Aron Culotta

Aron Culotta is a Full Professor of Computer Science at Tulane University, leading the Text Analysis in the Public Interest lab and serving as Director of the Tulane Center for Community-Engaged Artificial Intelligence and the Jurist Center for Artificial Intelligence. He holds a Ph.D. from the University of Massachusetts Amherst (2008), a M.S. from the same institution (2004), and a B.S. from Tulane University (2002). His work focuses on human-centered AI, leveraging NLP and social network analysis to address societal challenges in public health, emergency response, criminal justice, and civic transparency. Culotta has pioneered methods to track disease outbreaks, measure public health campaign effectiveness, and inform disaster response through social media analysis.

Research interests include natural language processing, causal inference, domain adaptation, and crisis informatics. Notable contributions span frameworks for reducing algorithmic bias, developing community-driven AI platforms, and analyzing social media dynamics for public good. His interdisciplinary projects are supported by over $4.8M in funding from NSF, NEH, and Tulane initiatives, among others. Culotta has mentored 33 capstone teams and advised 5 graduated PhD students now in academia and industry.

• Awards: Barbara E. Moely Service Learning Award (2024-2025), Nayar Prize Finalist (2016), Teacher of the Year (2018), and multiple best paper recognitions at AAAI and CSCW.
• Leadership: Spearheads the Tulane CEAI Center, fostering collaborations across 7 universities and 3 non-profits. Hosts workshops like PACE 2024 and Gulf Coast AI Social at NeurIPS.
• Education: Ph.D. in Computer Science (UMass Amherst, 2008), M.S. (UMass Amherst, 2004), B.S. (Tulane University, 2002).

His work emphasizes collaboration with community partners to ensure AI systems are inclusive, transparent, and equitable. Recent projects include a criminal court transparency platform and AI tools for tracking blight in New Orleans. Culotta’s research bridges technical innovation with societal impact, addressing urgent challenges like health equity and algorithmic fairness.