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Columbia CS, Dean's List | 40 Years Coding | 1,000+ Sessions
Carlos R.

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About Carlos

Bio

My strongest areas are C++, Python, algorithms, debugging, and software performance. I’ve spent more than 40 years writing software, but the skill that matters most in tutoring is finding where someone’s understanding went off track. We look at what the program is actually doing, then rebuild the missing idea. I want you to understand the code, not just get it to pass.

If you’re a working engineer or changing careers, I can help with modern C++ (C++20/23), Python, algorithms, systems...

My strongest areas are C++, Python, algorithms, debugging, and software performance. I’ve spent more than 40 years writing software, but the skill that matters most in tutoring is finding where someone’s understanding went off track. We look at what the program is actually doing, then rebuild the missing idea. I want you to understand the code, not just get it to pass.

If you’re a working engineer or changing careers, I can help with modern C++ (C++20/23), Python, algorithms, systems programming, and performance. I’ve also used AI heavily in my engineering work for more than two years. I teach practical AI-assisted coding: how to direct tools such as ChatGPT and Claude, test what they produce, and catch subtle bugs. AI is useful only if you can judge its answers.

For college students, I tutor C/C++, Python, Java, data structures and algorithms, operating systems, and memory management. Bring a difficult concept, an assignment, or code that refuses to behave. I’ll help you reason through it without doing the work for you.

I also work with middle- and high-school students on AP Computer Science A, AP Computer Science Principles, programming fundamentals, and capstone projects. Over the past two years, I’ve completed more than 1,000 one-on-one mentoring sessions with students worldwide through a large international college-preparation organization.

I earned my BS in Computer Science from Columbia University, an Ivy League school, where I made the Dean’s List. I wrote commercial assembly-language software in high school, was introduced to C++ at Bell Labs in 1987, and later built startups, UAV systems, scientific software, and a platform with more than 30,000 users. I’ve also written two technical books.

Lessons are informal and hands-on. I ask questions and run small experiments to make abstract ideas visible. Curiosity is always encouraged; sloppy thinking less so. Send me a note about your goals. We can begin with a free 15-minute Wyzant video consultation.

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Education

Columbia University, School of Engineering
Computer Science

Additional Languages

Spanish

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Approved Subjects

C++

C++

I have programmed in C++ since my time at Bell Labs in 1987, serving as a senior and lead C++ engineer at multiple companies building performance-critical systems. My work spans everything from legacy codebases to modern C++20, including high-performance scientific computing, real-time embedded drone controllers, and a C++ library I designed and released as a solo founder. For the past two years, I have tutored middle and high school students one-on-one, so I know how to make C++ approachable for beginners while teaching the habits that produce fast, clean, professional-quality code. Whether you are stuck on pointers and memory management or writing your very first program, I will meet you where you are and help you build real understanding.
Computer Gaming

Computer Gaming

I wrote and sold my first commercial arcade game in assembly language while still in high school, and I have been a lifelong gamer and software developer ever since. I teach game development with Godot, a free, professional game engine used to build real, published games. In my lessons, students don’t just follow tutorials: they design and build their own playable game while learning the programming, logic, and problem-solving skills behind it. Students walk away with a finished game they can show friends and family, as well as real coding skills that transfer to any language.
Computer Science

Computer Science

I have been programming professionally since 1981 and earned a B.S. in Computer Science from Columbia University’s School of Engineering and Applied Science. My career spans over 45 years of hands-on development in more than a dozen languages — from 6502 assembly language games and C++ at Bell Labs to modern work in Python, Scala, and TypeScript — giving me deep command of core CS fundamentals like data structures, algorithms, and systems architecture. I have led teams and designed production systems in scientific computing, machine learning, big data, and SaaS, including a novel adaptive neural network algorithm I implemented in real time. As the author of two technical books and 150 educational videos, with years of experience leading training and development teams, I enjoy helping students turn CS theory into working, well-engineered code.
Data Analysis

Data Analysis

I hold a BS in Computer Science from Columbia University and have more than 40 years of experience building software and analyzing complex technical data. I developed a data-driven aircraft-design platform used by more than 30,000 registered users, including neural-network models trained with approximately 12,000 hours of CPU time. My professional work includes building reporting and visualization systems with R, Knitr, ggplot2, Vega, D3, Python, and MongoDB, as well as designing a C++ system that analyzed 100 million telephone calls to identify billing overcharges. After leading more than 1,000 one-on-one mentoring sessions with middle and high school students, I teach data analysis through practical projects involving data organization, visualization, interpretation, and machine-learning fundamentals.
Data Science

Data Science

I hold a BS in Computer Science from Columbia University and have more than 40 years of experience building software and applying computational methods to real-world problems. My data science and machine learning experience includes developing a real-time neural network system for estimating customer lifetime value, training neural networks for an online aircraft-design platform using approximately 12,000 hours of CPU time, and working as a Machine Learning Engineer on high-performance systems for processing machine-learning datasets. I have worked with Python, Scala, C++, R, and data-visualization tools including ggplot2, Vega, and D3. After leading more than 1,000 one-on-one mentoring sessions with middle and high school students, I teach data science through hands-on projects that emphasize data analysis, visualization, machine-learning fundamentals, and the thoughtful use of AI tools.
Data Structures

Data Structures

I have spent over 45 years building software where choosing the right data structure makes the difference between success and failure — from a C++ system that audited 100 million telephone call records in under 15 hours to the C database layer I wrote for an in-memory transactional key-value store, adding custom index support. My performance-critical work in high-performance computing with CUDA, OpenMP, MPI, and SIMD has given me practical insight into how data structures interact with memory hierarchies, cache behavior, and parallelism — topics textbooks rarely cover in depth. I have designed and debugged sophisticated structures across more than a dozen languages, including a real-time adaptive neural network that processes each observation in roughly one millisecond in a single pass. As the author of two technical books and 150 educational videos, I know how to break down hash tables, trees, graphs, and heaps into clear, intuitive lessons for students.
Information Technology

Information Technology

I hold a BS in Computer Science from Columbia University and have more than 40 years of professional experience in information technology, including software engineering, systems architecture, technical management, consulting, and product development. I have designed and built web, desktop, embedded, high-performance, and SaaS systems using C++, Python, Java, Scala, JavaScript/TypeScript, Linux, databases, and frameworks such as React. My experience includes leading engineering teams, developing distributed and n-tier applications, building highly available production systems, troubleshooting performance and reliability issues, and integrating hardware with software. After leading more than 1,000 one-on-one mentoring sessions with middle and high school students, I teach IT through practical, project-based guidance tailored to each learner’s goals.
Linux

Linux

I have used Linux as my primary home operating system since 2000, building over 25 years of hands-on experience across embedded, desktop, and production server environments. As a professional C++ engineer, I have developed and optimized performance-critical Linux software for scientific computing, machine learning, big data, and SaaS platforms, frequently using tools such as Linux perf and Intel VTune to isolate and fix bottlenecks. My experience also spans Linux build systems (CMake, Ninja), Python scripting and automation, kernel-level signal handling, and multi-server deployments with transparent failover. With a B.S. in Computer Science from Columbia University and four decades of professional programming, I bring both deep technical knowledge and a passion for teaching and mentoring.
Machine Learning/ AI

Machine Learning/ AI

I bring hands-on production machine learning experience that spans the full practical pipeline: I trained the neural networks powering RCadvisor’s model airplane design calculator (about 12,000 CPU-hours of traditional backpropagation) and built a novel real-time adaptive neural network at BrainyGuy that processes each observation in roughly one millisecond in a single streaming pass, without GPU acceleration. As a Machine Learning Engineer at Xpress.ai, I wrote C++ and Scala back-ends for machine learning datasets running on embedded vector engines, replacing Apache Spark for high-performance processing, and my HPC background (CUDA, Xeon Phi, OpenMP, MPI, AVX-512) gives me a deep grasp of how models run efficiently at scale. That experience lets me teach the why behind machine learning — how neural networks learn, gradient descent, backpropagation, data preparation, and model evaluation — not just the how. In more than 1,000 one-on-one sessions, I’ve mentored middle and high school students, from those with zero coding experience to those building and deploying their own Python machine learning projects, using AI assistants like ChatGPT and Claude to learn the modern way.
React

React

I built and shipped production React applications as the sole engineer of Giopler, a SaaS debugging and profiling platform whose front end combines React with TypeScript, Tailwind CSS, and Vega/D3 for real-time, data-heavy visualizations running across multiple production servers. That hands-on work covers the full React toolkit I teach daily — components, props, hooks (useState, useEffect, useContext), routing, state management, and performance optimization — as well as modern tooling like Vite and npm. It builds on nearly two decades of front-end development, from hand-optimized browser JavaScript to ActionScript and TypeScript, which lets me explain not just how React works but why patterns like immutability and unidirectional data flow matter. As a mentor, I’ve led more than 1,000 one-on-one sessions with middle and high school students, helping many go from zero coding experience to deploying React apps, and I teach a modern approach that pairs solid React fundamentals with AI coding assistants, so students learn to review, debug, and improve generated code.
Robotics

Robotics

I bring hands-on robotics experience from designing unmanned aerial vehicles: I selected the hardware, designed the circuit board, and wrote the embedded C++ control system for a drone; I also designed the Cavehawk UAV under contract to the U.S. military, guiding it through prototyping and flight testing to final acceptance. My 45+ years of programming include embedded systems work ranging from assembly language on a DSP microcontroller at Bell Labs to modern C++ and vector processing, giving me deep insight into the real-time software, sensor integration, and control logic that robotics depends on. I recently built a Godot game to use as a teaching aid, so I know how to make robotics and programming concepts visual, interactive, and engaging for students. With a B.S. in Computer Science from Columbia University and two published technical books on aircraft design, I can guide students from C++ fundamentals through embedded programming and control systems.
UNIX

UNIX

I have developed software on Unix and Linux systems for over 25 years, from high-performance scientific computing and parallel clusters to production web servers and embedded drone controllers. I have also run Linux as my daily home desktop since 2000, so the command line, shell scripting, and the Unix philosophy are second nature to me. I can help you with shell scripting (bash), command-line tools, system programming in C/C++, build systems like CMake, and understanding how Unix systems really work under the hood. Whether you are a student tackling your first systems course or a professional leveling up, I will meet you where you are with clear, patient, practical guidance.

Examples of Expertise

Carlos has provided examples of their subject expertise by answering 2 questions submitted by students on Wyzant’s Ask an Expert.

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Hourly Rate: $59
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