Tehran Institute for Advanced Studies (TeIAS)

/ Events by M

Teias Short Course

Information Design

Lecture by Dr. Saman Darougheh

  • Date:
    Dec 22 2018
  • Time:
    10:00 am - 4:00 pm
  • Location:
    Khatam University
  • Registration
    Email [email protected]

Overview:

Information design studies information disclosure policies and their effects on the payoffs of senders and receivers of information. In this short course, we provide an overview of information design, with an eye towards more applied work.We start with Bayesian Persuasion, which presented a framework for studying information design (Kamenica and Gentzkow, 2011). We then study two applications to markets. First, we study how a seller’s ability to price discriminate based on observable  characteristics of consumers affects producer and consumer surplus (Bergemann, Brooks, and Morris, 2015). Second, we discuss whether or not consumers benefit from knowing their own preferences (Roesler and Szentes, 2017).

Biography

Nima Haghpanah is an assistant professor of Economics at Pennsylvania State University.   Prior to that, he was a postdoctoral associate at MIT CSAIL and Sloan School of Management. He obtained his PhD in 2014 from Northwestern University.  His dissertation was on optimal multi-parameter auctions, and his research interests are mechanism design, auction design, and game theory. Nima has received a best dissertation award from Northwestern University, and a graduate fellowship from the Simons Foundation.

Schedule:

8:30 – 10:00
Plan A
10:00 – 11:00
Plab B
12:00 – 14:00
Plan C
8:30 – 10:00
Plan A
10:00 – 11:00
Plab B
12:00 – 14:00
Plan C

Map

Gallery

Speakers:

Hosein Joshaghani

Dr. Ahmad Lashkaripour

Assistant Professor of Economics Indiana University

I am an Assistant Professor of Economics at Indiana University. My Research interests are at the intersection of International trade and Economic development. My work emphasizes the role of composition (product-mix) in trade. Specifically, I study the link between the characteristics of a nation and the structure of its foreign trade. My recent work shows that the welfare-improving effects of trade are remarkably larger in the developing world, when one accounts for the composition of trade flows. In my free time, I play and watch soccer. I’m an avid supporter of Man Utd.

Dr. Ahmad Lashkaripour

Assistant Professor of Economics Indiana University

I am an Assistant Professor of Economics at Indiana University. My Research interests are at the intersection of International trade and Economic development. My work emphasizes the role of composition (product-mix) in trade. Specifically, I study the link between the characteristics of a nation and the structure of its foreign trade. My recent work shows that the welfare-improving effects of trade are remarkably larger in the developing world, when one accounts for the composition of trade flows. In my free time, I play and watch soccer. I’m an avid supporter of Man Utd.

Dr. Ahmad Lashkaripour

Assistant Professor of Economics Indiana University

I am an Assistant Professor of Economics at Indiana University. My Research interests are at the intersection of International trade and Economic development. My work emphasizes the role of composition (product-mix) in trade. Specifically, I study the link between the characteristics of a nation and the structure of its foreign trade. My recent work shows that the welfare-improving effects of trade are remarkably larger in the developing world, when one accounts for the composition of trade flows. In my free time, I play and watch soccer. I’m an avid supporter of Man Utd.

Program:

  • 09:00 – 10:00 Introduction to Statistics – Session 4
  • 10:00 – 10:15 Coffee / Tea Break 
  • 10:15 – 11:15 Introduction to Statistics – Session 5
  • 11:15 – 11:30 Coffee / Tea Break 
  • 11:30 – 12:15 Python Programming – Basics – Session 2
  • 12:15 – 13:30 Lunch Break 
  • 13:30 – 14:15 Python Programming – Basics – Session 3
  • 14:15 – 14:30 Coffee / Tea Break 
  • 14:30 – 15:15 Machine Learning – Session 1
  • 15:15 – 15:30 Coffee / Tea Break
  • 15:30 – 16:30 Machine Learning – Session 2
  • 16:30 – 17:00 Practical Problems in Data Science
 
  • 09:00 – 10:00 Introduction to Statistics – Session 4
  • 10:00 – 10:15 Coffee / Tea Break 
  • 10:15 – 11:15 Introduction to Statistics – Session 5
  • 11:15 – 11:30 Coffee / Tea Break 
  • 11:30 – 12:15 Python Programming – Basics – Session 2
  • 12:15 – 13:30 Lunch Break 
  • 13:30 – 14:15 Python Programming – Basics – Session 3
  • 14:15 – 14:30 Coffee / Tea Break 
  • 14:30 – 15:15 Machine Learning – Session 1
  • 15:15 – 15:30 Coffee / Tea Break
  • 15:30 – 16:30 Machine Learning – Session 2
  • 16:30 – 17:00 Practical Problems in Data Science
  •  
  • 09:30 – 10:00 Opening 
  • 10:00 – 10:30 Introduction to the School
  • 10:30 – 10:45 Coffee / Tea Break 
  • 10:45 – 12:00 Introduction to Statistics – Session 1
  • 12:00 – 13:15 Lunch Break 
  • 13:15 – 14:15 Python Programming – Basics – Session 1
  • 14:15 – 14:30 Coffee / Tea Break
  • 14:30 – 15:30 Introduction to Statistics – Session 2
  • 15:30 – 15:45 Coffee / Tea Break
  • 15:45 – 16:30 Introduction to Statistics – Session 3
  • 16:30 – 16:45 Coffee / Tea Break
  • 16:45 – 17:45 Data Science in Practice Panel
  • 09:00 – 10:00 Introduction to Statistics – Session 4
  • 10:00 – 10:15 Coffee / Tea Break 
  • 10:15 – 11:15 Introduction to Statistics – Session 5
  • 11:15 – 11:30 Coffee / Tea Break 
  • 11:30 – 12:15 Python Programming – Basics – Session 2
  • 12:15 – 13:30 Lunch Break 
  • 13:30 – 14:15 Python Programming – Basics – Session 3
  • 14:15 – 14:30 Coffee / Tea Break 
  • 14:30 – 15:15 Machine Learning – Session 1
  • 15:15 – 15:30 Coffee / Tea Break
  • 15:30 – 16:30 Machine Learning – Session 2
  • 16:30 – 17:00 Practical Problems in Data Science
  • 09:00 – 10:15 Machine Learning – Session 3
  • 10:15 – 10:30 Coffee / Tea Break 
  • 10:30 – 11:45  Machine Learning – Session 4
  • 11:45 – 12:00 Coffee / Tea Break 
  • 12:00 – 12:45  Machine Learning – Session 5
  • 12:45 – 13:45 Lunch Break 
  • 13:45 – 14:30 Python Programming – Data Analysis – Session 4
  • 14:30 – 14:45 Coffee / Tea Break 
  • 14:45 – 15:30 Python Programming – Data Analysis – Session 5
  • 15:30 – 17:00 Programming Lab
  • 09:00 – 10:15 Machine Learning – Session 6
  • 10:15 – 10:30 Coffee / Tea Break 
  • 10:30 – 11:15 Machine Learning – Session 7
  • 11:15 – 11:30 Coffee / Tea Break 
  • 11:30 – 12:15 Python Programming – Data Analysis – Session 6
  • 12:15 – 13:30 Lunch Break 
  • 13:30 – 14:15 Python Programming – Data Analysis – Session 7
  • 14:15 – 14:30 Coffee / Tea Break 
  • 14:30 – 15:15 Python Programming – Data Analysis – Session 8
  • 15:15 – 15:30 Coffee / Tea Break
  • 15:30 – 16:15 Python Programming – Machine Learning – Session 9
  • 16:15 – 16:30 Coffee / Tea Break
  • 16:30 – 17:15 Python Programming – Machine Learning – Session 10
  • 09:00 – 10:15 Introduction to Data Science – Session 1
  • 10:15 – 10:30 Coffee / Tea Break 
  • 10:30 – 11:30 Introduction to Data Science – Session 2
  • 11:30 – 11:45 Coffee / Tea Break 
  • 11:45 – 12:30  Introduction to Data Science – Session 3
  • 12:30 – 13:30 Lunch Break 
  • 13:30 – 14:30 Introduction to Data Science – Session 4
  • 14:30 – 14:45 Coffee / Tea Break 
  • 14:45 – 15:45  Introduction to Data Science – Session 5
  • 15:45 – 16:00 Coffee / Tea Break
  • 16:00 – 16:30 Closing session
  • 09:00 – 10:00 Introduction to Statistics – Session 4
  • 10:00 – 10:15 Coffee / Tea Break 
  • 10:15 – 11:15 Introduction to Statistics – Session 5
  • 11:15 – 11:30 Coffee / Tea Break 
  • 11:30 – 12:15 Python Programming – Basics – Session 2
  • 12:15 – 13:30 Lunch Break 
  • 13:30 – 14:15 Python Programming – Basics – Session 3
  • 14:15 – 14:30 Coffee / Tea Break 
  • 14:30 – 15:15 Machine Learning – Session 1
  • 15:15 – 15:30 Coffee / Tea Break
  • 15:30 – 16:30 Machine Learning – Session 2
  • 16:30 – 17:00 Practical Problems in Data Science
  • 15:15 – 15:30 Coffee / Tea Break
  • 15:30 – 16:30 Machine Learning – Session 2
  • 16:30 – 17:00 Practical Problems in Data Science