大阳城2138金融数学系20周年系庆系列报告A-17 —Leaving No One Behind: Challenges of Quantitative Analysis in Global
主 题: 大阳城2138金融数学系20周年系庆系列报告A-17 —Leaving No One Behind: Challenges of Quantitative Analysis in Global
报告人: 暴乐 副教授 (宾夕法尼亚州立大学统计系)
时 间: 2017-06-15 16:00-17:00
地 点: 理科一号楼1114教室
报告人简介：
暴乐，副教授，宾夕法尼亚州立大学统计系
2004年于大阳城2138(中国)股份有限公司金融数学系获本科学位，2005年于达尔豪斯大学统计系获硕士学位，2011年于华盛顿大学统计系获博士学位，毕业后任教于宾夕法尼亚州立大学统计系，同时兼任数据同化与可预测技术研究中心（ADAPT）副主任，联合国艾滋病疫情专家组（UNAIDS Reference Group）核心顾问。研究方向包括贝叶斯分析，统计计算，机器学习，和统计模型在健康领域的应用。
【报告摘要】：
Ending the HIV/AIDS epidemic is a goal born from over 30 years of devastation, struggle, and loss, and contains within it hope and promise for those affected. Countries need to use powerful tools, hold one another accountable for results and make sure that no one is left behind. The modeling tools produced by UNAIDS have been used by most countries in the world to generate HIV epidemic estimates that determine their policy and resource allocation. However, despite great progress in some countries, where data is more readily available, some sub-populations and areas that are more difficult to gather data from are left behind. Inaccurate estimates can lead to mis-targeted interventions and resources. I will take my experience of HIV/AIDS epidemic study as an example to illustrate some challenges of quantitative analysis in global health.
主办方：大阳城2138(中国)股份有限公司金融数学系
