Award-Winning Linear Algebra Tutors
serving Detroit, MI

I'm a recent graduate from Reed College where I majored in Political science with additional concentrations in environmental science, sociology, philosophy, and 3D art.

I am currently a graduate student in Chemical Engineering at the University of Delaware. I am working on using magnetic and flow fields to create advanced materials by directing the self-assembly process of nanoparticles . I have tutored students in Chemistry, Physics and Math all throughout undergraduate and graduate work. I truly enjoy breaking material down into its core components that allows the students to understand complicated information.

During my Bachelor's studies at the University of Michigan-Dearborn, I was a mathematics and statistics tutor for a year, which I greatly enjoyed. I am currently a fourth-year Ph.D. student studying mathematics at the University of Florida. During my Ph.D. at the University of Florida, I was a teaching assistant for Calculus I, Calculus II, and Precalculus, and I was an instructor for a section of Calculus I. These experiences helped me develop my tutoring skills. Many students see math as a set of formulas that they can apply to the problems on their exams and homework. However, I feel that this way of thinking not only stifles true understanding, but also makes students' lives harder. My teaching philosophy is that if a strong conceptual understanding is built, then students will be well-equipped to answer any question that they can be asked. When I tutor, I make sure that students develop this foundation first and foremost.

Teaching middle and high school math for several years means Jacob has watched students build from basic systems of equations all the way up to the abstraction that linear algebra demands — he knows exactly which foundational gaps cause trouble when determinants, vector spaces, and matrix operations enter the picture. His math degree and competition math background give him the formal training to tackle both the computational and theoretical sides of the course. Rated 5.0 by students.

A PhD in Statistics built on a biomedical engineering foundation means Sam has leaned heavily on matrix algebra — from multivariate regression to principal component analysis — where understanding rank, column space, and decompositions isn't optional. He breaks down the theoretical side by showing students how each abstraction maps onto a statistical or engineering problem they can visualize. Rated 4.9 by students.

I am a senior with a Neuroscience major at Swarthmore College. My favorite subjects include Biology and Psychology. I am interested in teaching students how to develop a better grasp of their academic material, improve their learning skills, and succeed in whatever course they take. Outside of the classroom, I enjoy playing violin, reading, and traveling. I also have extensive community service experience and have traveled to China, Kenya, and the Dominican Republic to engage in volunteer work.

Hello, my name is Yosef and I would be happy to serve as a math tutor. I place strong emphasis on a good balance between knowledge of mathematical content and proficiency in problem-solving, reasoning, and conveying mathematical ideas in writing. There are times when a student needs to be informed of a solution, times when he or she also needs to hear the explanation of why the solution works, and times when he or she should be guided to finding the solution on his or her own. It is important for the tutor to recognize which approach is appropriate. Frequently, when students struggle, it is because they do not understand the notation or terminology in use. In such cases, it is important to reassure the student, reminding him or her that he or she is only struggling with understanding a single word, not the entire mathematical concept. As a rule, people perform better and are better motivated when they have self-confidence, not when the task ahead seems frighteningly daunting. It is also important to recognize that different students learn best through different means. As an example, some students are visual learners and can understand the material best through pictures and gestures. Other students learn best through hearing the procedures vocalized, while still others learn best through writing out the steps of the solution procedure. I know to adapt my teaching style to the individual student. with these considerations in mind, I promise to provide the best assistance that I can, taking your individual needs into consideration.

With both a bachelor's and a master's in math — the latter focused on statistics — Duncan has worked through linear algebra at multiple levels, from the foundational course to its heavy use in multivariate statistical theory where matrix decompositions and quadratic forms are essential tools. He breaks down concepts like eigenvalues, determinants, and vector space proofs with the clarity of someone who's had to rely on them repeatedly in advanced coursework. Rated 5.0 by students.

I obtained my Ph.D. in Applied Mathematics at the University of Connecticut (UConn) and I now work as a Lecturer for the University of Minnesota-Twin Cities, School of Mathematics. I also obtained both my Bachelor's and Master's of Arts degree from Rhode Island College (RIC) and have worked as a Math Tutor and Teacher's Assistant throughout my time at RIC. Intellectually, I believe knowledge is fluid and requires practice to perfect. I enjoy showing my peers/students different ways of examining problems in order to achieve a well-rounded understanding of the material through derivation, never memorization. My main mission is to showcase my passion for Math and hopefully encourage students to see the beauty and wonder of this phenomenal subject.

I am interested in Physics and Mathematics and working out practical problems from plumbing to electronics. I will someday go back for my Ph.D. in Physics but until then I am looking to grow as an engineer or computer programmer.

Pryce studied both economics and math at the University of Pennsylvania, which means he hit linear algebra from two sides — the theoretical proof-based course and the applied matrix methods that underpin econometrics and optimization models. That double exposure makes him especially effective at unpacking concepts like vector spaces and linear transformations for students who can do the row reduction but can't yet articulate why it works. Rated 5.0 by students.

A math degree from Colby plus plans for a PhD means Alexander isn't just passing through linear algebra — he's building a career on the kind of abstract reasoning the course demands. He's particularly good at unpacking the shift from matrix computation to the proof-heavy second half, where students suddenly need to show why a transformation is onto or why a set spans a subspace. Rated 5.0 by students.

A master's in statistics built on a math undergraduate degree means Nicholas has lived inside matrix algebra — covariance matrices, projections, and least-squares estimation all run on linear algebra's core machinery. He teaches determinants, eigendecompositions, and rank not as isolated procedures but as the mechanics driving real statistical models. Rated 5.0 by students.