Photo of Adel Daoud

Adel Daoud

Senior Associate Professor

The overarching vision of my research is to harness the predictive power of machine learning—a form of artificial intelligence (AI)—guided by the conceptual insights of sociology to explain how poverty can exist in a world of sufficient resources.

A social scientist interested in global issues and new ways of portraying the world

I am an Associate Professor at Institute for Analytical Sociology, Linköping University, and Affiliated Associate Professor in Data Science and Artificial Intelligence for the Social Sciences, Department of Computer Science and Engineering, Chalmers University of Technology, Gothenburg, Sweden. Previously I held positions at Harvard University, University of Cambridge, and the Alan Turing Institute.

I study the impact of economic, political, and natural shocks on child poverty globally. I work on figuring out why we have so much poverty in a world of plenty. My research revolves around the question why societies often value financial resources over peoples’ health or lives. Another focal point is how families and their children suffer because of dysfunctional governments, institutions, or policies. Societies will develop, if children are enabled to flourish.

In my research I implement novel methodologies in machine learning and causal inference to identify population heterogeneities.

I have published in journals such as PNAS, World Development, American Journal of Economics and Sociology, Cambridge J of Economics, Food Policy, Epidemiology, and Ecological Economics.

Brief facts

Academic positions

  • 2021, March - Associate Professor (Biträdande professor) in analytical sociology, Institute for Analytical Sociology, Department of Management and Engineering, Linköping University, Norrköping, Sweden. 
  • 2020, Jun - Affiliated Associate Professor in Data Science and Artificial Intelligence for the Social Sciences, The Division of Data Science and Artificial Intelligence of the Department of Computer Science and Engineering, Chalmers University of Technology, Gothenburg, Sweden. 
  • 2018, Jan - Academy Research Fellow, Royal Swedish Academy of Letters, History, and Antiquities, Stockholm, Sweden.  
  • 2018, Jan - Research fellow in political economy (Honorary), Centre for Business Research, Judge Business School, University of Cambridge, Cambridge, the U.K
  • 2020, Jan. – 2021, March Associate Professor (Senior Lecturer), Department of Sociology, University of Gothenburg, Gothenburg, Sweden.
  • 2017, Oct. – 2019, Dec. Turing Fellow, the Alan Turing Institute, London, U.K.
  • 2016, Jul. – 2017, Dec. Research fellow in political economy, Centre for Business Research, Judge Business School, University of Cambridge, Cambridge, U.K.
  • 2016, Oct. – 2017, Oct. Postdoctoral Research Associate, Trinity Hall, University of Cambridge, Cambridge, U.K. 

Visiting positions

  • 2016, Jan - 2016, Jun. Department of Sociology, University of Cambridge, the UK.
  • 2015, Sept. – 2015, Dec. Fielding School of Public Health, University of California, Los Angeles, the U.S.
  • 2015, Feb. – 2015, Sept. Department of Economics, The New School for Social Research, New York, the U.S.
  • 2013, Sept. – 2015, Jan. The Max Planck Institute for the Studies of Societies, Cologne, Germany.
  • 2012, Mar. – 2012, Apr. Townsend Center for International Poverty Research, University of Bristol, the UK.
  • 2010, Feb. – 2010, Apr Faculty of Economics, University of Cambridge, the UK.

Education

  • 2016 B.A in Political Science, University of Gothenburg
  • 2011-2012 Pedagogical Training for Teaching in Higher Education, (various certificates), University of Gothenburg
  • 2011 PhD. in Sociology, Department of Sociology, University of Gothenburg, Gothenburg, Sweden.
  • 2006 M.A. in Sociology. Minor in: Political Science, Economics, and Mathematics. University of Gothenburg, & University of Jönköping, Sweden.

Awards

  • Academy Research Fellow, Royal Swedish Academy of Letters, History, and Antiquities, Stockholm, Sweden

Publications

2024

Sourabh Balgi, Jose M. Peña, Adel Daoud (2024) ρ-GNF: A Copula-based Sensitivity Analysis to Unobserved Confounding Using Normalizing Flows 12th International Conference on Probabilistic Graphical Models, p. 20-37 (Conference paper)
Sourabh Balgi, Jose M. Peña, Adel Daoud (2024) Counterfactually-Equivalent Structural Causal Modelling Using Causal Graphical Normalizing Flows 12th International Conference on Probabilistic Graphical Models, p. 164-181 (Conference paper)
Mohammad Kakooei, Adel Daoud (2024) Increasing the Confidence of Predictive Uncertainty: Earth Observations and Deep Learning for Poverty Estimation IEEE Transactions on Geoscience and Remote Sensing, Vol. 62, Article 4704613 (Article in journal) Continue to DOI
Adel Daoud, Fredrik D. Johansson (2024) The impact of austerity on children: Uncovering effect heterogeneity by political, economic, and family factors in low-and middle-income countries Social Science Research, Vol. 118, Article 102973 (Article in journal) Continue to DOI
Adel Daoud (2024) A theory of famines-A response Journal of International Development, Vol. 36, p. 2505-2512 (Article in journal) Continue to DOI

Earlier publications

Koumakhov, Rouslan and Daoud, Adel, 2020, Decisions and Structures: Dialogue between Herbert Simon and Critical Realists British Journal of Management

Daoud, Adel, Rockli Kim, and S V Subramanian, 2019 Evaluating the predictive power of socioeconomic factors in capturing women’s height in 58 low- and middle-income countries: a machine learning approach, Social Science & Medicine, 238 (2019) 112486

Daoud, Adel and Nandy, Shailen, 2019 Implications of the politics of caste and class on child poverty in India, Sociology of Development, Vol. 5, Number 4, pp 428-451, DOI: doi.org/10.1525/sod.2019.5.4.428

Daoud, Adel, Bernhard Reinsberg, Alexander Kentikelenis, Thomas Stubbs, Lawrence King., 2019 The International Monetary Fund’s Interventions in Food and Agriculture: An Analysis of Loans and Conditions. Food Policy, Vol 83, pp 204-218. doi.org/10.1016/j.foodpol.2019.01.005

Daoud, Adel, and Bernhard Reinsberg, 2018 Structural adjustment, state capacity, and child health: Evidence from IMF programs, International Journal of Epidemiology, Volume 48, Issue 2,  Pages 445–454

Daoud, Adel, 2018, Unifying studies of Scarcity, Abundance, and Sufficiency, Ecological Economics. Vol 147, Issue: May, pp. 208 – 217. Doi: 10.1016/j.ecolecon.2018.01.019.

Daoud, Adel, Elias Nosrati, Bernhard Reinsberg, Alexander Kentikelenis, Thomas Stubbs, and Lawrence King., 2017, ”Impact of International Monetary Fund programs on child health“, Proceeding of the National Academy of Sciences of the United States of America. doi: 10.1073/pnas.1617353114

Daoud, Adel, 2017, “A Framework for Synthesizing the Malthusian and Senian approaches: exemplified by the 1943 Bengal Famine”., Cambridge J of Economics, Vol 42, Issue 2, pp. 453-476, Doi: 10.1093/cje/bew071

Research

Ongoing research

18 million SEK (1.8 million USD) Combining satellite images and artificial intelligence to measure poverty in 1982-2020, and use these data to explaining the effects of World Bank and Chinese development programs in Africa, Swedish Research Council’s Research Environment Grant 2020 (Awarded to only about 8 projects in the social sciences. Acceptance rate 7 precent.) Principal Investigator

12 million SEK (1.2 million USD) Observatory of poverty: Combining image-recognition algorithms and satellite images to produce historical and geographical poverty data of Africa Swedish Research Council’s Consolidator Grant 2020 (Awarded to only about 20 projects across natural, medical and social sciences every second year. Acceptance rate 7 precent.) Principal Investigator

13 million SEK (1.3 million USD), Understanding society through register-based machine learning. Swedish Research Council’s Register-based research (acceptance rate 18%). Co-Principal Investigator.

Research interests

  • Political Economy and Development studies: global poverty; inequality, governance; natural disasters; economic crises.
  • Economic Sociology: theory of Scarcity, Abundance, and Sufficiency; theory of science; social stratification.
  • Methodology: causal inference, machine learning, topic modeling (quantitative text analysis).
Decorative background picture

Global lab AI

The vision of The AI and Global Development Lab is to combine AI and earth observation to analyze the causes and consequences of human development historically, geographically, and globally—thereby enhancing research on sustainability.

Teaching

Teaching interest

  • Political Economy and Development studies: (child) poverty; inequality, comparative policy and governance;
  • Economic Sociology: social theory, new economic sociology
  • Methodology: Quantitative methods, multilevel modeling, social network analysis, topic modeling (quantitative * textual analysis), R-programming.

News

Co-workers at the Institute of Analytical Sociology

Organisation