Project Results
Conference Presentations
Bus Departure Offset Prediction
Radhakrishnan, J., Uyematsu, D., Collazo, M., Hou, Y., & Salloum, M. (2021). Towards Predicting Bus On-Time Performance in the Inland Empire, 2021 IEEE International Conference on Big Data. https://bigdataieee.org/BigData2021/
Using Big Data to Quantify Public Transit Equity
Reed, P., Tan, S., Chea, H., Zhang, Y., Hou, Y., & Collins, K. (2022, April 19). Using Big Data to Quantify Public Transit Equity. Leonard Transportation Center 2022 Regional Mobility Dialogue Series: Optimizing Transportation Equity Through Big Data. https://www.csusb.edu/leonard-transportation-center/conversations/events/2022-inland-empire-dialogue-series/april-event
Reed, P., Tan, S., Chea, H., Zhang, Y., Hou, Y., & Collins, K. (2022). Shifts in Public Transit Equity During the COVID-19 Pandemic: A Case Study at Riverside, California. American Society of Civil Engineers (ASCE) International Conference on Transportation & Development (ICTD) 2022.
Meet the Research Team
Holly Chea is a graduate student in the MBA program at California State University San Bernardino. Her concentration area of study is in Business Intelligence and Information Systems. Holly is interested in the collection, processing, analysis, and interpretation of data to help in data informed decision making. She previously worked for the last seven years in the financial industry in Private Banking and briefly in the Mortgage Industry. At CSUSB she served as a Board of Director for Associated Students Inc. (ASI) and as Treasurer of Society of Human Resource Management (SHRM).
Holly is looking forward to working with this team combining her love for the Inland Empire with Big Data Analysis to impact the transportation sector of this area.
Martin Collazo is a fourth-year computer engineering student at California State University, San Bernardino, with an interest in big data analysis as well as electric vehicle efficiency and value. Martin has always been interested in vehicle data analysis with a focus in optimization. When the LTC Research Challenge opportunity presented itself, he instantly jumped at the chance to participate in a real-world, real-life research issue with traffic in the Inland Empire. He is excited to be a part of the LTC research team and help make the public transportation system more efficient.
Preston Reed is a computer science graduate student at University of California, Riverside. Preston has a strong interest in artificial intelligence and machine learning as well as a budding interest in urban planning and research. Some of his personal hobbies include hiking, traveling, and producing electronic music. Preston is eager to apply his knowledge and skills in computer science with the LTC research team and add value to the ongoing discussion of improving public transportation in the Inland Empire.
Jai Radhakrishnan is a junior at the University of California, Riverside studying computer Science. Jai has a strong inclination for data science and machine learning. Some of his hobbies include writing short stories, reading novels, and building up some personal projects like a chess engine. He is eager to apply his prior knowledge in data science and visualization into an academic environment and create an impact on the society that has shaped him!
Sheng Tan is a fourth-year civil engineering major with an emphasis on geospatial engineering at California State Polytechnic University Pomona. Sheng is interested in the transportation engineering industry. He is also an active member of Cal Poly Pomona’s campus community, serving as Cal Poly Rose Float’s Club Chair and California Land Surveyor Association Cal Poly Pomona Student Chapter’s Conference Chair. He is looking forward to working as a Research Assistant at CSUSB’s Leonard Transportation Center along with other amazing candidates from different campuses and learning more about transportation related topics.
Daniel Uyematsu is a fourth-year civil engineering student at Cal Poly Pomona interested in transportation engineering. Daniel hopes to contribute to the LTC Student Research Challenge with his skills in Python and visual programming along with his educational background in civil engineering. He plans to be an industry professional that applies programming to transportation engineering.
Faculty Advisors:
- Kimberly Collins, Ph.D. - California State University, San Bernardino
- Yunfei Hou, Ph.D. - California State University, San Bernardino
- Yongping Zhang, Ph.D. - Cal Poly Pomona
- Mariam Salloum, Ph.D. - University of California, Riverside