I have 7 years’ experience of using large data sets to predict market supply, demand and price dynamics, and to evaluate the effects of organizational decisions and interventions. I have a flair in discovering connections and patterns from data and coming up with innovative insights and solutions.

Experience

  • Assistant Professor

    at Aarhus University

    September 2015 - September 2018

    Region Midtjylland

    • Develop mathematical models to analyze the determination and dynamics of labour market price, demand, and supply • Apply advanced econometrics, statistics, and machine learning methods to predict labour market price and resource distribution, and to estimate effects of business decisions • Program with Python, STATA, SAS and to prepare and analyze large longitudinal data sets consisting of 30000+ individuals over 72 months • Present research results at international conferences, e.g. at Princeton University and TsingHua University, etc. • Lecture on Microeconomics, Macroeconomics, and Seminars • Supervise bachelor thesis and student projects Expected outcomes: Identify and frame the problem; improve performance of machine learning models; present findings at conferences; propose and develop new projects; develop new market and collaborations, etc.

  • Ph.D. Fellow

    at Aarhus University

    September 2011 - August 2015

    Region Midtjylland

    • Develop advanced econometric and machine learning models to predict business performance matrices and to measure the impacts of marketing and HRM practices etc. • Program and run algorithms on large data efficiently • Keep updating with state-of-art techniques in advanced econometrics, machine learning and programming, etc. • Export, merge, clean, impute, and visualize data with STATA and SAS • Communicate research results to both academics and practitioners, at e.g., Federal Reserve Bank (US), ZEW (Germany), Druid, etc. • Teach Microeconomics, Microeconometrics, Personnel Economics Deliverables: Select performance measure; prepare data; select and engineer features; select and train machine learning models; fine-tune models; etc.

Education

  • University Teacher Training Program

    at Aarhus University

    2016 - 2017 (1 year) Region Midtjylland

  • Using Python for Research

    at Edx

    2016 - 2016 (1 year)

  • Machine Learning

    at Coursera

    2015 - 2015 (1 year)

  • Ph.D. in Economics

    at Aarhus University

    2011 - 2015 (4 years) Region Midtjylland

  • MSc. International Economic Consulting

    at Aarhus University

    2009 - 2011 (2 years) Region Midtjylland

Languages

  • English Negotiation

  • Danish Conversation

  • Chinese Native

Hives