2nd Big Data Economics Summer School

2nd Big Data Economics Summer School


Aim & Focus Areas

Big Data Economics summer school aims to address the theoretical, computational and statistical underpinnings of big data analysis through a series of talks from leading academic experts. The focus will be the econometric models and novel machine learning techniques to manipulate and analyze the big data and their Implications in research focusing on interesting economic questions that arise from considering the rapid changes in data availability and computational technology. With the rise of big data and the very real opportunities that machine learning now brings, there is no better time to find out how novel techniques can be used for economic research.

Target Audience

  • Faculty members and graduate (Masters and Ph.D.) students
  • Banking and financial industry experts and policy makers
  • Researchers (from Econ, Finance, Math, Stat, CS and ML backgrounds)

Link to our 1st Summer School in 2016 (click here)


Dates: 5th- 8th August 2018

VenueThe 2nd Big Data Economics Summer School will be held at Khatam University 

Registration Deadline: 2nd August

Tuition :

General: 1,000,000 Toman

Students: 500,000 Toman

(Payable at the first day of Summer School)

Scholarship for strong resumes is Available.



Sunday - August 5th

Professor Ali Emrouznejad Aston

Topic: “Big Data Performance Measurement”

Sunday- 13:45-15:15, 15:30-17:00.
Monday- 13:45-15:15, 15:30-17:00.

Ali Emrouznejad is a Professor and Chair in Business Analytics at Aston Business School, UK. His areas of research interest include performance measurement and management, efficiency and productivity analysis as well as data mining and big data. He holds an MSc in applied mathematics and received his PhD in operational research and systems from Warwick Business School in 1998. Ali is Editor of Annals of Operations Research, Associate Editor of RAIOR-Operations Research, Associate Editor of Socio-Economic Planning Sciences, Associate Editor of IMA journal of Management Mathematics, and Senior Editor of Data Envelopment Analysis journal. He has published over 120 articles in top ranked journals. Ali is also  author / editor of several books including “Big Data Optimization” (Springer).


Professor  Esfandiar Maasoumi – Emory

Topic: “Model Averaging in Macroeconomic Forecasting”

Sunday- 9:00-10:30, 10:45,-12:15.

Esfandiar Maasoumi is a Distinguished Professor of Economics at Emory University, Atlanta, GA. He received his bachelor’s degree, masters, and PhD from the London School of Economics in 1977. Maasoumi has served as Editor of Econometric Reviews since 1987. Esfandiar is also a Fellow of the Royal Statistical Society, a Fellow of the American Statistical Association, and a Fellow of the Journal of Econometrics. He is a member of the Econometric Society, the American Statistical Association, the American Economic Association, and the American Mathematical Society. He is ranked in the Econometricians Hall of Fame. He has influential contributions in forecasting, specification analysis, information theory, multidimensional welfare/wellbeing, mobility and inequality. He has published more than 100 theoretical and empirical articles and reviews in the leading journals in economics.


Professor Lorenzo Trapani – Nottingham

Topic: “Dealing with large covariance matrices: identification and monitoring for breaks”

Tuesday- ALL DAY

Lorenzo Trapani is a Professor of Econometrics at the School of Economics, University of Nottingham, UK. His main research interests are econometric theory, asymptotic theory for time series and panel data, testing for structural breaks and the change point problem as well as large factor models, nonparametric statistics and random coefficient autoregressive model. Lorenzo holds a PhD from the University of Bergamo, Italy in 2004. He was a Senior Lecturer in Financial Econometrics at Cass Business School, City University London and he has been member of the Centre for Econometric Analysis at Cass since its foundation.


Dr. Ali Habibnia –  Virginia Tech

Topic: “Nonlinear Forecasting in Big Data Environments: Deep Learning Approach”

Wednesday- ALL DAY

Ali Habibnia is joining the Department of Economics at Virginia Tech as an Assistant Professor of Big Data Economics. He holds an MSc in quantitative finance from Cass Business School and received his PhD in statistics from the London School of Economics and Political Science in 2017. His research focuses on the intersection of deep learning and big data econometrics, with a particular interest in the high-dimensional nonlinear time-series analysis and their applications in forecasting and identifying risk in highly connected networks. He also worked as a trader and portfolio strategist for several years and developed different algorithmic trading strategies. Habibnia is the Chair of the Big Data Economics Summer School.


Dr. Kasra Alishahi – Sharif University of Technology

Topic: “Large Scale Inference & Shrinkage Estimators”

Monday- 9:00-10:30, 10:45-12:15.

Kasra Alishahi is an Assistant Professor in Mathematics at Sharif University of Technology, Iran. He received his PhD from the Department of Mathematical Sciences, Sharif University of Technology, Tehran, Iran, in 2008. His research interests are stochastic processes, probabilistic methods and statistics.