Award-Winning Computer Science Tutors
serving Boston, MA

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 a computer science major heading into her senior year, Allison is deep in the material students are encountering for the first time — data structures, algorithm analysis, object-oriented design. She explains concepts like recursion and Big-O notation by building up from simple examples in Python before introducing the formal definitions, which makes abstract ideas click faster.

Christine is a third-year CS student at Northeastern who lives this material daily — from data structures and algorithms to object-oriented design and recursion. She walks through problems by connecting the abstract logic to concrete code, so concepts like linked lists or graph traversals click rather than feel like rote memorization. Rated 4.9 by students.

I am passionate about helping students succeed in computer science by making complex concepts clear and engaging. With over seven years of teaching experience in higher education, I have taught a range of courses in programming and information systems. I hold a Master's degree in Computer Science from the University of Trento, Italy, and a Bachelor's degree in Information Systems from Addis Ababa University, Ethiopia, and I am currently pursuing my Ph.D. in Computer Science. My favorite subjects to tutor are C++, Java, and Systems Analysis and Design because they build strong problem-solving and analytical skills. I focus on creating an interactive, supportive learning environment that helps students gain confidence and apply their knowledge. Outside of academia, I am interested in pursuing roles in the tech industry as a system analyst or software engineer.

Studying computer science at MIT, Brice digs into everything from data structures and algorithms to systems-level thinking with students at any stage. He's tutored over 30 students in the past year alone, tackling topics like recursion, object-oriented design, and algorithmic complexity. Rated 4.9 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.

Between Java, Python, and the AP Computer Science A curriculum, William covers the languages and frameworks that most high school and intro-level college students actually encounter. His Northeastern CS program keeps him close to the material — he's working through the same data structures, algorithms, and OOP principles his students are learning, which means he can pinpoint exactly where a concept like recursion or inheritance starts to feel slippery. Rated 5.0 by students.

A working software developer with a BS in Computer Science, Andy covers core CS topics — data structures, algorithms, recursion, Big-O analysis — with the perspective of someone who uses them daily in mobile application design. He explains not just how an algorithm works but why you'd choose it over alternatives in a real codebase.

Allison holds a B.S. in Computer Science from Mount Holyoke College, so she's been through the full gauntlet — from writing first programs to tackling data structures, algorithms, and debugging logic that refuses to cooperate. She teaches coding concepts by building up from how the computer actually processes instructions, which makes abstract ideas like recursion and iteration far more intuitive.

An Electronic Design degree from Hampshire College means Micah lives at the intersection of code and hardware — he's built electronics curricula and understands programming as a tool for making things work in the real world. He tackles core CS concepts like control flow, data structures, and debugging by grounding them in tangible projects rather than abstract exercises.

Studying computer science at Tufts alongside civil engineering gives Adam a dual perspective — he understands both the theoretical foundations like data structures and algorithms and how code gets applied to solve real-world problems. He unpacks concepts like recursion, object-oriented design, and sorting algorithms by building small programs that make abstract ideas concrete. That hands-on approach clicks especially well for students who learn by doing.

Adriano leans into the proof-based, mathematical side of computer science — the discrete math foundations, formal logic, and algorithmic correctness arguments that many introductory courses rush past. As an MIT CS undergrad, he's immersed in that rigor daily and brings it to sessions where students need to understand not just what an algorithm does but how to prove it works.

I'm Cindy! I'm a freshman at Harvard University and graduated from San Mateo High School this past year. I love to teach and have years tutoring students of all ages in a variety of subjects. Feel free to send me a message if you have any questions or would like to schedule a tutoring session!

I'm Connor, a computer science, linguistics, and Japanese major at the University of Massachusetts Amherst. I'm in my third year expecting to graduate in May next year.

A Duke CS graduate now pursuing a Master's in Cybersecurity, Noah covers everything from foundational data structures and algorithms to systems-level concepts like memory management and network protocols. He breaks down abstract topics — recursion, Big-O analysis, object-oriented design — by connecting them to real problems rather than leaving them as textbook definitions. Students get someone who's still actively building in the field, not just teaching from notes.

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.

Michael earned his B.S. in Computer Science from UCLA, where he dug into everything from data structures and algorithms to software design principles. He breaks down abstract concepts like recursion, Big-O analysis, and object-oriented programming into concrete, step-by-step logic that clicks. He also teaches JavaScript, giving him a practical edge when students need to connect theory to actual code.

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.

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.

From data structures and algorithms to systems-level thinking, computer science covers enormous ground. John earned a BS in Computer Science and codes in Java, C++, and SQL, giving him the range to dig into whatever topic is causing trouble — whether that's recursion, Big-O analysis, or database design.

Between his coursework at Rice and his background in algorithms, Daniel tackles computer science from both the practical and theoretical sides — writing clean code and understanding why one sorting algorithm outperforms another for a given dataset. He's especially strong at breaking down recursion, data structures, and algorithmic complexity into steps that build logically on each other.

A Stanford MS in Computer Science means David can teach everything from data structures and algorithms to object-oriented design with the depth that comes from building real systems — not just reading about them. He spent a summer teaching web and app development to high school students in Palestine, so he knows how to make abstract CS concepts click through hands-on projects.

Jeff tackles computer science by connecting abstract concepts like recursion, data structures, and algorithmic complexity to concrete problem-solving steps students can follow. His science background means he's comfortable with the mathematical logic underlying CS, from Boolean algebra to Big-O analysis.

Studying computer science at Cornell, Eric tackles everything from algorithm analysis and Big-O notation to systems-level concepts like memory management and recursion. He breaks down problems the way a CS student actually encounters them — whiteboarding a solution, tracing through edge cases, then translating logic into clean code. His 5.0 rating speaks to how clearly that approach lands.

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.

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.