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UC Berkeley PhD & Startup Founder: Math, CS, and Science Tutor
Bill B.

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Hourly Rate: $80
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About Bill

Bio

I believe that the most effective learning happens when elite academic rigor is paired with genuine curiosity and real-world context. I hold a Ph.D. in Neuroscience from UC Berkeley, where my research focused on the biological mechanisms of memory and real-time signal analysis. Prior to my doctorate, I earned a double B.S. in Mathematics and Computer Science from Carnegie Mellon University with a minor in Biomedical Engineering, placing in the top 500 nationally in the Putnam mathematics...

I believe that the most effective learning happens when elite academic rigor is paired with genuine curiosity and real-world context. I hold a Ph.D. in Neuroscience from UC Berkeley, where my research focused on the biological mechanisms of memory and real-time signal analysis. Prior to my doctorate, I earned a double B.S. in Mathematics and Computer Science from Carnegie Mellon University with a minor in Biomedical Engineering, placing in the top 500 nationally in the Putnam mathematics competition.

I have been teaching and mentoring students for over eight years in various capacities. As an undergraduate, I served as an online Computer Science tutor, helping students understand the fundamentals of algorithmic logic. During my doctoral studies at Berkeley, I was a Graduate Student Instructor for two separate courses, where I guided students through complex topics by grounding them in concrete examples. My background in neuroscience also gives me a unique perspective on how we process information; I approach every session with an appreciation for cognitive learning mechanics, ensuring that we build a strong mental framework that makes difficult concepts "stick."

Currently, I am the Founder and Lead Engineer of a hardware startup based in Oakland, where I design embedded systems and write high-performance audio software. This active industry experience is a major asset for my students, as I can bridge the gap between textbook theory and practical application. Whether I am helping a high schooler master AP Calculus or guiding a college student through a difficult Operating Systems project, my focus remains the same: to empower students with the technical fluency and problem-solving skills they need to succeed on their own.

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Education

Carnegie Mellon University
CS and Math double
UC Berkeley
PhD

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Approved Subjects

Algebra 2

Algebra 2

Algebra 2 is the "gateway" to higher mathematics, and I help students cross that threshold with confidence. With a double major in Math and CS from Carnegie Mellon, I have a deep mastery of the fundamental functions and transformations that students encounter in this course. I focus on visual intuition—teaching students to "see" the shape of a graph or the behavior of an equation—so they are fully prepared for Pre-Calculus.
Biology

Biology

I hold a Ph.D. in Neuroscience from UC Berkeley, where I conducted deep research into biological systems and cellular mechanisms. My background allows me to explain biology not just as a list of terms to memorize, but as a logical system of machines working together. I help students connect the dots between the micro-level (DNA, enzymes) and the macro-level (organ systems), making the subject more cohesive and easier to retain.
C++

C++

As the Founder/Engineer of a hardware company, I write high-performance, real-time C++ code for embedded audio systems. I have a deep understanding of manual memory management, pointers, and object-oriented design patterns that are critical for serious software engineering. I help students move beyond syntax errors to understand how the code actually interacts with the computer's hardware.
Calculus

Calculus

Calculus is the language of change, and I have used it daily throughout my degrees in Physics and Math, and now in my engineering work. I placed in the top 500 nationally in the Putnam mathematics competition, which requires a creative and deep understanding of calculus concepts. I help students move beyond memorizing rules to understanding the physical meaning of derivatives and integrals, which is essential for success in AP Calculus AB/BC.
Computer Programming

Computer Programming

I have been coding for over a decade, from my CS degree at Carnegie Mellon to my current role building the software stack for a commercial hardware product. My experience spans the entire stack, including low-level firmware, audio engines, and data analysis tools. I focus on teaching "computational thinking"—helping students understand how to break down a problem and structure a solution before they even write a single line of code.
Computer Science

Computer Science

I hold a B.S. in Computer Science from Carnegie Mellon University, widely recognized for its rigorous approach to algorithmic fundamentals. Currently, I apply these concepts daily as a lead engineer building embedded software and hardware for my startup. My teaching focuses on bridging the gap between theoretical computer science concepts—like complexity theory and memory management—and their practical application in writing clean, efficient code.
Data Analysis

Data Analysis

During my Ph.D. in Neuroscience at UC Berkeley, I specialized in analyzing massive datasets of real-time electrophysiological signals. I have extensive experience building custom analysis pipelines in Python using NumPy, SciPy, and Pandas to extract meaningful statistics from raw data. I help students not only run the code but understand the statistical validity and "story" behind the data they are visualizing.
Data Science

Data Science

My background combines a double major in Math/CS from CMU with the scientific rigor of a Berkeley Ph.D., giving me a unique approach to Data Science. I have applied machine learning techniques and statistical modeling to biological data, requiring a deep understanding of both the math "under the hood" and the practical implementation. I teach students how to design robust experiments and avoid common pitfalls in data interpretation.
Data Structures

Data Structures

Data Structures was the cornerstone of my education at Carnegie Mellon, and I continue to rely on these fundamental concepts to build software for my startup. I provide clear, visual explanations for abstract structures like hash tables, binary trees, and graphs. My goal is to help you intuitively "see" the data structure so you can choose the right tool for any coding interview or exam problem.
Discrete Math

Discrete Math

With a double major in Math and CS, I have lived at the intersection of these two fields, which is exactly where Discrete Math sits. I placed in the top 500 nationally in the Putnam mathematics competition, which requires a mastery of combinatorics and creative proof construction. I help students transition from "calculation" math to "conceptual" math, making proofs and logic puzzles feel approachable and solvable.
Guitar

Guitar

I am a semi-professional funk bassist with over a dozen tracks on Spotify and touring experience. As an audio engineer who designs musical instruments, I approach music with a deep appreciation for the physics of sound and the mathematical structures of music theory. I can help students improve their technique while simultaneously teaching them the "why" behind the notes and chords they play.
Linear Algebra

Linear Algebra

Linear Algebra is the engine behind computer graphics, quantum mechanics, and data science—all fields I have worked in. As a Math/CS double major from Carnegie Mellon, I have a rigorous theoretical understanding of vector spaces and eigenvalues. I teach this subject by connecting abstract matrix operations to their real-world applications in engineering and coding, making the "dry" math feel relevant and powerful.
Logic

Logic

Formal logic is the language of both rigorous mathematics and computer hardware, both of which are central to my background. I have years of experience constructing formal proofs and analyzing logical propositions, skills I honed during my time at Carnegie Mellon. I teach students how to deconstruct complex arguments into simple, valid steps, a skill that is essential for success in higher-level mathematics and philosophy.
Music Production

Music Production

I am currently designing and bringing a new electronic musical instrument to market, which requires expert knowledge of digital signal processing (DSP) and synthesis. I combine this technical engineering knowledge with practical experience producing and mixing tracks for release on streaming platforms. I help students understand the technical side of their DAW (Digital Audio Workstation) so they can focus on creativity without getting stuck on technical hurdles.
Music Theory

Music Theory

I combine the practical ear of a touring bassist with the theoretical rigor of an audio engineer who designs musical instruments. I understand music theory from the physics of sound waves up to complex jazz harmony and counterpoint. I help students understand the mathematical structure behind Western music, turning "rules" into tools they can use for analysis or composition.
Neuroscience

Neuroscience

My doctoral research at UC Berkeley focused on the biological mechanisms of memory and the analysis of neural circuit dynamics. I served as a Graduate Student Instructor for two separate neuroscience courses, where I helped students navigate complex topics ranging from ion channel physics to cognitive systems. I excel at breaking down dense biological processes into intuitive, logical systems that are easier to memorize and understand.
Python

Python

I have used Python for everything from analyzing neural brain signals during my PhD to writing manufacturing scripts for my hardware startup. I teach Python as a practical tool, focusing on clean syntax, using libraries like NumPy and Pandas, and writing readable code. Whether you are a beginner automating a spreadsheet or a student analyzing scientific data, I can help you write code that is efficient and "Pythonic."
SAT Math

SAT Math

Having placed in the top 500 nationally in the Putnam math competition, I understand that standardized math tests are often more about logic and pattern recognition than raw calculation. I teach students how to identify the "shortcuts" and underlying concepts in SAT problems so they can solve them quickly and accurately. My goal is to reduce test anxiety by equipping students with a toolkit of reliable strategies for every question type.
Statistics

Statistics

My Ph.D. research at UC Berkeley relied heavily on advanced statistics to interpret complex biological data and signal noise. I have practical experience with probability distributions, hypothesis testing, and statistical significance, having applied them to real-world scientific problems. I help students understand the "why" behind the formulas, ensuring they can interpret data correctly rather than just plugging numbers into a calculator.
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Hourly Rate: $80
Contact Bill