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Angana Borah wins Michigan fellowship for AI research
The doctoral candidate is recognized for research on inclusive AI, advancing work on bias, culture, and language models.
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Pranavi Sharma - Thu, 09, Apr 2026
- 02:14 EDT
- 11
Angana Borah / University of Michigan
Angana Borah, who was born in the Indian state of Assam, has received the Rackham Predoctoral Fellowship on April 8, 2026, recognizing her research progress in artificial intelligence and supporting her doctoral work at the University of Michigan.
Borah is a doctoral candidate in computer science and engineering. Her dissertation focuses on evaluating and improving large language models to promote cultural inclusivity, truthful communication, and social well-being.
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The fellowship is awarded annually to a select group of doctoral candidates who demonstrate strong progress toward completing their dissertations. Selection is based on research outcomes, including publications and conference presentations, along with contributions to teaching, mentorship, or service.
Borah’s work examines a key issue in modern AI systems. Many large language models are trained on data that largely reflects Western, educated, industrialized, rich, and democratic populations. This imbalance can result in systems that miss regional differences, reinforce stereotypes, or behave inconsistently in group interactions.
Warm congratulations to @AnganaBorah2 for receiving a @umichgradschoolRackham Predoctoral Fellowship!
— MichiganAI (@michigan_AI) April 8, 2026
The award recognizes Angana’s exemplary research progress and will support her continued work on culturally inclusive and socially responsible #AI.https://t.co/nqgdE451fL pic.twitter.com/IUbYIDacWm
Her research explores these challenges through multi-agent AI systems and evaluation methods grounded in social context. In one study, she analyzed interactions between multiple language model agents. The findings showed that even when a single model appears unbiased on its own, biased patterns can re-emerge and intensify during interactions between agents.
In another project, Borah studied cross-cultural image captioning. She developed a framework called MosAIC, which uses agents with different cultural perspectives to produce more context-aware captions. The work also introduced datasets and evaluation metrics designed to measure how cultural information is reflected in model outputs.
Her research has been presented at major conferences, including ACL, EMNLP, NAACL, EACL, and AAAI.
“Angana has already distinguished herself as a talented and impactful researcher,” said Rada Mihalcea, her advisor. “Few students at her stage can both set the research agenda by identifying open problems of global importance, and also deliver concrete, high-impact solutions that are already shaping the field.”
Beyond her research, Borah has contributed to academic and global initiatives. She has co-organized workshops such as NLP for Positive Impact at ACL 2025 and participated in programs focused on teaching and outreach in Kenya and Romania.
The fellowship will support her continued work on developing AI systems that function more equitably across different cultural and social contexts.
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