Award-Winning Computer Science Tutors
serving Evansville, IN

From data structures and algorithms to computational complexity, Victoria covers the core CS concepts that show up in both coursework and technical interviews. Studying computer science and math simultaneously at WashU gave her a knack for explaining the mathematical reasoning behind topics like recursion, sorting efficiency, and graph traversal. She holds a 5.0 rating from students.

Having TA'd courses in C Programming, Digital Systems Design, and iOS development at Purdue, Akio has debugged student code across enough languages and paradigms to spot the conceptual gaps that cause the most frustration — whether it's misunderstanding pointer arithmetic or struggling with event-driven programming patterns. His computer engineering degree means he teaches software concepts with a hardware-aware perspective, connecting ideas like memory allocation and data representation to what's physically happening on the chip. Rated 4.8 by students.

Christopher approaches computer science as structured problem-solving, breaking down concepts like algorithms, data types, and control flow into digestible steps before ever touching a keyboard. His business analytics coursework at Indiana University keeps him actively coding and thinking computationally, which translates into clear, practical explanations for students just getting started.

Having a triple major that includes both Computer Science and Mathematics, Darren connects programming concepts to the formal logic and problem-solving frameworks that make them click. Whether it's data structures, algorithm efficiency, or debugging stubborn code, he walks through each problem step by step until the reasoning — not just the syntax — makes sense.

I am an incoming college sophomoore studying Aerospace Engineering at the Georgia Institute of Technology. I was one of the top scholars at Carmel High School in Indiana and have various experiences teaching and tutoring through leading the Carmel High School Science Olympiad team to Nationals for two years in a row. Many of my friends consistently come to me for help with various subjects because of my willingness to help and teach in a way that makes sense to everyone. My specialities are physics, chemistry, math, and economics but I am comfortable tutoring any STEM subject, the SAT, and the ACT. Some of my accomplishments include a perfect 36 ACT score, 800 on the Physics, Math Level 2, and Chemistry SAT subject tests, and a 5 on all the physics, Calculus BC, Chemistry, Macroeconomics, Computer Science, etc. AP exams. When teaching, I focus on making sure that not only do students understand different concepts, but also that students understand why and practical applications of the different concepts. As a recent high school graduate, I have a deep understanding of how high-schoolers think, what is covered in various courses now, and can connect with my students a lot more. Additionally, as an undergraduate teaching assistant at the College of Computing at Georgia Tech, I taught weekly recitation sections of 30 students and held weekly office hours. Therefore, I have lots of experience teaching and working with students.

I am currently a sophomore at the University of Notre Dame. I am majoring in Applied Mathematics and Statistics.

Elizabeth's computer science degree and professional software development career mean she teaches CS concepts the way they're actually used — not just as textbook definitions. Whether it's understanding recursion, tracing through data structures, or reasoning about algorithmic efficiency, she connects abstract ideas to real code she's written on the job.

Pursuing a CS master's at Penn while TAing discrete math means Keenan lives in both the theoretical and practical sides of computer science every day. He unpacks core topics like algorithm complexity, data structure tradeoffs, and computational logic in a way that connects abstract ideas to real code. Rated 5.0 across all sessions.

John transitioned from law into co-founding a software company, which meant teaching himself to think in algorithms, data structures, and system design under real deadlines. He approaches computer science the same way — breaking problems into smaller, solvable pieces before writing a single line of code. That builder's mindset makes debugging and logic design feel less intimidating.

Biomedical engineering at Rice requires heavy computational coursework, so Theresa has tackled core computer science concepts — from object-oriented programming and data structures to algorithm complexity — in the context of solving real problems. She explains abstract ideas like recursion and sorting algorithms by connecting them to concrete examples rather than letting students drown in theory. Rated 5.0 by students.

Ryan is a computer science major at Cornell, which means he's actively working through the same core curriculum — algorithms, data structures, computational complexity — that college CS students encounter. He explains concepts like recursion, Big-O analysis, and graph traversal by tracing through concrete examples rather than relying on abstract definitions. Rated 4.8 across his sessions.

Earning a certificate in Statistics and Machine Learning at Princeton gave Julie hands-on experience with core computer science concepts — algorithm design, data structures, and computational complexity. She approaches CS the way she approaches philosophy: by asking students to reason through *why* a solution works, not just whether it compiles.

Isabella TA'd multiple computer science courses at MIT, so she's seen exactly where students get stuck — whether it's tracing recursive calls, understanding how data structures like linked lists and trees actually work in memory, or debugging logic errors in their code. She explains the underlying concepts so that writing correct programs becomes intuitive rather than trial-and-error. Rated 5.0 by students.

Studying computer science since before college and now pursuing a master's at UMass Amherst, Milo covers the full stack — from data structures and algorithms to systems-level concepts like memory management and concurrency. He spent three years in his university's tutoring center breaking down topics like recursion, sorting complexity, and graph traversal for students at every level.

From data structures and algorithms to computational complexity, Michelle covers the core CS curriculum with the depth you'd expect from a Duke CS graduate heading into a PhD at Michigan. She's especially strong at explaining abstract concepts like recursion and graph traversal by connecting them to concrete, visual examples that make the logic intuitive.

Holding both a B.S. in Computer Science from the University of Kentucky and a game development master's in progress at SCAD, Evan covers the full stack of CS fundamentals: data structures, algorithm analysis, object-oriented design, and software architecture. He connects abstract concepts like Big-O complexity or recursion to concrete implementations in C, C++, and Java so the theory actually sticks.

Pursuing both computer science and data science at NYU's Courant Institute with a cybersecurity minor, Diego lives in this material daily — from algorithms and data structures to networking and systems-level thinking. He breaks abstract CS concepts into smaller, buildable pieces so students can trace the logic themselves rather than just copying solutions.

Allison's CS degree from Dartmouth means she's worked through the full arc — from writing first programs to tackling data structures, algorithms, and computational theory. She unpacks abstract concepts like recursion and Big-O analysis by walking through concrete code examples, making the logic visible before the notation takes over.