LTC Student Researchers
I am an Undergraduate Student Researcher at the William and Barbara Leonard Transportation Center (LTC), majoring in Computer Science. At the LTC, my research focuses on artificial intelligence, particularly retrieval-augmented generation (RAG) systems that aim to improve reliable information access in high-stakes domains. My work involves contributing to both system development and evaluation, with an emphasis on creating tools that are transparent, trustworthy, and accessible. This experience allows me to strengthen my technical skills while also exploring how technology can be designed to better support human decision-making.
Beyond my research, I am an IEEE student member and serve as an instructional student assistant, where I help mentor undergraduates in computer science courses. These experiences have given me the opportunity to combine my passion for technology with teaching, communication, and collaboration.
My academic interests extend to artificial intelligence, machine learning, quantum computing, and the future of human-AI collaboration. Looking ahead, I plan to pursue a Ph.D. in Computer Engineering/Computer Science with a focus on machine learning and quantum computing, in order to continue building on these research directions and contribute to advancing solutions for complex, real-world challenges.
Iman Reihanian is a Machine Learning Scientist and graduate student in Computer Science at California State University, San Bernardino (CSUSB). He holds a bachelor’s degree in Computer Science and Artificial Intelligence from the University of California, Irvine, and is currently pursuing his master’s degree while preparing for doctoral studies in Artificial Intelligence and Machine Learning.
At CSUSB, Iman serves as a research assistant under Professor Yunfei Hou at the William and Barbara Leonard Transportation Center, where his work focuses on generative AI, anomaly detection, graph-based modeling, and algorithmic complexity. He has co-authored and presented peer-reviewed research on the integration of generative AI in computer science education and is developing new frameworks to explore foundational questions in theoretical computer science. In addition to his academic research, Iman has professional experience as a software programmer, with expertise in data science, and applied machine learning. His broader research interests include large language models, generative AI applications in education, graph neural networks, and the intersection of AI with human-centered systems. He has also been awarded competitive research grants and actively participates in academic conferences and scholarly communities.
Shaun Colegado is an Undergraduate Researcher at the William and Barbara Leonard Transportation Center (LTC) at California State University, San Bernardino. He is currently pursuing a Bachelor of Science in Computer Science, with an expected graduation in December 2026. As an avid enthusiast for mass transit and rail systems, Shaun's work at the LTC allows him to bridge his passion for transportation with his growing expertise in artificial intelligence.
His research interests focus on the trustworthiness and transparency of human-AI systems, contributing to projects that evaluate the reliability of AI-generated explanations for complex models. His background also includes international experience from his exchange year at International Christian University in Tokyo, where he supported social psychology research on AI dependency by analyzing the performance of various AI models. After completing his undergraduate studies, Shaun plans to pursue a Ph.D. in Human-Computer Interaction (HCI).
Past Student Researchers
Ahmed Sahlem Burgos Nagi
Alberto S. Sanchez
Bhavik Khatri
Dorlins Villalobos
Gabriel Lara
Holly Chea
Jordan Leffew
Paul Sena
Sai Kalyan Ayyagari
Vaishnavi Rode
Yasamin Rasouli