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Ou, Y., Rodriguez-Pardo, C., Al Khourdajie, A. ORCID: https://orcid.org/0000-0003-1376-7529, Rogelj, J. ORCID: https://orcid.org/0000-0003-2056-9061, Zhou, P., Mukkavilli, S.K., Tavoni, M., Clarke, L., Liu, Y., Wang, T., Oh, A. & McJeon, H. (2026). Artificial intelligence to support cross-disciplinary climate change research. Nature Climate Change 10.1038/s41558-026-02624-x. (In Press)

Li, P., Zhu, R., McJeon, H., Byers, E. ORCID: https://orcid.org/0000-0003-0349-5742, Zhou, P. & Ou, Y. (2025). Using deep learning to generate key variables in global mitigation scenarios. Nature Climate Change 10.1038/s41558-025-02352-8.

Blanco, G., Gerlagh, R., Suh, S., Barrett, J., de Coninck, H.C., Morejon, C.F.D, Mathur, R., Nakicenovic, N. ORCID: https://orcid.org/0000-0001-7176-4604, Ahenkorah, A.O., Pan, J., Pathak, H., Rice, J., Richels, R., Smith, S.J., Stern, D.I., Toth, Ferenc & Zhou, P. (2014). Chapter 5 - Drivers, trends and mitigation. In: Climate Change 2014: Mitigation of Climate Change. IPCC Working Group III Contribution to AR5. Cambridge University Press.