Award-Winning Computer Science Tutors
serving Winston-Salem, NC

Florence doesn't just study computer science at Duke — she teaches it, having served as a TA for Intro to Databases and Computer Network Architecture while also interning in software development at IBM. That combination of academic depth and industry experience means she can explain everything from relational algebra to TCP/IP networking with concrete, real-world context. Rated 5.0 by students.

Studying computer science at Duke means Susie is immersed in everything from algorithm analysis to systems design right now, which keeps her explanations current and grounded. She's especially sharp at connecting theoretical ideas like Big-O notation and recursion to the practical code students actually write. Co-founding a tutoring club in high school gave her early practice at making tough material click.

Studying computer science at UNC Chapel Hill means Jack lives in the material — algorithms, data structures, operating systems, and computational theory aren't abstract topics for him but daily coursework. He breaks down concepts like recursion, Big-O analysis, and memory management into intuitive explanations that stick.

Tackling a computer science minor alongside mechanical engineering at Duke, Shaan lives at the intersection of hardware thinking and software logic. He teaches core CS concepts — algorithm complexity, recursion, data structures, and object-oriented design — by connecting abstract ideas to concrete implementations, which is especially useful for students encountering Big-O notation or sorting algorithms for the first time.

Understanding computer science means thinking algorithmically: knowing not just that a sorting algorithm works, but why merge sort outperforms bubble sort at scale and how to analyze that difference with Big-O notation. Shourya codes in Python, C++, and MATLAB, which lets him adapt explanations to whichever language a student's course uses while keeping the focus on the underlying logic of data structures and algorithms.

I graduated from the University of North Carolina at Chapel Hill with a Bachelor of Science in Physics. I work with students in a variety of subjects, including Math, Physics, and Chemistry. I have experience working with students on the Autism spectrum and with ADHD.

I am a graduate student at George Mason University studying Computer Science. I also graduated at Vanderbilt University, with Bachelors Degrees in Computer Science, Mathematics, and Philosophy. When a student does not understand a topic or concept, I believe the best way to teach it is to meet students where they are at, providing individually catered feedback, and exploring the aspects of a student's weaknesses, finding a way to explain the concept in a way that resonates with and makes sense to the student. I am most familiar with tutoring for the SAT, where I have generally increased scores by 120-300 points.

From sorting algorithms and Big-O analysis to data structures like linked lists and binary trees, Rhamy covers the foundational CS concepts that show up in coursework and technical interviews alike. His computer engineering degree at Vanderbilt, paired with experience in multiple languages, lets him explain abstract ideas through concrete code. Rated 5.0 by students.

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.

Eric treats coding problems the same way he treats logical puzzles — by breaking them apart, finding the pattern, and building a solution step by step. As a CS major at Washington University in St. Louis, he's deep in Java and JavaScript right now, which means he can walk students through everything from writing their first function to structuring a full object-oriented program. His approach emphasizes learning to think through problems algorithmically before jumping to syntax.

Julia is a computational science major at Stanford who writes code daily and understands the gap between knowing syntax and thinking like a programmer. She digs into core concepts like recursion, data structures, and algorithm design by walking through problems step by step until the logic becomes intuitive. Students learning Python, Java, or tackling their first real debugging challenge get someone who can explain the *why* behind every line.

Building AI systems and low-level software at Stanford — in both Python and C++ — Kevin knows where the theoretical meets the practical in computer science. His biocomputation specialization means he can explain not just how to implement an algorithm, but why certain computational approaches work better for different problem domains. Rated 5.0 by students.

Recursion, data structures, algorithmic complexity — these topics trip up students who try to memorize patterns without understanding why they work. Kevin holds both a bachelor's and master's in computer science from NYU, and he's the kind of tutor who will explain a concept three different ways until the logic genuinely lands. Rated 4.8 by students.

Ritesh's applied physics program at Cornell involves significant programming, from numerical simulations to data analysis, giving him hands-on fluency with core computer science concepts like algorithm design, data structures, and debugging logic. He unpacks topics such as recursion, sorting algorithms, and object-oriented principles by tying them to concrete problems rather than abstract definitions.

Between his AP Computer Science 5 and his engineering coursework at Vanderbilt, William has written code across contexts — from introductory Java to computational modeling in his chemical engineering classes. He breaks down abstract concepts like recursion, data structures, and algorithm efficiency by walking through concrete examples line by line. Students who can follow the logic but freeze when writing code from a blank screen tend to gain traction quickly with his approach.

As a computer science major at Boston University, Irene is immersed in the subject daily — from data structures and algorithms to object-oriented design. She breaks down abstract programming concepts into concrete steps, walking through how to trace logic, debug code, and think like a developer rather than just memorize syntax.

As an engineering student at Brown, Kashish works with programming languages and computational thinking daily — from writing algorithms to debugging code and understanding data structures like arrays, linked lists, and trees. She breaks down abstract CS concepts by connecting them to concrete problems, making topics like recursion or object-oriented design click for students encountering them for the first time. Her analytical precision and 5.0 rating make her a strong fit for introductory through intermediate computer science.

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.

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.