a hierarchical grouped genetic algorithm via modified NSGA-II to optimize public bus network fleet size and technology composition across multiple objectives. He worked on the mathematical formulation of the scheduling problem and fitness functions, as well as the algorithm code. He utilized current literature to inform project development. |
Aidan GleasonMajor: Environmental Science & ManagementMentor: Dr. Jamey VolkerAidan analyzed state highway expansion projects across California to estimate the scale and spatial distribution of induced travel, aiming to evaluate the success of numerous transportation policies. Using the NCST Induced Travel Calculator and ArcGIS Pro, he calculated annual VMT impacts from new lane miles and examined how these projects intersect with urbanized areas and disadvantaged communities. |
Isabella GonzalesMajor: StatisticsMentors: Dr. Kari Watkins & Maha AhmadIsabella investigated the service improvements Capitol Corridor can invest in to improve ridership, specifically focusing on gaining the non-commuter demographic, by analyzing survey data. |
Leon KangMajor: Computer Science and EngineeringMentor: Dr. Siddhartha GulhareLeon supported the development of a white paper on adopting Cargo E-Eikes for last mile deliveries, analyzing factors such as currently available bikes and infrastructure. By accounting for factors such as the optimal proximity to microhubs and zoning limitations for industrial or commercial areas, cargo e-bikes could serve as an efficient solution for the most polluting part of the delivery process. |
Talia LeviMajor: Sustainable Environmental Design; DesignMentor: Dr. Elisa BarbourTalia contributed to a project investigating complete streets policies in California by analyzing local plans and projects in Berkeley and Oakland. She prepared a case study report on the motivations, barriers, and successes of road reallocation projects implemented in the two cities. |
Ben MatsubayashiMajor: Sustainable Environmental DesignMentor: Dr. Elisa BarbourBen contributed to a report on California’s Complete Streets policy by researching and writing a summary of case study projects and legislation in Los Angeles. He analyzed the struggles and successes of local governments and advocacy groups in gaining public support and resources to carry out safety initiatives. |
Samriddhi (Sam) MehrotraMajor: Managerial EconomicsMentor: Dr. Aviv SterenSam analyzes California survey data from the UC Davis Electric Vehicle Research Center to compare the monthly cost of ownership across four vehicle powertrain types. The analysis examines how household vehicle expenses vary by vehicle type and user characteristics. Results highlight the conditions under which electric vehicles reduce costs, where they impose higher expenses, and how these trade-offs shape household expenses. |
Susannah OlsondayMajor: Mechanical EngineeringMentors: Dr. Kari Watkins & Marcus ChanSusannah investigated the utility of mobile ticketing data in finding key ridership patterns. She analyzed Unitrans mobile ticketing data to find spatiotemporal ridership patterns and passenger behavior. She conducted a literature review to synthesize research on digital ticketing data analysis. |
Arly ReyesMajor: Environmental Science and ManagementMentor: Dr. Jesus BarajasArly studied how access to schools in Jefferson County Public Schools varies by transportation mode, income, race, and car ownership, highlighting disparities in a district with a desegregation program. Using custom spatial data and travel time analysis in R Studio, the research examined how public transit influences equitable access to education. |
Sonali SenthilMajor: Environmental Policy Analysis & Planning; EconomicsMentor: Dr. Scott HardmanSonali worked on coding and analysing survey responses related to consumer views on and preferences for amenities at public DC fast charging stations. This research will be helpful to understand how public EV charging stations can be profitable witout relying on government subsidies. |
Simone ShupperMajor: Sustainable Environmental DesignMentor: Dr. Dillon Fitch-PolseSimone worked on evaluating the accuracy of manual raters to establish a baseline count for comparing computer automated counts. This research will help the broader study of testing sensor accuracy, and the data from this study will allow CalTrans to purchase and use more effective sensors to collect safety data for active transportation that occurs within areas monitored by CalTrans. |
Annapurna SivaMajor: Environmental Science and ManagementMentor: Dr. Susie PikeAnnapurna worked to better understand considerations and barriers for transit agency mergers and coordination efforts by conducting interviews with multiple transit operators throughout California. She also helped revise and update the literature review and conduct descriptive statistics for transit partnerships and innovations during COVID-19. |
Summer TresemerMajor: ChemistryMentors: Dr. Jesus Velazquez, Pranay NinaweI worked on methods of synthesis of electrocatalysts for hydrogen evolution and carbon dioxide reduction reactions. These electrocatalysts have the potential to reduce cost and improve efficiency of manufacturing alternative fuels. |
Cayden YuMajor: Aerospace Engineering, Mechanical EngineeringMentor: Dr. Michael ZhangCayden worked on designing an H-infinity controller to achieve lane tracking and stability robustness of an automobile. After deriving the equations of motion and calculating the transfer function of the controller, the weighting function were tuned through an iterativee process to achieve a controller that is able to reject external disturbances and achieve a lateral deviation of less than 0.5m from the desired pathway. |