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Ignat, Oana

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Oana Ignat

Curriculum Vitae (CV)

Dr. Oana Ignat is an Assistant Professor in the Department of Computer Science and Engineering at Santa Clara University. She earned her Ph.D. and completed her postdoctoral training in Computer Science at the University of Michigan in 2022.

Dr. Ignat directs the AIM Research Lab, where she and her students study Artificial Intelligence at the intersection of Natural Language Processing (NLP) and Computer Vision (CV). Her research focuses on building multimodal, multilingual, and culturally grounded AI systems that work equitably across diverse populations. A central goal of her work is to address disparities in AI performance across dimensions such as language, culture, socioeconomic status, gender, age, and geography, and to develop benchmarks, datasets, and models that better reflect global diversity.

Dr. Ignat’s work emphasizes AI for social good and responsible deployment, with applications spanning emotion understanding, cross-cultural reasoning, low-resource languages, and socioeconomic fairness in foundation models. She has published extensively at top venues including ACL, NAACL, EMNLP, NeurIPS, and AAAI, and her research has received multiple best paper and best resource awards. Her contributions include widely used benchmarks and evaluation frameworks for multilingual emotion recognition, cross-cultural multimodal reasoning, and fairness analysis of large vision–language models.

Beyond research, Dr. Ignat is deeply committed to broadening participation in computing and mentoring students from underrepresented backgrounds. She is a co-organizer of the NLP for Positive Impact workshop series at ACL and EMNLP, has led SemEval shared tasks on emotion recognition in low-resource languages, and plays an active role in the ACL global mentorship program, helping early-career researchers navigate academia and industry worldwide. Through her research, teaching, and outreach, she aims to ensure that AI technologies are developed with and for the diverse communities they impact.

Courses
  • CSEN 498: Ph.D. Thesis
  • CSEN 497: Master's Thesis
  • CSEN 493: Industry-Mentored Projects (AI Practicum) under MS in AI 
  • CSEN 346: Natural Language Processing
  • CSEN 266: Artificial Intelligence
  • CSEN 140: Machine Learning and Data Mining
  • CSEN 29: AI Literacy
  • CSEN 12: Data Structures and Algorithms
Publications

An up-to-date publication list is available on Google Scholar.