About

I am an Academic Affiliate in the Department of Sociology at the University of South Carolina, where I continue a longstanding research collaboration with Matthew E. Brashears. Our work together dates to the founding of Cornell's Social Science Research Laboratory and now includes research on collective problem solving and information change in networks of machine agents, latent diffusion, and error correction in adaptive search.

At Iron Light Public Affairs, I led behavioral science, experimental design, measurement, and applied research across political, advocacy, and public affairs engagements. The work included field and survey experiments, audience and message research, behavioral measurement, and the integration of quantitative, qualitative, and computational evidence into research and campaign decisions. I sourced and managed research vendors, writing requests for proposals, evaluating bids, and selecting vendors for work from data collection through reporting.

I developed reusable analytical tools and research workflows, including systems that used large language models for coding, measurement, and analysis. Much of the work involved evaluating interventions in changing field environments, where observed outcomes could reflect several competing influences. Research designs and analyses were developed around those conditions, with particular attention to what could be attributed to an intervention and what remained uncertain.

At Roku, I developed behavioral measurement and analytical infrastructure and conducted research across streaming, audience, platform, and organizational contexts. The work combined large-scale behavioral data with surveys, qualitative evidence, and other sources to investigate individual and population-level patterns. Some analyses drew on streaming data covering tens of millions of households. This work also involved sourcing and managing external research vendors, including requests for proposals, bid evaluation, and vendor selection, for work in the United States and internationally.

I built measurement frameworks, behavioral taxonomies, segmentation methods, dashboards, and recurring analytical systems. These made it possible to examine patterns across data sources originally collected for different purposes, including sources with different units of observation and different measurement limitations.

An important part of this work was determining how concepts drawn from behavioral research could be measured meaningfully in platform and organizational data. Observed actions were often informative, but did not necessarily establish the motivations behind them. Combining behavioral traces with other evidence was therefore part of the research design, not simply an additional analytical step.

At Meta, I conducted behavioral and computational research involving randomized experiments, network modeling, measurement, and large-scale behavioral data. Research topics included civic participation, integrity, economic inequality, public-health behavior, and questions arising from emerging technologies and platform features. I also managed qualitative and quantitative research vendors in the United States and internationally across a wide range of projects. I identified vendors, wrote requests for proposals, evaluated bids, and oversaw the work from data collection through reporting.

The work included survey and field research and collaborations with the National Institutes of Health and Centers for Disease Control and Prevention on behavior during the COVID-19 pandemic. These studies brought together experimental methods, computational analysis, and evidence from populations and social relationships that are difficult to observe outside large platforms.

The research required attention to the distinctive statistical and substantive problems of platform data, including dependence among observations, heterogeneous populations, and the relationship between observed behavior and the constructs being measured.

I held a dual visiting appointment with Linköping University and Stockholm School of Economics through the Institute for Analytical Sociology. My research focused on diffusion, network structure, collective behavior, computational social science, and experimental methods.

The appointment included research using Swedish population-register data, public and invited research presentations, and mentoring doctoral students. It extended my work on how network structure and local interaction shape the movement of information and the emergence of collective outcomes.

At the University of Kentucky, I directed an independent research program investigating social networks, diffusion, communication, error, perception, coordination, and collective behavior. My research combined experiments with human participants, network analysis, and computational models to study how local interactions and individual decisions generate larger social and organizational patterns.

The program included federally supported human social-network experiments, computational studies of diffusion and problem solving, and theoretical work on information transmission and collective behavior. I published peer-reviewed research, collaborated with scholars across disciplines, mentored doctoral students, and presented research to academic and practitioner audiences.

I taught Applied Network Analysis and Negotiations, using behavioral theory, quantitative methods, and simulation-based instruction. I also contributed research expertise to projects conducted through university partnerships.

My doctoral research examined social networks, information transmission, error, and collective behavior through experimental, computational, and theoretical approaches. My dissertation, Innovation from Imitation: Error in Diffusion Processes, investigated how errors introduced during social transmission affect diffusion and collective outcomes.

Alongside that research, I managed operations for the Cornell Business Simulation Laboratory from 2012 to 2016. The laboratory supported approximately five to ten behavioral studies per week. I supervised and trained undergraduate experimenters and managed participant recruitment, research protocols, scheduling, study administration, and quality control for experiments conducted under institutional review board oversight.

Earlier, from 2010 to 2012, I co-founded the Cornell Department of Sociology's Social Science Research Laboratory with Matthew E. Brashears. We established its physical and technical infrastructure, acquired research equipment, developed participant recruitment and scheduling procedures, and integrated the laboratory with university research resources.

These responsibilities established an enduring part of my research practice: developing and managing the instruments and environments needed to study behavior, rather than treating research infrastructure as something separate from the scientific work.

Through Graystone Industries, I conduct commissioned research and develop computational tools and systems for research and analysis. The work spans experimental design, behavioral and organizational research, social-network analysis, simulation, AI-system evaluation, evidence synthesis, analytical pipelines, and custom research software.

Some engagements begin with a defined empirical question and existing data. Others require building the instruments, measures, experimental environments, or software needed to investigate the question. I use AI-assisted development extensively for implementation, automation, and testing, while retaining responsibility for research design, validation, and interpretation.

This independent practice also provides a setting for developing computational research methods and systems beyond the requirements of individual engagements.