Physics training builds a specific habit that transfers directly to economics: modeling complex systems with graphs, equations, and simplifying assumptions. Avram's three physics degrees mean he's deeply practiced at translating real-world behavior into formal models — exactly the skill students need when working through supply-and-demand curves, elasticity calculations, or equilibrium analysis.

Caltech's economics program is heavily quantitative — Brian's coursework there meant building economic models with real calculus and statistical tools, not just sketching supply-and-demand curves. His computer science double major adds a computational edge that's particularly useful for students tackling game theory, optimization problems, or any econ course where the math suddenly gets serious. His 1580 SAT reflects the kind of analytical precision he brings to breaking down dense material.

Carter earned his economics degree at Brown and then taught game theory to advanced middle school students at a Johns Hopkins CTY program in Hong Kong — so he knows how to make concepts like Nash equilibria, marginal analysis, and market structures click for learners at very different levels. He connects economic models to real decisions rather than leaving them as abstract graphs. His approach digs into the intuition behind supply-and-demand shifts, elasticity, and welfare analysis so the math and the logic reinforce each other.

As an economics major at Northwestern, Sarah digs into the same core principles — scarcity, opportunity cost, market equilibrium, elasticity — that introductory students encounter for the first time. She translates abstract models into concrete examples, making supply-and-demand curves and production possibilities frontiers feel intuitive rather than mechanical.

Matt's finance degree means he learned economics not as an isolated academic subject but as the engine behind investment decisions, corporate strategy, and market behavior — so when he teaches concepts like elasticity or market structures, he can show students where the theory actually lands. His SAT score of 1530 also signals the kind of sharp analytical reading that economics coursework demands, especially when students need to interpret dense graphs or parse tricky problem setups.

Three economics degrees deep, Simon lives in supply-and-demand curves, GDP models, and game theory the way most people live in their native language. He unpacks concepts like elasticity, monetary policy, and market equilibrium by tying them to real headlines — tariff debates, Federal Reserve decisions, housing markets — so the math and the intuition reinforce each other.

Supply and demand diagrams are just the entry point — JF digs into the reasoning behind elasticity, comparative advantage, and market equilibrium so that students can tackle unfamiliar problems without relying on memorized setups. His dual math and computer science training at Stanford gives him a quantitative edge when explaining concepts like marginal analysis and cost curves.

As an economics major at Duke, Eric tackles everything from supply-and-demand fundamentals to more advanced topics like game theory, market structures, and macroeconomic policy. He connects abstract models to real-world examples that make concepts like elasticity or comparative advantage intuitive rather than formulaic. Rated 5.0 by students.

Monetary policy, banking systems, and market behavior aren't abstractions to Cole — they were the focus of his cum laude master's thesis at the University of Amsterdam. He teaches economics by grounding theory in current events, so students see how supply-and-demand diagrams or GDP calculations connect to headlines they've actually read. Rated 5.0 by students.

Studying both History and Economics at Harvard, Finley tackles economics the way it actually works — as a discipline shaped by real-world policy decisions and historical context. He breaks down concepts like supply-and-demand elasticity, market structures, and game theory by grounding them in concrete examples rather than abstract graphs alone. Rated 5.0 by students.

Physics training builds a specific habit that transfers directly to economics: modeling complex systems with graphs, equations, and simplifying assumptions. Avram's three physics degrees mean he's deeply practiced at translating real-world behavior into formal models — exactly the skill students need when working through supply-and-demand curves, elasticity calculations, or equilibrium analysis.

Caltech's economics program is heavily quantitative — Brian's coursework there meant building economic models with real calculus and statistical tools, not just sketching supply-and-demand curves. His computer science double major adds a computational edge that's particularly useful for students tackling game theory, optimization problems, or any econ course where the math suddenly gets serious. His 1580 SAT reflects the kind of analytical precision he brings to breaking down dense material.

Carter earned his economics degree at Brown and then taught game theory to advanced middle school students at a Johns Hopkins CTY program in Hong Kong — so he knows how to make concepts like Nash equilibria, marginal analysis, and market structures click for learners at very different levels. He connects economic models to real decisions rather than leaving them as abstract graphs. His approach digs into the intuition behind supply-and-demand shifts, elasticity, and welfare analysis so the math and the logic reinforce each other.

As an economics major at Northwestern, Sarah digs into the same core principles — scarcity, opportunity cost, market equilibrium, elasticity — that introductory students encounter for the first time. She translates abstract models into concrete examples, making supply-and-demand curves and production possibilities frontiers feel intuitive rather than mechanical.

Matt's finance degree means he learned economics not as an isolated academic subject but as the engine behind investment decisions, corporate strategy, and market behavior — so when he teaches concepts like elasticity or market structures, he can show students where the theory actually lands. His SAT score of 1530 also signals the kind of sharp analytical reading that economics coursework demands, especially when students need to interpret dense graphs or parse tricky problem setups.

Three economics degrees deep, Simon lives in supply-and-demand curves, GDP models, and game theory the way most people live in their native language. He unpacks concepts like elasticity, monetary policy, and market equilibrium by tying them to real headlines — tariff debates, Federal Reserve decisions, housing markets — so the math and the intuition reinforce each other.

Supply and demand diagrams are just the entry point — JF digs into the reasoning behind elasticity, comparative advantage, and market equilibrium so that students can tackle unfamiliar problems without relying on memorized setups. His dual math and computer science training at Stanford gives him a quantitative edge when explaining concepts like marginal analysis and cost curves.

As an economics major at Duke, Eric tackles everything from supply-and-demand fundamentals to more advanced topics like game theory, market structures, and macroeconomic policy. He connects abstract models to real-world examples that make concepts like elasticity or comparative advantage intuitive rather than formulaic. Rated 5.0 by students.

Monetary policy, banking systems, and market behavior aren't abstractions to Cole — they were the focus of his cum laude master's thesis at the University of Amsterdam. He teaches economics by grounding theory in current events, so students see how supply-and-demand diagrams or GDP calculations connect to headlines they've actually read. Rated 5.0 by students.

Studying both History and Economics at Harvard, Finley tackles economics the way it actually works — as a discipline shaped by real-world policy decisions and historical context. He breaks down concepts like supply-and-demand elasticity, market structures, and game theory by grounding them in concrete examples rather than abstract graphs alone. Rated 5.0 by students.