This is a list of all the classes I’ve been involved with.

Tutored/Graded/Proctored Classes

System-on-Chip Deisgn	Experimental Engineering	Graph Theory
Commutative Algebra	Digital Design and Computer Architecture	Abstract Algebra
Differential Equations	Linear Algebra	Calculus

Engr 154: System-on-Chip Design

System-on-chip design of a RISC-V based platform. Topics include RISC-V architecture, C and assembly language programming and debugging, platform emulation, Linux-based workflow automation, SystemVerilog, logic synthesis and validation, pipelined microarchitecture, privileged operations, bus interfaces and peripherals, memory systems, branch prediction, computer arithmetic, benchmarking, operating systems, and silicon implementation. Class project involving design and optimization.

Taught by David Harris, SP23. I helped write the textbook for this class.

Engr 80: Experimental Engineering

A laboratory course designed to acquaint the student with the basic techniques of instrumentation and measurement in both the laboratory and in engineering field measurements. Emphasis on experimental problem solving in real systems.

Taught by Staff, SP23.

Math 104: Graph Theory

An introduction to graph theory with applications. Theory and applications of trees, matchings, graph coloring, planarity, graph algorithms, and other topics.

Taught by Mohamed Omar, SP23.

Math 189AA: Commutative Algebra

This course is an introduction to the fundamental concepts and questions in the study of commutative rings, with a special focus on the notion of “prime ideals,” and how they generalize the idea primeness in the integers. Possible topics include Noetherian rings, primary decomposition, basic module theory, exact sequences and key results like the Krull Altitude Theorem and Nakayama’s Lemma.

Taught by Haydee Lindo, FA22.

Engr 85: Digital Design and Computer Architecture

Design and implementation of digital systems. Topics include levels of abstraction, Boolean algebra, combinational logic, sequential logic, finite state machines, hardware description languages, computer arithmetic, C and assembly programming, embedded systems, and microarchitecture. Lab practices include simulation, prototyping, and debugging.

Taught by David Harris, FA22.

Math 171: Abstract Algebra

Groups, rings, fields and additional topics. Topics in group theory include groups, subgroups, quotient groups, Lagrange’s theorem, symmetry groups, and the isomorphism theorems. Topics in Ring theory include Euclidean domains, PIDs, UFDs, fields, polynomial rings, ideal theory, and the isomorphism theorems. In recent years, additional topics have included the Sylow theorems, group actions, modules, representations, and introductory category theory.

Taught by Michael Orrison, SP22; Mohamed Omar, FA21 and SP21.

Math 82: Differential Equations

Modeling physical systems, first-order ordinary differential equations, existence, uniqueness, and long-term behavior of solutions; bifurcations; approximate solutions; second-order ordinary differential equations and their properties, applications; first-order systems of ordinary differential equations. Applications to linear systems of ordinary differential equations, matrix exponential; nonlinear systems of differential equations; equilibrium points and their stability.

Taught by Staff, FA20.

Math 19: Calculus

A comprehensive view of the theory and techniques of differential and integral calculus of a single variable together with a robust introduction to multivariable calculus. Topics include limits, continuity, derivatives, definite integrals, infinite series, Taylor series in one and several variables, partial derivatives, double and triple integrals, linear approximations, the gradient, directional derivatives and the Jacobian, optimization and the second derivative test, higher-order derivatives and Taylor approximations, line integrals, vector fields, curl, divergence, Green’s theorem, and an introduction to flux and surface integrals.

Taught by Staff, FA20.

Math 73: Linear Algebra

Theory and applications of linearity, including vectors, matrices, systems of linear equations, dot and cross products, determinants, linear transformations in Euclidean space, linear independence, bases, eigenvalues, eigenvectors, and diagonalization. General vector spaces and linear transformations; change of basis and similarity.

Taught by Staff, SP20.

Math Classes Taken

Algebraic Topology	Algebraic Number Theory	Algebraic Geometry
Elementary Number Theory	Probability	Harmonic Analysis
Complex Analysis	Real Analysis	Commutative Algebra
Partial Differential Equations	Galois Theory	Discrete Math

Math 527: Algebraic Topology

This course covers some essential elements of algebraic topology. It has, very broadly, two parts: Homology and Cohomology.

Taught by Liam Watson, SP24.

Math 538: Algebraic Number Theory

This will be a standard graduate number theory course. Topics will include:

• Number fields, rings of integers, ideals and unique factorization. Finiteness of the class group.

• Valuations and completions; local fields.

• Ramification theory, the different and discriminant.

• Geometry of numbers: Dirichlet’s Unit Theorem. and discriminant bounds.

Taught by Lior Silberman, SP24.

Math 502: Commutative Algebra

We cover the basics of commutative rings, ideals, modules. We generally follow the textbook. Additional topics include some algebraic geometry and combinatorial algebra.

Taught by Kalle Karu, SP24.

Math 532: Algebraic Geometry

A first introduction to algebraic geometry. The goal is to prepare students to take more advanced courses in the subject. We study the basic objects of algebraic geometry, algebraic varieties and schemes.

Taught by Kai Behrend, FA23.

Math 537: Elementary Number Theory

The students are expected to learn the following, which also includes being able to solve questions combining all of these topics: the Fundamental Theorem of Arithmetic; properties of congruences; Fermat’s Little Theorem and Euler’s Theorem; important multiplicative functions; properties of the primitive root corresponding to a given moduli; the quadratic reciprocity theorem; and basic Diophantine Equations and basic Diophantine Approximation.

Taught by Dragos Ghioca, FA23.

Math 157: Intermediate Probability

Continuous random variables, distribution functions, joint density functions, marginal and conditional distributions, functions of random variables, conditional expectation, covariance and correlation, moment generating functions, law of large numbers, Chebyshev’s theorem and central-limit theorem.

Taught by Jina Kim, FA22.

Math 189J: Harmonic Analysis on Finite Groups

This advanced topics course will focus on the use of permutation representations of finite groups to analyze complex-valued functions defined on finite sets. Possible topics include random walks on graphs, Gelfand pairs, generalized fast Fourier transforms, and related applications to statistics, machine learning, and voting theory.

Taught by Michael Orrison, SP22.

Math 135: Complex Analysis

An introduction to the theory and application of analytic functions of a complex variable. Topics may include: Mobius transformation, multiple-valued functions, Cauchy-Riemann equations, harmonic functions, Cauchy’s Theorem, Liouville’s Theorem, Cauchy’s Integral Formula, Maximum Modulus Principle, Argument Principle, Rouche’s Theorem, series expansions, isolated singularities, calculus of residues, conformal mapping.

Taught by Asuman Aksoy, FA21.

Math 180: Partial Differential Equations

Partial Differential Equations (PDEs) including the heat equation, wave equation, and Laplace’s equation; existence and uniqueness of solutions to PDEs via the maximum principle and energy methods; method of characteristics; Fourier series; Fourier transforms and Green’s functions; Separation of variables; Sturm-Liouville theory and orthogonal expansions; Bessel functions.

Taught by Andrew Bernoff, FA21.

Math 189AA: Commutative Algebra

Taught by Haydee Lindo, SP21.

Math 172: Galois Theory

This course covers selected topics in the theories of groups, rings, fields, and modules with a specific emphasis on Galois Theory. Topics covered will include polynomial rings, field extensions, splitting fields, algebraic closure, separability, Fundamental Theorem of Galois Theory, Galois groups of polynomials and solvability.

Taught by Leonid Fukshansky, SP21.

Math 171: Abstract Algebra

Taught by Jessalyn Bolkema, SP20.

Math 55A: Discrete Math

Topics include combinatorics (clever ways of counting things), number theory, and graph theory with an emphasis on creative problem solving and learning to read and write rigorous proofs. Possible applications include probability, analysis of algorithms, and cryptography.

Taught by Arthur Benjamin, FA19.

Engineering Classes Taken

VLSI Design	Advanced Computer Architecture	System-on-Chip Design
High Power Rocketry	Microprocessor Based Systems	Experimental Engineering
Materials Engineering	Digital Design and Computer Architecture	Systems Engineering
Continuum Mechanics	Chemical and Thermal Processes	Analog Circuits

ELEC 502: Advanced Topics in Very-Large-Scale Integration (VLSI) Design

Deep learning has emerged as an important technique for solving critical problems across a diverse set of applications. However, VLSI architectures for implementing efficient learning systems remains an open question and a very active research area. Topics will include (1) detailed overview of computations, data patterns, and neural network architectures used in deep learning with the goal of understanding the operations we want to accelerate in hardware, (2) Emerging applications of deep learning, (3) Advanced VLSI topics for designing efficient hardware acceleration of deep learning systems with a focus on VLSI design trade-offs, techniques, and optimizations, (4) Techniques and optimizations for mapping deep learning workloads to general-purpose (CPUs, GPUs) and custom hardware, (5) Exploration of the latest research in both academic and commercial deep learning hardware acceleration. By the end of the course, students will have a good overview of this exciting and emerging field that has many open research opportunities.

Taught by Scott Chin and Bradley Quinton, SP24.

CPEN 411: Advanced Computer Architecture

First, we learn about the microarchitecture of a single microprocessor core and then how multiple such cores are combined in modern processors. We learn the mechanisms used to improve performance given a fixed implementation technology (e.g., 14 nm silicon) and techniques used in designing computer systems at both the microarchitecture and architecture levels. The course combines both theoretical and practical components, and students will be evaluated on their proficiency in both aspects.

Taught by Prashant Nair, FA23.

Engr 154: System-on-Chip Design

Taught by David Harris, SP23. I helped write the textbook for this class.

Engr 155: Microprocessor Based Systems: Design and Applications

Introduction to digital design using programmable logic and microprocessors. Combinational and sequential logic. Finite state machines. Hardware description languages. Field programmable gate arrays. Microcontrollers and embedded system design. Students gain experience with complex digital system design, embedded programming, and hardware/software trade-offs through significant laboratory and project work.

Taught by Josh Brake, FA22.

Engr 178: High Power Rocketry

This course uses high power rockets as a vehicle for learning and demonstrating competence in modeling, experimental data collection and data analysis of rigid body and flight dynamics. In particular, students will perform 1-D analytical and numerical characterization of flight data including motor performance, testing and characterization of avionics and telemetry, develop and use models for inertial navigation and sensor fusion, and characterize structural dynamics during flight. The final project will demonstrate all of the above from data the students collect during flights of the rockets the students will construct and instrument, designed to reach Mach 1.6 and an altitude of 13,000 ft.

Taught by Erik Spjut, SP22.

Engr 80: Experimental Engineering

Taught by Staff, SP22.

Engr 101: Advanced Systems Engineering

Analysis and design of continuous-time and discrete-time systems using time domain and frequency domain techniques. The first semester focuses on the connections and distinctions between continuous-time and discrete-time signals and systems and their representation in the time and frequency domains. Topics include impulse response, convolution, continuous and discrete Fourier series and transforms, and frequency response. Current applications, including filtering, modulation and sampling, are presented, and simulation techniques based on both time and frequency domain representations are introduced. In the second semester additional analysis and design tools based on the Laplace- and z-transforms are developed, and the state space formulation of continuous and discrete-time systems is presented. Concepts covered during both semesters are applied in a comprehensive treatment of feedback control systems including performance criteria, stability, observability, controllability, compensation and pole placement.

Taught by Professors Phillip Cha and Qimin Yang, FA21.

Engr 86: Materials Engineering

Introduction to the structure, properties and processing of materials used in engineering applications. Topics include: material structure (bonding, crystalline and non-crystalline structures, imperfections); equilibrium microstructures; diffusion, nucleation, growth, kinetics, non-equilibrium processing; microstructure, properties and processing of: steel, ceramics, polymers and composites; creep and yield; fracture mechanics; and the selection of materials and appropriate performance indices.

Taught by Gordon Krauss, FA21.

Engr 85: Digital Electronics and Computer Engineering

Taught by David Harris, FA21.

Engr 84: Electronic and Magnetic Circuits and Devices

Introduction to the fundamental principles underlying electronic devices and applications of these devices in circuits. Topics include electrical properties of materials; physical electronics (with emphasis on semiconductors and semiconductor devices); passive linear electrical and magnetic circuits; active linear circuits (including elementary transistor amplifiers and the impact of non-ideal characteristics of operational amplifiers on circuit behavior); operating point linearization and load-line analysis; electromagnetic devices such as transformers.

Taught by Ruye Wang, SP21.

Engr 83: Continuum Mechanics

The fundamentals of modeling continuous media, including: stress, strain and constitutive relations; elements of tensor analysis; basic applications of solid and fluid mechanics (including beam theory, torsion, statically indeterminate problems and Bernoulli’s principle); application of conservation laws to control volumes.

Taught by Phillip Cha, SP21.

Engr 82: Chemical and Thermal Processes

The basic elements of thermal and chemical processes, including: state variables, open and closed systems, and mass balance; energy balance, First Law of Thermodynamics for reactive and non-reactive systems; entropy balance, Second Law of Thermodynamics, thermodynamic cycles and efficiency.

Taught by Erik Spjut, FA20.

Engr 4: Introduction to Engineering Design and Manufacturing

Design problems are, typically, open-ended and ill-structured. Students work in small teams applying techniques for solving design problems that are, normally, posed by not-for-profit clients. The project work is enhanced with lectures and reading on design theory and methods, and introduction to manufacturing techniques, project management techniques and engineering ethics. Enrollment limited to first-year students and sophomores, or by permission of the instructor.

Taught by Professors Steven Santana and Leah Mendelson, FA20.

CS Classes Taken

Algorithms

Data Structures and Program Development

Principles of Computer Science

CS 140 / Math 168: Algorithms

Algorithm design, analysis, and correctness. Design techniques including divide-and-conquer and dynamic programming. Analysis techniques including solutions to recurrence relations and amortization. Correctness techniques including invariants and inductive proofs. Applications including sorting and searching, graph theoretic problems such as shortest path and network flow, and topics selected from arithmetic circuits, parallel algorithms, computational geometry, and others. An introduction to computational complexity, NP-completeness, and approximation algorithms.

Taught by Chris Stone, SP23.

CS 70: Data Structures and Program Development

Abstract data types including priority queues and dynamic dictionaries and efficient data structures for these data types, including heaps, self-balancing trees and hash tables. Analysis of data structures including worst-case, average-case and amortized analysis. Storage allocation and reclamation. Secondary storage considerations. Extensive practice building programs for a variety of applications.

Taught by Professors Calden Wloka and Melissa O’Neill, SP23.

CS 60: Principles of Computer Science

Introduction to principles of computer science: Information structures, functional programming, object-oriented programming, grammars, logic, logic programming, correctness, algorithms, complexity analysis, finite-state machines, basic processor architecture and theoretical limitations.

Taught by Staff, FA20.

CS 5 Black: Advanced Introduction to Computer Science

Introduction to elements of computer science. Students learn computational problem-solving techniques and gain experience with the design, implementation, testing and documentation of programs in a high-level language. In addition, students learn to design digital devices, understand how computers operate, and learn to program in a small machine language. Students are also exposed to ideas in computability theory. The course includes discussions of societal and ethical issues related to computer science.

Taught by Geoff Kuenning, FA19.