Mica's Science, Technology, and Society degree at Stanford meant constant data wrangling — organizing research datasets, running analyses, and presenting findings in structured formats. She brings that academic rigor to Excel sessions, tackling everything from formula logic and data cleanup to building spreadsheets that actually answer a research question. Rated 5.0 by students.

Most people use about ten percent of what Excel can do. David applies spreadsheet tools extensively in his research — pivot tables, VLOOKUP, conditional formatting, and basic macro automation — and teaches students to move from manual data entry toward efficient, formula-driven workflows that save hours of repetitive work.

Most people use about ten percent of what Excel can do. Matthew's quantitative background in math and CS means he digs into the powerful side — pivot tables, VLOOKUP versus INDEX/MATCH, conditional formatting rules, and basic VBA automation — turning spreadsheets from data dumps into actual analytical tools.

Most people only scratch the surface of Excel — Avram goes deeper into VLOOKUP, pivot tables, conditional formatting, and array formulas that turn messy data into something useful. His quantitative background in physics means he's comfortable building spreadsheets that handle real calculations, not just store information.

Elliot learned Excel the way most researchers do — out of necessity, building complex data models, pivot tables, and conditional formulas to analyze neuroscience datasets. That means he teaches the tool the way it's actually used: not as a list of menu options but as a way to organize messy information, automate calculations, and visualize patterns quickly.

Spreadsheets become genuinely powerful once you move past basic formulas into VLOOKUP, pivot tables, conditional formatting, and macro automation. Keenan's computer science background at Penn means he understands the logic underneath Excel — why an INDEX-MATCH works where VLOOKUP fails, or how to structure data so a pivot table actually gives you useful answers.

Engineering coursework and biomedical research gave Sparsh daily practice in Excel — from organizing large datasets and writing nested formulas to building pivot tables and generating publication-ready charts. He walks through each function in the context of a real task so students learn not just the syntax but when and why to use it.

Most people use about 10% of what Excel can do. Gabriel digs into the functions that actually save time — VLOOKUP, INDEX/MATCH, pivot tables, conditional formatting — and shows students how to structure spreadsheets so the data answers questions instead of just sitting in rows.

Spreadsheet fluency is a core requirement in Andrew's Labor and Industrial Relations program at Cornell, where he regularly builds models using formulas, pivot tables, and data visualization tools. He teaches Excel by starting with the task a student actually needs to accomplish — whether that's organizing a dataset, running calculations, or building a chart — and works backward to the functions that get it done.

Most people learn Excel by Googling one formula at a time, which leaves gaps that compound as spreadsheets get more complex. Firas approaches it systematically — pivot tables, VLOOKUP vs. INDEX/MATCH, conditional formatting, and basic data cleaning workflows — so students build a toolkit they can apply to any dataset. His data-intensive research background means he also knows when a problem has outgrown Excel and how to transition to more powerful tools.

Reed's economics degree from Carleton College meant constant spreadsheet work — building econometric models, running regressions on datasets, and formatting results for presentation. He teaches Excel by connecting functions like INDEX-MATCH, data validation, and chart building to the kind of analytical tasks students encounter in econ, finance, and business courses.

Adam's statistics and data analysis coursework in cognitive science meant living inside spreadsheets — building formulas, cleaning datasets, and using pivot tables to make sense of experimental results. He teaches Excel as a practical tool rather than an abstract skill set, covering everything from VLOOKUP and conditional formatting to chart design that actually communicates findings clearly.