Emily Aiken

CV | Google Scholar | GitHub | eaiken@ucsd.edu

Headshot

I am an assistant professor at UC San Diego, jointly appointed in the School of Global Policy and Strategy and the Halıcıoğlu Data Science Institute. My research interests are in data science and development economics, with a focus on analyzing large digital traces to inform the design and targeting of social protection and humanitarian aid programs. I was previously a postdoctoral scholar at Carnegie Mellon University Africa (2024-2025). I received my PhD from the UC Berkeley School of Information, where I was advised by Joshua Blumenstock. I also hold an MS (UC Berkeley) and BA (Harvard) in computer science.

News (See all news)

09/2026
Our paper on the meta-design of allocation algorithms was accepted at NeurIPS '26.
09/2026
Two new PhD students joined my group at UCSD in fall 2026: Ntuthuko Hlela and Isabella Rodas Arango.
09/2026
I will give a talk on our work on aid targeting in Bangladesh at the Zurich workshop on AI in applied economics.
05/2026
I am now an affiliate of CEGA and the Kigali Collaborative Research Center.
02/2026
Two new preprints on the relative value of prediction in allocation and cross-country evidence on phone data for poverty prediction.

Group

PhD Students

Isabella Rodas Arango (PhD student, UCSD, 2026-present)
Ntuthuko Hlela (PhD student, UCSD, 2026-present)
Prabhmeet Matta (PhD student, UCSD, 2025-present)

 

MS Students

Ayebilla Avoka (Research associate, KCRC, 2025-present)
Mustapha Alaba (Research associate, KCRC, 2025-present)
Sheila Wafula (Research associate, CMU Africa, 2025-present)

 

Undergraduate Students

Chloe Suwignjo (BS student, UCSD, 2026-present)

Work with me

I am looking for exceptional students and research assistants who are motivated to work on problems at the intersection of data science and development. I currently prioritize students based at UC San Diego with substantial expertise in programming, statistics, development economics, and/or human-computer interaction. If you are a prospective PhD applicant at UCSD, please apply to the data science PhD program at the Halıcıoğlu Data Science Institute. Please also send me an email so that I know to look out for your application. If you are a prospective postdoc, please reach out directly by email, and consider applying to postdoctoral fellowships at UCSD. If you are an MS or undergraduate student, please reach out by email with your transcript and CV, but note that I receive many such inquiries and may not be able to respond to all of them.

Papers

Preprints and Working Papers

Scalable targeting of social protection: When do algorithms out-perform surveys and community knowledge?
E. Aiken, A. Ashraf, J. Blumenstock, R. Guiteras, A. Mobarak
NBER Working Paper No. 33919 (2025).
Accepted for presentation at: Zurich workshop in AI and applied economics (2026).
          
Moving targets: The role of model and data recency in proxy means test accuracy.
E. Aiken, T. Ohlenburg, and J. Blumenstock.
Working Paper (2023).
Accepted for presentation at: NEUDC (2023), COMPASS (2023) and the NeurIPS Workshop on Computational Sustainability (spotlight talk, 2023).
          

 

Peer Reviewed Journal Articles and Conference Proceedings

Empirically understanding the value of prediction in allocation.
U. Fischer-Abaigar, E. Aiken, C. Kern, and J.C. Perdomo
NeurIPS (accepted, 2026).
     
Predicting well-being with mobile phone data: Evidence from four countries.
E. Aiken, J. Blumenstock, S. Milusheva, and M.M. Smith
AEA Papers and Proceedings (2026).
          
Estimating impacts with surveys vs. digital traces: Evidence from randomized cash transfers in Togo.
E. Aiken, S. Bellue, D. Karlan, C. Udry, and J. Blumenstock.
Journal of Development Economics 175 (2025).
Early versions: NBER Working Paper No. 31751 (2023).
     
Expanding perspectives on data privacy: Insights from rural Togo.
Z. Kahn, C. PERE, E. Aiken, N. Kohli, and J. Blumenstock.
CSCW (accepted, 2025).
          
Privacy gaurantees for personal mobility data in humanitarian response.
N. Kohli*, E. Aiken*, and J. Blumenstock.
Scientific Reports 14, No. 28505 (2024).
          
Fairness and representation in satellite-based poverty maps:
Evidence of urban-rural disparities and their impacts on downstream policy.
E. Aiken*, E. Rolf*, and J. Blumenstock.
IJCAI (2023).
Early versions: ICLR Workshop on Machine Learning for Remote Sensing (2023) and KDD Workshop on Humanitarian Mapping (2022).
Can strategic data collection improve the performance of poverty prediction models?
S. Soman, E. Aiken, E. Rolf, and J. Blumenstock.
ICLR Workshop on Practical ML for Development (2023).
          
Machine learning and phone data can improve targeting of humanitarian aid.
E. Aiken, S. Bellue, D. Karlan, C. Udry, and J. Blumenstock.
Nature 603, No. 7903 (2022).
★ Cover article
Early versions: NBER Working Paper No. 29070 (2022).
Phone sharing and cash transfers in Togo: Quantitative evidence from mobile phone data.
E. Aiken*, V. Thakur*, and J. Blumenstock.
ACM COMPASS (2022).
★ Best paper award
Home location detection from mobile phone data: Evidence from Togo.
R. Warren, E. Aiken, and J. Blumenstock.
ACM COMPASS (2022).
          
Targeting development aid with machine learning and mobile phone data:
Evidence from an anti-poverty intervention in Afghanistan.
E. Aiken, G. Bedoya, A. Coville, and J. Blumenstock.
Journal of Development Economics 161 (2022).
Early verisons: World Bank Policy Research Working Paper No. 10252 (2022). Extended abstract at ACM COMPASS (2020).
Towards the use of neural networks for influenza prediction at multiple spatial resolutions.
E. Aiken, A. Nguyen, C. Viboud, and M. Santillana.
Science Advances 7, No. 8 (2021).
Early versions: Extended abstract at NeurIPS ML for Health (2019).
     
Real-time estimation of disease activity in emerging outbreaks using internet search information.
E. Aiken, S. McGough, M. Majumder, G. Wachtel, A. Nguyen, C. Viboud, and M. Santillana.
PLoS Computational Biology 16, No. 8 (2020).
     

*Equal Contribution

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