Data Science Talk Series

The Data Science Talk Series aims to bring together professionals, researchers, and students to explore and discuss the latest trends, innovations, and challenges in the field of data science. The series will host guest speakers, industry experts, and academics who present on a wide range of topics such as machine learning, artificial intelligence, data visualization, big data, and ethical considerations in data usage.

The purpose of the series is to foster a collaborative environment for learning and knowledge exchange, providing attendees with insights into cutting-edge developments and best practices. It also serves as an opportunity for networking, career growth, and the sharing of practical experiences and case studies. Whether for beginners or advanced practitioners, the series helps participants stay informed about the evolving landscape of data science and its real-world applications. Questions or comments, please contact Dr. Haihua Chen.

Spring 2025 Schedule

Dr. Hanchen Jiang

Title: Evaluating Rent Control Policy - The Case of Rent Stabilization in New York City

Speaker: Dr. Hanchen Jiang, Assistant Professor of Economics at the University of North Texas

Time: February 13, 2025 at 1:30 pm - 3:00 pm

Room: E297L, Discovery Park, UNT

Zoom link

Coordinator: Dr. Haihua Chen

Dr. Xuan Lu

Title: Towards Sustainable Remote Work: A Practice of Human-Centered Data Science

Speaker: Dr. Xuan Lu, Assistant Professor at the University of Arizona

Time: February 27, 2025 at 1:30 pm - 3:00 pm

Room: E297L, Discovery Park, UNT

Format: Online Zoom link and In-person: E297L, Discovery Park, UNT

Coordinator: Dr. Yunhe Feng

Abstract: The COVID-19 pandemic has dramatically accelerated the decentralization processes of organizations, such as the transition from in-person workplaces to remote work. With data accumulated through these emergent changes on both the organization side and the worker side, it is crucial to involve data science methodologies to understand these changes, predict their outcomes, and prepare for future developments. In this talk, I will introduce a comprehensive human-centered data science approach (especially featuring machine learning and causal inference) to analyzing and improving the sustainability of remote workers and teams. In particular, the presented work will focus primarily on the open-source software development community analyze the factors that affect the sustainability of virtual teams under shock, and promote the long-term contribution of individual developers.

Speaker Bio: Xuan Lu is a tenure-track assistant professor at the College of Information Science, at the University of Arizona. Her research focuses on creating novel methodologies of human-centered data science and using them to understand and optimize the activities and outcomes of our future human society, especially those triggered by technological innovations, with a recent emphasis on the domain of the Future of Work. Her work has been published in multiple leading conferences and journals in the field of data science, and she is a recipient of the WWW Best Paper Award (2019) and the Microsoft Research Asia Fellowship (2017).