In addition to the most pressing issues of the day, scholars at the Freeman Spogli Institute for International Studies focus their research on many regions of the world, from Beijing to Brazil.
Research Spotlight
The Ripple Effects of China’s College Expansion on American Universities
Researchers at SCCEI trace how China’s unprecedented expansion of higher education has impacted U.S. graduate education and local economies surrounding college towns.
While Nayib Bukele's style of authoritarianism may have some successes on paper, Beatriz Magaloni and Alberto Diaz-Cayeros argue that the regime is headed for a reckoning.
Time for Iran to Make a No-enrichment Nuclear Deal
The time has come for Iran’s leaders to reconsider their past intransigent, deceptive posture and instead pursue a nuclear power program that will benefit the Iranian people, write Abbas Milani and Siegfried Hecker.
Stanford Law’s Lisa Larrimore Ouellette and SHP’s Josh Salomon co-author report to address a persistent flaw in the U.S. health system: prioritizing treatment investment based on market potential rather than medical necessity.
While the attacks have likely inflicted significant damage on critical nuclear facilities in the short term, their ultimate success in halting Iran’s nuclear program is far from assured
While AI can enhance efficiency in areas like predictive maintenance and operational planning, its integration into the nuclear enterprise poses significant risks, some of which are inherent in the nature of ML.
Proceedings of the National Academy of Sciences (PNAS),
June 6, 2025
The number of acutely food insecure people worldwide has doubled since 2017, increasing demand for early warning systems (EWS) that can predict food emergencies. Advances in computational methods, and the growing availability of near-real time remote sensing data, suggest that big data approaches might help meet this need. But such models have thus far exhibited low predictive skill with respect to subpopulation-level acute malnutrition indicators. We explore whether updating training data with high frequency monitoring of the predictand can help improve machine learning models’ predictive performance with respect to child acute malnutrition by directly learning the dynamic determinants of rapidly evolving acute malnutrition crises. We combine supervised machine learning methods and remotely sensed feature sets with time series child anthropometric data from EWS’ sentinel sites to generate accurate forecasts of acute malnutrition at operationally meaningful time horizons. These advances can enhance intertemporal and geographic targeting of humanitarian response to impending food emergencies that otherwise have unacceptably high case fatality rates.
Despite his election victory, Lee faces a challenging road ahead, both personally and politically. It remains to be seen whether Lee’s administration can rise above partisan politics and rebuild public trust through meaningful reforms.
