Finance majors often breeze through the business concepts in business calculus but hit a wall when they actually have to differentiate and integrate cost or revenue functions. Jonathan's finance degree means he speaks the business language fluently, so he spends his time on the calculus mechanics — setting up optimization problems, applying the chain rule to compound-interest models, and interpreting what a derivative actually tells you about profit at a given output level.

I am a firm believer of this and, as such, I do not spoon feed students during sessions but rather guide them to figure out how to answer their own questions and solve their own problems. Thus, I focus not only on what to do, but how and why to do it. One of the most significant drivers of independent learning is curiosity, and this is one of the primary traits I aim to cultivate in students.

I love helping students in topics related to math, to finance (public and private equity) and to engineering. I believe that if I can't explain concept, then I don't understand it. By that same token, if a student can't explain a concept back to me, then they don't understand it even if they say they do. I believe in getting to know all students, as their background is intricately connected with how they learn.

As a PhD economics student, Dana builds cost, revenue, and elasticity models daily — the exact functions business calculus courses ask students to differentiate and integrate. She teaches the chain rule or finding a local maximum not as isolated calc techniques but as steps in answering questions like "at what production level does profit peak," drawing problems straight from her graduate research at Stony Brook.

Having studied both economics and computer science at Caltech, Brian thinks about calculus the way business students need to — as a tool for modeling decisions, not as an exercise in proofs. He teaches derivatives through the lens of marginal analysis and optimization problems pulled from actual econ coursework, so concepts like cost minimization and revenue maximization click on the first pass.

Most business calculus students don't struggle with the mechanics of taking a derivative — they struggle with translating a word problem about profit margins or demand curves into the right setup. Alex's applied mathematics training at Stanford means he can bridge that gap, turning vague business scenarios into clean functions students know how to optimize. Rated 4.8 by students.

Three engineering degrees — including one in applied mathematics — mean Rahi has worked through calculus from every angle, pure and applied. For business calculus students, he zeroes in on translating derivative and integral mechanics into the language of profit maximization, cost analysis, and demand elasticity, bridging the gap between the math they're learning and the business decisions it models.

Where most business calculus students stumble isn't the differentiation itself — it's translating a word problem about profit margins or demand curves into the right function to differentiate. Jhonatan's biology and neuroscience training gave him years of practice applying calculus to real systems, from modeling population growth to analyzing rates of change in physiological data. That applied mindset, rated 5.0 by students, carries directly into breaking down optimization and marginal analysis problems.

An economics degree from Brown gives Bryan a natural advantage when teaching business calculus — he already thinks in terms of cost functions, demand curves, and optimization because those were core to his own coursework. He breaks down derivatives and integrals by anchoring each one to the economic model it serves, so a profit-maximization problem reads like a business question first and a math problem second. Rated 5.0 by students.

Drisana's applied mathematics degree means she treats every derivative and integral as a tool with a specific job — and in business calculus, that job is usually answering questions about cost, revenue, or profit at the margin. She breaks down optimization problems and exponential growth models by starting with what the business scenario is actually asking, then building the calculus around it. Rated 5.0 by students.

Finance majors often breeze through the business concepts in business calculus but hit a wall when they actually have to differentiate and integrate cost or revenue functions. Jonathan's finance degree means he speaks the business language fluently, so he spends his time on the calculus mechanics — setting up optimization problems, applying the chain rule to compound-interest models, and interpreting what a derivative actually tells you about profit at a given output level.

I am a firm believer of this and, as such, I do not spoon feed students during sessions but rather guide them to figure out how to answer their own questions and solve their own problems. Thus, I focus not only on what to do, but how and why to do it. One of the most significant drivers of independent learning is curiosity, and this is one of the primary traits I aim to cultivate in students.

I love helping students in topics related to math, to finance (public and private equity) and to engineering. I believe that if I can't explain concept, then I don't understand it. By that same token, if a student can't explain a concept back to me, then they don't understand it even if they say they do. I believe in getting to know all students, as their background is intricately connected with how they learn.

As a PhD economics student, Dana builds cost, revenue, and elasticity models daily — the exact functions business calculus courses ask students to differentiate and integrate. She teaches the chain rule or finding a local maximum not as isolated calc techniques but as steps in answering questions like "at what production level does profit peak," drawing problems straight from her graduate research at Stony Brook.

Having studied both economics and computer science at Caltech, Brian thinks about calculus the way business students need to — as a tool for modeling decisions, not as an exercise in proofs. He teaches derivatives through the lens of marginal analysis and optimization problems pulled from actual econ coursework, so concepts like cost minimization and revenue maximization click on the first pass.

Most business calculus students don't struggle with the mechanics of taking a derivative — they struggle with translating a word problem about profit margins or demand curves into the right setup. Alex's applied mathematics training at Stanford means he can bridge that gap, turning vague business scenarios into clean functions students know how to optimize. Rated 4.8 by students.

Three engineering degrees — including one in applied mathematics — mean Rahi has worked through calculus from every angle, pure and applied. For business calculus students, he zeroes in on translating derivative and integral mechanics into the language of profit maximization, cost analysis, and demand elasticity, bridging the gap between the math they're learning and the business decisions it models.

Where most business calculus students stumble isn't the differentiation itself — it's translating a word problem about profit margins or demand curves into the right function to differentiate. Jhonatan's biology and neuroscience training gave him years of practice applying calculus to real systems, from modeling population growth to analyzing rates of change in physiological data. That applied mindset, rated 5.0 by students, carries directly into breaking down optimization and marginal analysis problems.

An economics degree from Brown gives Bryan a natural advantage when teaching business calculus — he already thinks in terms of cost functions, demand curves, and optimization because those were core to his own coursework. He breaks down derivatives and integrals by anchoring each one to the economic model it serves, so a profit-maximization problem reads like a business question first and a math problem second. Rated 5.0 by students.

Drisana's applied mathematics degree means she treats every derivative and integral as a tool with a specific job — and in business calculus, that job is usually answering questions about cost, revenue, or profit at the margin. She breaks down optimization problems and exponential growth models by starting with what the business scenario is actually asking, then building the calculus around it. Rated 5.0 by students.