David A Brocker

David Brocker is an adjunct Professor member in NYU SPS's DAUS program. He specializes in quantitative methods, research design, and applied data analysis. He holds a master’s degree in Experimental Psychology and has over seven years of experience teaching statistics and research methods at the undergraduate level. His teaching emphasizes conceptual understanding, practical application, and statistical literacy, with the goal of helping students feel confident engaging with data in both academic and professional contexts.

Professor Brocker’s instructional approach integrates real-world datasets, interactive tools, and technology- enhanced learning to make complex statistical concepts accessible and engaging. He regularly incorporates software such as R and SPSS into his courses and places particular emphasis on data visualization, reproducible research practices, and ethical data use. His courses are designed to support students with diverse academic backgrounds, balancing rigor with clarity and approachability.

His research interests include curiosity, emotion, and decision-making, with a particular focus on morbid curiosity and how individuals engage with emotionally intense or aversive information. His work explores how curiosity intersects with risk-taking, affective responses, and cognitive processing, often using experimental and mixed-methods designs. He is also interested in language use and meaning-making in sensitive or taboo domains.

In addition to teaching and research, Professor Brocker is actively involved in curriculum development and pedagogical innovation. He has worked on revising professional development courses to emphasize career ready skills, including research communication, data interpretation, and the ethical use of artificial intelligence in academic and workplace settings. He is particularly interested in how emerging technologies can be used responsibly to support learning, mentorship, and student self-reflection.

Professor Brocker is committed to inclusive teaching practices and creating learning environments that encourage curiosity, critical thinking, and persistence. He aims to help students develop both technical competence and confidence, preparing them to apply psychological science and data-driven reasoning across a wide range of professional paths.