Triple-majoring in math, computer science, and chemistry meant Lance spent undergrad bouncing between proof-based theory and actual implementation in languages like Java, C, and C# — exactly the dual fluency IB Computer Science demands when students shift between pseudocode reasoning on Paper 1 and building a working IA project. His TA experience across over a dozen courses means he's already diagnosed the spots where students get stuck, particularly around abstract data structures and algorithm tracing on paper versus writing real code.

Between a master's in computer science, professional software development work, and fluency in Java, C++, Python, JavaScript, and PHP, Daniel has built and debugged enough real systems to make IB Computer Science's pseudocode feel intuitive rather than alien. His applied mathematics background also strengthens the algorithmic thinking and Big-O analysis that Paper 1 leans on heavily. Rated 5.0 by students.

Friends at UChicago regularly come to Jack for help debugging Python and working through tricky CS problem sets — that informal teaching experience translates well to IB Computer Science, where students need someone who can explain pseudocode logic and data structures conversationally, not just academically. His CS major and math minor at Chicago mean he's comfortable with both the programming side and the computational thinking and algorithm analysis that dominate Paper 1. Rated 5.0 by students.

A PhD in Mathematics and Computer Science means Irene has lived on both sides of the IB CS syllabus — the formal logic and algorithm analysis that dominate Paper 1, and the computational thinking required to design and justify an IA project. Her discrete math and graph theory expertise is especially relevant for the data structures and algorithm efficiency questions where students often lose marks by memorizing steps without understanding the underlying reasoning. Rated 4.9 by students.

A PhD candidate researching computer science, Dibyendu has deep fluency in algorithms, data structures, and computational thinking — the exact concepts IB Computer Science tests through pseudocode tracing and Paper 1's theoretical questions. He also teaches compilers and operating systems, which means topics like resource management and system fundamentals that many IB tutors skim over are areas he can unpack in genuine detail.

As a CS major at Duke who also teaches across German, essay writing, and music tutoring, Susie has an unusual knack for translating technical ideas into language that actually lands — a skill that matters when IB Computer Science asks students to reason through pseudocode on paper instead of just running code until it works. Her Java coursework and data structures experience give her direct overlap with the syllabus, and she's especially effective at breaking down the IA's documentation requirements, where clear written communication is just as important as the code itself.

I am a recent graduate with a master's in electrical engineering from Case Western Reserve University. I won the Bill and Melinda Gates Millennium Scholarship which covers full tuition up to Ph.D. I was on the Dean's List for three consecutive years. Additionally, I won the OZY Media Genius Award in 2015 to work on high-temperature superconductors. I currently work as a Technology Analyst at Accenture. I am also seriously considering whether I should go for a Ph.D. or not.

The IB Computer Science curriculum covers everything from binary representation to algorithm design to the internal assessment project, and the exam expects students to trace through pseudocode under time pressure. Sasha's engineering training makes her particularly effective at teaching the systems-level thinking IB requires — how abstract data structures translate into real computational processes. Rated 4.9 by students.

Building web applications with PostgreSQL and SQL while studying computer science gives Michael a hands-on perspective on databases and system fundamentals — two areas that show up on the IB CS syllabus but often feel abstract without real-world context. He also codes in Java, C++, JavaScript, and C#, which means he can support IA projects in whatever language a student chooses and connect pseudocode logic back to working implementations.

Rishik codes in Java, C++, Python, SQL, and HTML — a breadth that's especially handy for IB Computer Science students choosing a language for their IA project and needing someone who can actually debug alongside them. His CS degree also means the more abstract Paper 1 material, like algorithm efficiency and object-oriented design principles, comes from genuine understanding rather than memorized definitions.

Triple-majoring in math, computer science, and chemistry meant Lance spent undergrad bouncing between proof-based theory and actual implementation in languages like Java, C, and C# — exactly the dual fluency IB Computer Science demands when students shift between pseudocode reasoning on Paper 1 and building a working IA project. His TA experience across over a dozen courses means he's already diagnosed the spots where students get stuck, particularly around abstract data structures and algorithm tracing on paper versus writing real code.

Between a master's in computer science, professional software development work, and fluency in Java, C++, Python, JavaScript, and PHP, Daniel has built and debugged enough real systems to make IB Computer Science's pseudocode feel intuitive rather than alien. His applied mathematics background also strengthens the algorithmic thinking and Big-O analysis that Paper 1 leans on heavily. Rated 5.0 by students.

Friends at UChicago regularly come to Jack for help debugging Python and working through tricky CS problem sets — that informal teaching experience translates well to IB Computer Science, where students need someone who can explain pseudocode logic and data structures conversationally, not just academically. His CS major and math minor at Chicago mean he's comfortable with both the programming side and the computational thinking and algorithm analysis that dominate Paper 1. Rated 5.0 by students.

A PhD in Mathematics and Computer Science means Irene has lived on both sides of the IB CS syllabus — the formal logic and algorithm analysis that dominate Paper 1, and the computational thinking required to design and justify an IA project. Her discrete math and graph theory expertise is especially relevant for the data structures and algorithm efficiency questions where students often lose marks by memorizing steps without understanding the underlying reasoning. Rated 4.9 by students.

A PhD candidate researching computer science, Dibyendu has deep fluency in algorithms, data structures, and computational thinking — the exact concepts IB Computer Science tests through pseudocode tracing and Paper 1's theoretical questions. He also teaches compilers and operating systems, which means topics like resource management and system fundamentals that many IB tutors skim over are areas he can unpack in genuine detail.

As a CS major at Duke who also teaches across German, essay writing, and music tutoring, Susie has an unusual knack for translating technical ideas into language that actually lands — a skill that matters when IB Computer Science asks students to reason through pseudocode on paper instead of just running code until it works. Her Java coursework and data structures experience give her direct overlap with the syllabus, and she's especially effective at breaking down the IA's documentation requirements, where clear written communication is just as important as the code itself.

I am a recent graduate with a master's in electrical engineering from Case Western Reserve University. I won the Bill and Melinda Gates Millennium Scholarship which covers full tuition up to Ph.D. I was on the Dean's List for three consecutive years. Additionally, I won the OZY Media Genius Award in 2015 to work on high-temperature superconductors. I currently work as a Technology Analyst at Accenture. I am also seriously considering whether I should go for a Ph.D. or not.

The IB Computer Science curriculum covers everything from binary representation to algorithm design to the internal assessment project, and the exam expects students to trace through pseudocode under time pressure. Sasha's engineering training makes her particularly effective at teaching the systems-level thinking IB requires — how abstract data structures translate into real computational processes. Rated 4.9 by students.

Building web applications with PostgreSQL and SQL while studying computer science gives Michael a hands-on perspective on databases and system fundamentals — two areas that show up on the IB CS syllabus but often feel abstract without real-world context. He also codes in Java, C++, JavaScript, and C#, which means he can support IA projects in whatever language a student chooses and connect pseudocode logic back to working implementations.

Rishik codes in Java, C++, Python, SQL, and HTML — a breadth that's especially handy for IB Computer Science students choosing a language for their IA project and needing someone who can actually debug alongside them. His CS degree also means the more abstract Paper 1 material, like algorithm efficiency and object-oriented design principles, comes from genuine understanding rather than memorized definitions.