Long - Term Focus
Long - Term Focus
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The lab investigates gender dynamics in the workplace, examining how negotiation, creativity, self-promotion, and identity shape professional experiences and outcomes. Our ongoing work includes the Triangulation Project, which is currently under advanced review at a premier social science journal. Students and researchers develop core methodological skills through hands-on training in conceptual modeling, survey design, and empirical research.
Lab Guest Speaker Series
Lab Guest Speaker Series
With a PhD in Marketing from the University of Illinois at Urbana–Champaign, where she researched consumer behavior and digital platforms. Working as a Staff Data Scientist at Meta, she focuses on advertising measurement and experimentation. She talked about a range of quantitative methods, including A/B testing, difference-in-differences, propensity score matching, and machine learning, and how they guide product development and optimization.
With a PhD in Marketing from the University of Illinois at Urbana–Champaign, where she researched consumer behavior and digital platforms. Working as a Staff Data Scientist at Meta, she focuses on advertising measurement and experimentation. She talked about a range of quantitative methods, including A/B testing, difference-in-differences, propensity score matching, and machine learning, and how they guide product development and optimization.
With a PhD in Organizational Behavior from Stanford Graduate School of Business, Lara talked about her research, which broadly lies in the intersection of identity, culture, and social networks, as well as her experience in a variety of methods, combining cutting-edge natural language processing models with surveys and field experiments.
With a PhD in Organizational Behavior from Stanford Graduate School of Business, Lara talked about her research, which broadly lies in the intersection of identity, culture, and social networks, as well as her experience in a variety of methods, combining cutting-edge natural language processing models with surveys and field experiments.
Graduate Student Research Projects
Graduate Student Research Projects
Kimberly Bautista
Kimberly Bautista
Kimberly’s master’s thesis examines how the language organizations use in their diversity statements can influence applicant perceptions and ultimately strengthen diversity applicant pools. Building off of Ely & Thomas (2001), three organizational perspectives, and Georgeac & Rattan's (2023) research on organizational diversity cases, this study introduces three different methods of framing diversity. Learning and Integration Perspective, Access and Legitimacy Perspective (Business Case), and the Discrimination and Fairness Perspective (Fairness Case). We are also interested in testing these statements’ effects in first-generation college students, a group that makes up nearly 40% of undergraduate students and represents a growing segment of the new workforce.
Miriam Alfano
Miriam Alfano
Miriam’s master’s thesis investigates how employees' personal attitudes toward the use of AI at work influence theirlevels of work engagement. Based on the Technology Acceptance Model, we suggest that the perceived utility of AI (an indicator of a positive attitude) will increase engagement, as it enables employees to leverage AI’s benefits. Incontrast, AI-induced insecurity is hypothesized to be associated with lower levels of work engagement. We further investigate whether a higher degree of perceived organizational support moderates both the positive and negative relationships hypothesized above, allowing employees to feel more engaged with their work despite the fear induced by AI, and even more so when they perceive AI as useful.
Shree Kritika Shanmugavel
Shree Kritika Shanmugavel
Krithika’s Master’s thesis examines how individuals transition from non-IT to IT occupations, focusing on the influence of gender, education level, and STEM background. Using large-scale workforce data, the research investigates who is most likely to enter IT careers and under what conditions. The project also analyzes broader trends such as age at transition, occupational tenure, salary changes, industry origins, and generational patterns to observe how IT has evolved over time.
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