Selected Publications

We present a model for estimating neonatal mortality rates for all countries. Neonatal mortality is an important indicator to track progess towards the Sustainable Development Goals. The model is used by the United Nations Inter-agency Group for Child Mortality Estimation.
Demographic Research

We present a Bayesian hierarchical model to estimate age-specific mortality at the subnational level. The model framework overcomes issues with estimating mortality in small populations, is flexible enough to be implemented in a wide variety of situations, and produces estimates of different measures of inequality across regions.

Recent Publications

More Publications

  • Deaths without denominators: using a matched dataset to study mortality patterns in the United States

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  • Estimating Subnational Populations of Women of Reproductive Age

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  • Global Estimation of Neonatal Mortality using a Bayesian Hierarchical Splines Regression Model

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University of California, Berkeley

  • Instructor, Formal Demography Workshop, June 2017
  • Instructor, Formal Demography Workshop, August 2015
  • Graduate Student Instructor, Demographic Methods, Fall Semester, 2014

University of Tasmania

  • Tutor, Calculus and Applications I, Semester 1, 2009
  • Tutor, Data Handling and Statistics I, Semester 2, 2008
  • Demonstrator, Chemistry I, Semester 1, 2008


Professional Experience

University of Massachusetts, Amherst

Graduate Student Researcher, January 2017 – Current

World Health Organization

Consultant, September 2016 – June 2017

Data Science for Social Good

Fellow, May 2016 – September 2016

Human Mortality Database

Graduate Student Researcher, January 2015 – May 2016

UNICEF Technical Advisory Group

Consultant, March 2014 – December 2015

The Centre for Aboriginal Economic Policy Research

Research Officer, April 2012 – December 2014

Reserve Bank of Australia

Analyst/Senior Analyst, February 2010 – June 2013

Recent Posts

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Berkeley Demography and Population Center affiliates will be presenting their work at PAA 2018. Check out some of their great work! Magali Barbieri Session 6-2: Contribution of drug poisonings to divergence in life expectancy Session 45-3: Cause-specific mortality data at the subnational level Boroka Bo Poster (Health and Mortality 1): Time poverty by ethnicity Gabriel Borges Session 68-4: Mortality rates from sibling histories Session 83-2: Bayesian melding to estimate census coverage Stephanie Child Poster (Health and Mortality 1): Social networks and stress Will Dow Session 72-3: Cuba’s cardiovascual risk factors Poster (Children and Youth): Parenting and Early Childhood Development in Indigenous and Non-Indigenous Mexican Communities Poster (Health and Mortality 2): Incentive-Based Interventions for Smoking Cessation Poster (Marriage, Families, Households, and Unions 2; Gender, Race, and Ethnicity): Paid parental leave Denys Dukhovnov Poster (Marriage, Families, Households, and Unions 1): Stress coping strategies Poster (Health and Mortality 1): Time poverty by ethnicity Dennis Feehan Session 68-4: Mortality rates from sibling histories Session 167-3: Estimating internet adoption using Facebook Joshua Goldstein: Organizer, Mathematical demography session Ron Lee Session 95-2: Life expectancy, pension outcomes and income Session 140-3: Aging and intergenerational flows Hayley Pierce Session 160-4: Risk and Protective Factors for Generational Refugee Children Danny Schneider Session 167-2: Facebook as a Tool for Survey Data Collection Session 174-4: Inequalities in parental time Ruijie (Mia) Zhong Poster (Marriage, Families, Households, and Unions 2; Gender, Race, and Ethnicity): Education and marriage in Japan …and me!


Introduction The Gompertz model is one of the most well-known mortality models. It does remarkably well at explaining mortality rates at adult ages across a wide range of populations with just two parameters. This post briefly reviews the Gompertz model, highlighting the relationship between the two Gompertz parameters, \(\alpha\) and \(\beta\), and the implied mode age at death. I focus on the situation where we only observe death counts by age (rather than mortality rates), so estimation of the Gompertz model requires choosing \(\alpha\) and \(\beta\) to maximize the (log) density of deaths.