CV

You can download my CV here.

Basics

Name Amir Bagheri
Label Research Fellow
Email bagheri@stanford.edu
Url https://ambadal.github.io/
Summary Research Fellow at Stanford Graduate School of Business, in the field of Economics

Work

  • 2024.09 - 2026.06
    Research Fellow
    Stanford Graduate School of Business
    Standard track research fellow in the field of Economics. Currently working with Professor Ali Yurukoglu and Professor Michael Ostrovsky. Previously worked with Professor Shoshana Vasserman and Professor Samuel Goldberg
  • 2023.08 - 2024.08
    Research Assistant
    Tehran Institute for Advanced Studies (TeIAS)
    Supervisor: Prof. Masoud Seddighin. Contributed to the 'Metric Distortion under Public-Spirited Voting' paper by designing algorithms to derive some of the theorems and their proofs, along with participating in writing and editing of the paper.
  • 2023.02 - 2023.05
    Research Assistant
    National University of Singapore (NUS)
    Supervisor: Prof. Poorya Kabir. Studied the effect of Medicaid expansion on households' participation in stock market and holding risky assets by investigating several survey data and implementing econometric models to explain this effect.
  • 2022.06 - 2022.09
    Algorithmic Trading Intern
    Danesh Co.
    Supervisor: Prof. MohammadAmin Fazli. Implemented algorithmic trading strategies using machine learning models to analyze market trends and make predictions.

Education

  • 2024.09 - 2025.06

    Stanford, CA

    Predoctoral Research Fellow (Non-matriculated)
    Stanford Graduate School of Business, Stanford, CA
    Economics
    • (MS&E 233): Game Theory, Data Science & AI (Graduate), (CS 234): Reinforcement Learning (Graduate), (EE364A): Convex Optimization I (Graduate), (MGTECON 600): Microeconomics I (PhD), (ECON 270-272): Intermediate Econometrics I, II, III (PhD)
  • 2019.09 - 2024.06

    Tehran, Iran

    Bachelor of Science
    Sharif University of Technology, Tehran, Iran
    Computer Engineering and minors in Economics
    • Calculus I-II, Linear Algebra, Differential Equations, Probability and Statistics, Numerical Computation, Advanced Programming, Data Structures and Algorithms, Design of Algorithms, Game Theory, Advanced Information Retrieval, Machine Learning (Graduate), Social and Economic Networks (Graduate), Microeconomics, Macroeconomics, Econometrics, Industrial Organization, Public Economics, Neuroeconomics (Graduate), Finance coursework: Financial Economics, Financial Machine Learning (Graduate), Financial Engineering (Graduate)

Interests

Economics
Industrial Organization
Market Design
Applied Microeconomics

Awards

Publications

  • 2024
    Metric Distortion Under Public-Spirited Voting
    23rd International Conference on Autonomous Agents and Multiagent Systems (AAMAS'24)
    We investigate the impact of public-spirited voting on the distortion in the metric framework. We employ the public-spirited model proposed by Flanigan et al. (EC’23) to model the public-spirited behavior of the agents and evaluate the distortion of different voting rules, including Plurality, Borda, Copeland, Veto, 𝑘-approval, and PluralityVeto.

Projects

Skills

Programming Languages
Python
Julia
R
C/C++
Java
Libraries
TensorFlow
PyTorch
Keras
Scikit-learn
Pandas
Technologies
Git
LaTeX
Slurm Scheduler
SQL Databases

Languages

Farsi
Native speaker
English
Fluent
Arabic
Elementary
French
Elementary

Certificates

LSE Summer School - Spark: Professional Skills - GOLD Award
London School of Economics and Political Science (LSE)
Behavioral Finance
Duke University
Financial Markets
Yale University
Game Theory
Stanford University
The Global Financial Crisis
Yale University
Narrative Economics
Yale University
Introduction to Psychology
Yale University
Introduction to Marketing
University of Pennsylvania