Paul Animesh is a researcher and strategist at the intersection of generative AI, user experience, and equitable education. His work focuses on improving access to engineering and technology careers for minoritized and queer students, and on designing data-informed systems that expand access to opportunities in higher education and workforce development.

Animesh combines qualitative research, including interviews, usability testing, and surveys, with quantitative analysis to translate user insights into practical solutions. His research explores digital inequalities, graduate admissions, and generative AI to support personalized learning and equitable pathways.

He holds expertise in UX research, generative AI, inclusive design, and mixed-methods analysis, and is proficient in SQL, Python, Tableau, Power BI, NVivo, MAXQDA, and SPSS. Animesh is currently pursuing a Doctor of Philosophy at the University of Georgia, specializing in engineering education and transformative practice.

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