• Affiliate Assistant Professor, Global Health
  • Co-Founder & Executive Director, Surgo Foundation
  • Adjunct Assistant Professor, Department of Global Health and Population, Harvard T.H. Chan School of Public Health

United States

Phone Number: 
206-330-6272
Fax: 
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Biography 

Dr. Sema Sgaier is the Co-Founder and CEO of Surgo Ventures and Co-Founder of Surgo Foundation. Dr. Sgaier works at the intersection of behavior, data, and technology to solve complex global health and development problems. At Surgo, she leads a multi-disciplinary team of data scientists, behavioral scientists, technologists, and development experts. She led several large-scale programs, research and evaluation projects, and has worked with governments in India and Africa on public-health policy and large-scale delivery.

Prior to joining Surgo Foundation, Dr. Sgaier held several roles at the Bill & Melinda Gates Foundation. She led a portfolio on voluntary medical male circumcision for HIV prevention across eastern and southern Africa. As part of BMGF’s India Country Office, Dr. Sgaier led the scale-up of the foundation’s Avahan HIV prevention program in several states, managed its transition to the government of India, and developed data platforms for decision-making.

Dr. Sgaier has been selected as a Rising Talent by the Women’s Forum for the Economy and Society. She serves on the board of the BMGF's Alumni Network.

Education 
  • PhD (New York University)
  • MSc (New York University)
  • MA (Brown University)
  • BSc (Bogazici University)
Languages 
  • Arabic
  • Italian
  • Turkish
Health Topics 
  • Community Health Workers
  • Community-Based Primary Health Care
  • Epidemiology
  • Family Planning
  • Health Disparities
  • Health Information Systems
  • Health Interventions
  • Health Outcomes
  • Health Policy
  • Health Systems Strengthening and Human Resources Development
  • HIV Transmission
  • HIV/AIDS
  • Immunizations
  • Implementation Science
  • Infectious Diseases
  • Male Circumcision
  • Maternal Child Health (incl. Reproductive Health)
  • Maternal Mortality
  • Metrics and Evaluation
  • Mobile Health (mHealth)
  • Modeling
  • Prevention
  • Qualitative Research and Methods
  • Research
  • Sociobehavioral
  • TB
DGH Centers, Programs and Initiatives and Affiliated Organizations 
Expertise 

Scale up of large scale public health programs, innovation introduction into delivery platforms, Monitoring & Evaluation, Demand Generation, Data for Decision Making, sustainability planning, management systems, health policy development

Publications 

Huang VS, Morris K, Jain M, Ramesh BM, Kemp H, Blanchard J, Isac S, Sarkar B, Gothalwal V, Namasivayam V, Kumar P, Sgaier SK. Closing the gap on institutional delivery in northern India: a case study of how integrated machine learning approaches can enable precision public health.BMJ Glob Health. 2020 Oct;5(10):e002340. doi: 10.1136/bmjgh-2020-002340.
PMID: 33028696

Smittenaar P, Ramesh BM, Jain M, Blanchard J, Kemp H, Engl E, Isac S, Anthony J, Prakash R, Gothalwal V, Namasivayam V, Kumar P, Sgaier SK. Bringing Greater Precision to Interactions Between Community Health Workers and Households to Improve Maternal and Newborn Health Outcomes in India.
Glob Health Sci Pract. 2020 Oct 2;8(3):358-371. doi: 10.9745/GHSP-D-20-00027. Print 2020 Oct 1.
PMID: 33008853


Helfinstein S, Engl E, Thomas BE, Natarajan G, Prakash P, Jain M, Lavanya J, Jagadeesan M, Chang R, Mangono T, Kemp H, Mannan S, Dabas H, Charles GK, Sgaier SK. Understanding why at-risk population segments do not seek care for tuberculosis: a precision public health approach in South India. BMJ Glob Health. 2020 Sep;5(9):e002555. doi: 10.1136/bmjgh-2020-002555.
PMID: 32912854

Engl E, Smittenaar P, Sgaier SK. Identifying population segments for effective intervention design and targeting using unsupervised machine learning: an end-to-end guide.
Gates Open Res. 2019 Oct 21;3:1503. doi: 10.12688/gatesopenres.13029.2. eCollection 2019.
PMID: 31701090

Engl E, Sgaier SK.CUBES: A practical toolkit to measure enablers and barriers to behavior for effective intervention design. Gates Open Res. 2019 Mar 18;3:886. doi: 10.12688/gatesopenres.12923.2. eCollection 2019.
PMID: 31294419