Category: Fellow Animesh Paul

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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In Works & News:

  • Canary in the Mine: An LLM Augmented Survey of Disciplinary Complaints to the Ordre des ingénieurs du Québec (OIQ) (Peer Reviewed)
  • Developing the Permanent Symposium on AI (poster): Presented at Engineering and Public Policy Division (EPP) Poster Session
  • Whole-Person Education for AI Engineers: Presented to CEEA (Peer Reviewed)
  • WIP: Gen AI in Engineering Education and the Da Vinci Cube (Peer Reviewed)
  • Work in Progress: Exclusive Rhetoric in AI Conference Mission Statements
  • What We Do Not Know: GPT Use in Business and Management
  • Path to Personalization: A Systematic Review of GenAI in Engineering Education
  • Exploring and Expanding Support for International Students in Engineering: Faculty Reflections Beyond Academic Boundaries
  • Reimagining AI Conference Mission Statements to Promote Inclusion in the Emerging Institutional Field of AI