applied math phd harvard

Engineering and Applied Sciences

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You will work toward a degree in one of six subjects— Applied Mathematics ;  Applied Physics ;  Computational Science & Engineering ;  Computer Science ;  Data Science —and Engineering Sciences, which includes Bioengineering , Electrical Engineering , Environmental Science and Engineering , and Materials Science & Mechanical Engineering . SEAS also offers a master's in design engineering jointly with the Harvard Graduate School of Design* and an MS/MBA: Engineering Sciences program ** jointly with Harvard Business School. PhD, SM, and ME students study primarily with SEAS faculty and are enrolled in and receive their degree from the Harvard Kenneth C. Griffin Graduate School of Arts and Sciences.

You may also pursue collaborative options through the Medical Engineering and Medical Physics program, which is part of the Harvard-MIT Division of Health Sciences and Technology , and supplement your studies by cross-registering in other Harvard graduate schools or at MIT.

Graduates of the Harvard John A. Paulson School of Engineering and Applied Sciences have gone on to found their own startups and work at some of the world's largest companies such as Intel, Tesla, Microsoft, Merck, IBM, McKinsey & Company, Amazon, JP Morgan, NASA, Google, and Apple. Others have gone on to academic careers with faculty appointments at MIT, Princeton, Columbia, Yale, Stanford, Imperial College-London, and Harvard.

Additional information on the graduate program is available from the  Harvard John A. Paulson School of Engineering and Applied Sciences  (SEAS) and requirements for the degree are detailed in  Policies .

*Prospective students who are interested in the master in design engineering degree program apply through the Harvard Graduate School of Design.

**Prospective students who are interested in the MS/MBA: Engineering Sciences degree program apply through Harvard Business School.​

***Prospective students who are interested in the Quantum Science and Engineering degree apply to Harvard Griffin GSAS through the Quantum Science and Engineering Program. 

Admissions Requirements

Please review the admissions requirements and other information before applying. You can find degree program-specific admissions requirements below and access additional guidance on applying from the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS)

Academic Background

Applicants typically have bachelor’s degrees in the natural sciences, mathematics, computer science, or engineering. In the application for admission, select “Engineering and Applied Sciences” as your degree program choice and your degree and area of interest from the “Area of Study“ drop-down. PhD applicants must complete the Supplemental SEAS Application Form as part of the online application process.

Standardized Tests

GRE General: Not Accepted

AB/SM Program

Harvard College students may apply to the AB/SM program , which enables them to earn a master’s degree in applied mathematics, applied physics, computational science and engineering, computer science, or engineering sciences while simultaneously completing their AB degree. Students interested in applying for the AB/SM should contact the Office of Undergraduate Education at Harvard College about eligibility.

Special Instructions for Medical Engineering and Medical Physics

If you are also applying to the Medical Engineering and Medical Physics program, please review their admissions instructions . By December 15, you must send a PDF of your completed Harvard Griffin GSAS application to [email protected] .

APPLICATION DEADLINE

Questions about the program.

Welcome to the Math PhD program at Harvard University and the Harvard Kenneth C. Griffin Graduate School of Arts and Sciences.

Learn more about Harvard’s Math community and our statement on diversity and inclusion.

The Harvard Griffin GSAS Office of Equity, Diversity, Inclusion & Belonging offers student affinity groups for graduate students and many other resources.

The Harvard University Office for Gender Equity has dedicated GSAS Title IX resource coordinators who work with and support graduate students.

open. The application deadline is December 15, 2021. -->

The application deadline for fall 2024 admission has passed. Applications for fall 2025 admission will open in September 2024.

For information on admissions and financial support, please visit the Harvard Harvard Kenneth C. Griffin Graduate School of Arts and Sciences.

Harvard Griffin GSAS is committed to ensuring that our application fee does not create a financial obstacle. Applicants can determine eligibility for a fee waiver by completing a series of questions in the Application Fee section of the application. Once these questions have been answered, the application system will provide an immediate response regarding fee waiver eligibility.

Course Listing

For a snapshot of courses being offered by Harvard School of Engineering over the next four years, visit our multi-year course planning  tool.

Computing with Python for Scientists and Engineers

APMTH 10 2024 Fall

Efthimios Kaxiras, Logan McCarty, Georgios Neofotistos Tuesday, Thursday 9:45am to 11:00am

This course is a systematic introduction to computing (with python and jupyter notebooks) for science and engineering applications. Applications are drawn from a broad range of disciplines, including physical, financial, and biological-epidemiological problems. The course consists of two parts: 1. Basics: essential elements of computing, including types of variables, lists, arrays, iteration and control flow (for, while loops, if statement), definition of functions, recursion, file handling and simple plots, plotting and visualization tools in higher dimensions. 2. Applications: development of computational skills for problem solving, including numerical and machine learning methods, and their use in deterministic and stochastic approaches; examples include numerical differentiation and integration, fitting of curves and error analysis, solution of simple differential equations, random numbers and stochastic sampling, and advanced methods like neural networks and simulated annealing for optimization in complex systems. Course work consists of attending lectures and labs, weekly homework assignments, a mid-term project and a final project; while work is developed collaboratively, coding assignments are submitted individually.

Solving and Optimizing

APMTH 22A 2024 Fall

Margo Levine Monday, Wednesday, Friday 9:00am to 10:15am

This course covers a combination of linear algebra and multivariate calculus with an eye towards solving systems of equations and optimization problems. Students will learn how to prove some key results, and will also implement these ideas with code.Linear algebra: matrices, vector spaces, bases and dimension, inner products, least squares problems, eigenvalues, eigenvectors, singular values, singular vectors.Multivariate calculus: partial differentiation, gradient and Hessian, critical points, Lagrange Multipliers.

Introduction to Applied Mathematics

APMTH 50 2024 Spring

Cengiz Pehlevan Monday, Wednesday, Friday 9:00am to 10:15am

This course provides an introduction to the problems and issues of applied mathematics, focusing on areas where mathematical ideas have had a major impact on diverse fields of human inquiry. The course is organized around two-week topics drawn from a variety of fields, and involves reading classic mathematical papers in each topic. The course also provides an introduction to mathematical modeling and programming.

APMTH 50 2025 Spring

Supervised Reading and Research

APMTH 91R 2024 Fall

Margo Levine

Supervised reading or research on topics not covered by regular courses. It cannot be taken as a fifth course. For AM concentrators, work may be supervised by faculty in other departments. For non-concentrators, work must be supervised by an AM faculty member. To be eligible to enroll in the course, students must receive the approval of the course instructors, including approved registration forms, prior to the start of the semester.

APMTH 91R 2024 Spring

Margo Levine, Sarah Iams

Supervised reading or research on topics not covered by regular courses.  For AM concentrators, work may be supervised by faculty in other departments.  For non-concentrators, work must be supervised by an AM faculty member.  Students must receive the approval of an (Associate) Director of Undergraduate Studies and obtain their signature before submitting AM91r forms.

APMTH 91R 2025 Spring

Thesis Research

APMTH 99R 2024 Fall

Provides an opportunity for students to engage in preparatory research and the writing of a senior thesis. Graded on a SAT/UNS basis as recommended by the thesis supervisor. The thesis is evaluated by the supervisor and by one additional reader.

APMTH 99R 2024 Spring

APMTH 99R 2025 Spring

Statistical Inference for Scientists and Engineers

APMTH 101 2024 Spring

Robert D. Howe Tuesday, Thursday 11:15am to 12:30pm

Introductory statistical methods for students in the applied sciences and engineering. Random variables and probability distributions; the concept of random sampling, including random samples, statistics, and sampling distributions; the Central Limit Theorem; parameter estimation; confidence intervals; hypothesis testing; simple linear regression; and multiple linear regression. Introduction to more advanced techniques as time permits.

APMTH 101 2025 Spring

Monday, Wednesday 3:45pm to 5:00pm

Complex and Fourier Analysis with Applications to Art, Science and Engineering

APMTH 104 2024 Fall

L Mahadevan Monday, Wednesday 10:30am to 11:45am

Complex analysis: complex numbers, functions, mappings, Laurent series, differentiation, integration, contour integration and residue theory, conformal mappings. Applications to visualization, art (especially M.C. Escher). Anamorphic images. Fourier Analysis: orthogonality, Fourier Series, Fourier transforms. Signal processing: sampling theorems (Nyquist, Shannon), fast Fourier transforms. Applications to image, audio analysis: filtering and deblurring.

Ordinary and Partial Differential Equations

APMTH 105 2024 Spring

Ordinary differential equations: power series solutions; special functions; eigenfunction expansions. Elementary partial differential equations: separation of variables and series solutions; diffusion, wave and Laplace equations. Brief introduction to nonlinear dynamical systems and to numerical methods.

APMTH 105 2025 Spring

Algebra for Models and Data

APMTH 106 2025 Spring

Anna Seigal Monday, Wednesday 3:00pm to 4:15pm

Introduction to abstract algebra and its applications. Rings, polynomials, and ideals. Factorization of matrices and polynomials. Applications to data analysis, statistical models, and optimization.

Graph Theory and Combinatorics

APMTH 107 2024 Spring

Adam Hesterberg Monday, Wednesday 11:15am to 12:30pm

Topics in combinatorial mathematics that find frequent application in computer science, engineering, and general applied mathematics. Course focuses on graph theory on one hand, and enumeration on the other. Specific topics include graph matching and graph coloring, generating functions and recurrence relations, combinatorial algorithms, and discrete probability. Emphasis on problem solving and proofs.

APMTH 107 2025 Spring

Leslie Valiant Tuesday, Thursday 9:45am to 11:00am

Nonlinear Dynamical Systems

APMTH 108 2024 Spring

Sarah Iams Monday, Wednesday, Friday 1:30pm to 2:45pm

An introduction to nonlinear dynamical phenomena, focused on identifying the long term behavior of systems described by ordinary differential equations. The emphasis is on stability and parameter dependence (bifurcations).  Other topics include: chaos; routes to chaos and universality; maps; strange attractors; fractals. Techniques for analyzing nonlinear systems are introduced with applications to physical, chemical, and biological systems such as forced oscillators, chaotic reactions, and population dynamics.

APMTH 108 2025 Spring

Introduction to PDEs and their Applications

APMTH 109 2024 Spring

Nick Trefethen Tuesday, Thursday 12:00pm to 1:15pm

This course serves as an introduction to partial differential equations (PDE) and their applications across the sciences. The course will familiarize students with the process of starting with a model, deriving the appropriate PDE, and solving it. Examples include wave equations, diffusion equations, the Laplace equation, and several nonlinear equations such as the Burgers and KdV equations. To build intuition for the analytical solutions, simple numerical simulations will be utilized.

APMTH 109 2025 Spring

Mathematical Modeling

APMTH 115 2024 Fall

Michael P. Brenner Tuesday, Thursday 10:30am to 11:45am

Abstracting the essential components and mechanisms from a natural system to produce a mathematical model, which can be analyzed with a variety of formal mathematical methods, is perhaps the most important, but least understood, task in applied mathematics. This course approaches a number of problems without the prejudice of trying to apply a particular method of solution. Topics drawn from biology, economics, engineering, physical and social sciences.

APMTH 115 2024 Spring

APMTH 115 2025 Spring

Zhiming Kuang Tuesday, Thursday 10:30am to 11:45am

Applied Linear Algebra and Big Data

APMTH 120 2024 Spring

Eli Tziperman Tuesday, Thursday 1:30pm to 2:45pm

Topics in linear algebra that frequently arise in applications, especially in the analysis of large data sets: linear equations, eigenvalue problems, linear differential equations, principal component analysis, singular value decomposition; data mining and machine learning methods: clustering (unsupervised learning) and classification (supervised) using neural networks and random forests. Examples from physical sciences, biology, climate, commerce, the internet, image processing, and more will be given. The approach is application-motivated, focusing on an intuitive understanding of the algorithms behind these methods obtained by analyzing small data sets. Programming assignments can be done using Python or Matlab.

APMTH 120 2025 Spring

Introduction to Optimization: Models and Methods

APMTH 121 2024 Fall

Melanie Weber Monday, Wednesday, Friday 12:00pm to 1:15pm

This course provides an introduction to basic mathematical ideas and computational methods for optimization. Topics include linear programming, integer programming, branch-and-bound, branch-and-cut, as well as first-order gradient-based methods with an emphasis on modeling and data science applications.

Physical Mathematics I

APMTH 201 2025 Spring

Michael P. Brenner Monday, Wednesday, Friday 10:30am to 11:45am

Introduction to methods for developing accurate approximate solutions for problems in the sciences that cannot be solved exactly, and integration with numerical methods and solutions. Topics include: dimensional analysis, algebraic equations, complex analysis, perturbation theory, matched asymptotic expansions, approximate solution of integrals.

Advanced Scientific Computing: Numerical Methods

APMTH 205 2024 Fall

Nick Trefethen Monday, Wednesday 3:00pm to 4:15pm

Mathematical theory and implementation aspects of well-established numerical algorithms applied in various scientific and engineering disciplines. The course will cover data fitting, numerical linear algebra, numerical differentiation and integration, optimization, and numerical solvers for differential equations. There will be a significant programming component. Students will be expected to implement a range of numerical methods as part of individual and group-based projects. The material is sufficiently diverse to match each student's background and programming skills.

Advanced Scientific Computing: Stochastic Methods for Data Analysis, Inference and Optimization

APMTH 207 2024 Fall

Petros Koumoutsakos Tuesday, Thursday 12:00pm to 1:15pm

The class aims to highlight the process of scientific discovery under uncertainty in the age of data. The class content stresses a unifying approach to data driven modeling and inference through stochastic  simulations, optimization and Bayesian uncertainty quantification. The class projects require transferring an idea to software in multi- and many-core computer architectures.

Geometric Methods for Machine Learning

APMTH 220 2024 Spring

Melanie Weber Monday, Wednesday 3:00pm to 4:15pm

Recently, there has been a surge of interest in exploiting geometric structure in data and models in machine learning. This course will give an overview of this emerging research area and its mathematical foundation, with a focus on recent literature and open problems. We will cover a range of topics at the intersection of geometry and machine learning including basic differential geometry, graph representation learning, manifold learning, graph neural networks, machine learning on manifolds, and geometric deep learning. Lectures will be complemented by student-led discussions of relevant papers.

APMTH 220 2025 Spring

Theory of Neural Computation

APMTH 226 2024 Fall

Cengiz Pehlevan Monday, Wednesday 9:00am to 10:15am

This course is an introduction to the theory of computation with artificial and biological neural networks. We will cover selected topics from theoretical neuroscience and deep learning theory with an emphasis on topics at the research frontier. These topics include expressivity and generalization in deep learning models; infinite-width limit of neural networks and kernel machines; deep learning dynamics; biologically-plausible learning and models of synaptic plasticity; reinforcement learning in the brain; neural population codes; normative theories of sensory representations; attractor network models of memory and spatial maps; sequential processing with recurrent neural networks and transformers; generative modeling.

Active Matter

APMTH 230 2025 Spring

L Mahadevan Friday 3:00pm to 5:45pm

Active matter describes out of equilibrium systems that consume energy to do work and become functional. Understanding their behavior and function has implications for biology and complex systems across scales, from cells to ecosystems, e.g., morphogenesis, collective behavior of flocks and herds, neurodynamics of locomotion, etc. The tools and concepts needed include non-equilibrium statistical mechanics, kinetic theory, soft matter, and hydrodynamics; methods for the analysis of the models include scaling, coarse-graining (homogenization, renormalization) and computational algorithms (for stochastic and deterministic DE). This course will provide an introduction to the questions, techniques and successes of this exploding field that cuts across the physical and biological sciences.

Decision Theory

APMTH 231 2024 Spring

Demba Ba Tuesday, Thursday 11:15am to 12:30pm

ES 201/AM 231 is a course in statistical inference and estimation from a signal processing perspective. The course will emphasize the entire pipeline from writing a model, estimating its parameters and performing inference utilizing real data. The first part of the course will focus on linear and nonlinear probabilistic generative/regression models (e.g. linear, logistic, Poisson regression), and algorithms for optimization (ML/MAP estimation) and Bayesian inference in these models. We will play particular attention to sparsity-induced regression models, because of their relation to artificial neural networks, the topic of the second part of the course. The second part of the course will introduce students to the nascent and exciting research area of model-based deep learning. At present, we lack a principled way to design artificial neural networks, the workhorses of modern AI systems. Moreover, modern AI systems lack the ability to explain how they reach their decisions. In other words, we cannot yet call AI explainable or interpretable which, as a society, poses important questions as to the responsible use of such technology. Model-based deep learning provides a framework to develop and constrain neural-network architectures in a principled fashion. We will see, for instance, how neural-networks with ReLU nonlinearites arise from sparse probabilistic generative models introduced in the first part of the course. This will form the basis for a rigorous recipe we will teach you to build interpretable deep neural networks, from the ground up. We will invite an exciting line up of speakers. Time permitting, we will provide a model-based pespective of the building blocks of modern language and image generative models.

Learning, Estimation, and Control of Dynamical Systems

APMTH 232 2024 Spring

Na Li Monday, Wednesday 9:45am to 11:00am

This graduate level course studies dynamic systems in time domain with inputs and outputs. Students will learn how to design estimator and controller for a system to ensure desirable properties (e.g., stability, performance, robustness) of the dynamical system. In particular, the course will focus on systems that can be modeled by linear ordinary differential equations (ODEs) and that satisfy time-invariance conditions. The course will introduces the fundamental mathematics of linear spaces, linear operator theory, and then proceeds with the analysis of the response of linear time-variant systems. Advanced topics such as robust control, model predictive control, linear quadratic games and distributed control will be presented based on allowable time and interest from the class. The material learned in this course will form a valuable foundation for further work in systems, control, estimation, identification, detection, signal processing, and communications.

Mathematics of High-Dimensional Information Processing and Learning

APMTH 254 2024 Fall

Yue Lu Tuesday, Thursday 12:45pm to 2:00pm

This course introduces students to fundamental results and recently developed techniques in high-dimensional probability theory and statistical physics that have been successfully applied to the analysis of information processing and machine learning problems. Discussions will be focused on studying such problems in the high-dimensional limit, on analyzing the emergence of phase transitions, and on understanding the scaling limits of efficient algorithms. This course seeks to start from basics, assuming just a solid understanding of undergraduate probability theory. Students will take an active role by exploring and applying what they learn from the course to their own research problems.

Special Topics in Applied Mathematics

APMTH 299R 2024 Fall

Madhu Sudan

Supervision of experimental or theoretical research on acceptable problems in applied mathematics and supervision of reading on topics not covered by regular courses of instruction.

APMTH 299R 2024 Spring

APMTH 299R 2025 Spring

In Applied Mathematics

• First-Year Exploration
• Areas of Application
• AM & Economics
• How to Declare
• Who are my Advisors?
• Secondary Field
• Senior Thesis
• Research for Course Credit (AM 91R & AM 99R)
• AB/SM Information
• Peer Concentration Advisors (PCA) Program
• Student Organizations
• How to Apply
• PhD Timeline
• PhD Model Program (Course Guidelines)
• Oral Qualifying Examination
• Committee Meetings
• Committee on Higher Degrees
• Research Interest Comparison
• Collaborations
• Cross-Harvard Engagement
• Clubs & Organizations
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• Alumni Stories

• Utility Menu

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• Administration
• Applied Math/Economics

The Applied Math/Economics (AM/Ec) "marriage" is a rational one. Mathematical modeling is used extensively in economics, and the foundation of economic theory is formed on a mathematical basis.

The Applied Math/Economics requirements include five Economics classes:

• ECON 1010A or ECON 1011A (preferably ECON 1011A)
• One of ECON 1126, STAT 186, or STAT 111
• Two economics classes from this list (if you would like more information on which courses historically counted, please email [email protected] )

Ordinarily, Applied Math / Economics does not give concentration credit for the less mathematical classes ECON 1010B or ECON 1123.

• COVID-19 Related Program Changes
• Declaring Economics
• Concentrator Guide
• Courses, Tutorials and Seminars
• Honors Program
• Senior Thesis
• Secondary Field
• Summer School
• Study Abroad
• Opportunities
• After Graduation
• Alumni Resources

MA & PhD in Architecture

Ucla architecture and urban design offers two academic graduate degrees: the master of arts in architecture (ma) and doctor of philosophy in architecture (phd)..

The programs produce students whose scholarship aims to provoke and operate within architecture’s public, professional, and scholarly constituencies. Both programs are supported by the Standing Committee, made up of five faculty members: Michael Osman (interim program director), Cristóbal Amunátegui , Dana Cuff , Samaa Elimam , and Ayala Levin . A number of visiting faculty teach courses to expand the range of offerings.

Applications for the MA/PhD program (Fall 2024 matriculation) are completed via the UCLA Application for Graduate Admission , and are due January 6, 2024. Candidates will be notified of decisions in March 2024; admitted candidates who wish to accept the offer of matriculation must submit their Statement of Intent to Register (SIR) by April 15, 2024.

All MA and PhD students are required to enroll in a two-year colloquium focused on methods for writing, teaching, and researching in the field of architecture. The six courses that constitute the colloquium train students in the apparatus of academic scholarship. Over the two-year sequence, students produce original research projects and develop skills in long-format writing.

Research Opportunities

The intellectual life of the students in the MA and PhD programs are reinforced by the increasing number of opportunities afforded to students through specialized faculty-led research projects. These include cityLAB-UCLA and the Urban Humanities Institute .

MA in Architecture

This program prepares students to work in a variety of intellectual and programmatic milieus including historical research, cultural studies, and interdisciplinary studies with particular emphasis on connections with geography, design, art history, history of science and literary studies, as well as studio and design based research.

Beyond the core colloquium, MA students take a series of approved courses both at UCLA AUD and across campus. The MA program is a two-year degree, culminating in a thesis. The thesis is developed from a paper written by the student in their coursework and developed in consultation with the primary advisor and the standing committee. In addition to courses and individual research, students often participate in collective, project-based activities, including publications, symposia and exhibitions.

The program is distinguished by its engagement with contemporary design and historical techniques as well by the unusual balance it offers: fostering great independence and freedom in the students’ courses of study while providing fundamental training in architectural scholarship.

Recent MA Theses

• Jacqueline Meyer, “Crafting Utopia: Paolo Soleri and the Building of Arcosanti.”
• Joseph Maguid, “The Architecture of the Videogame: Architecture as the Link Between Representational and Participatory Immersion.”
• Meltem Al, “The Agency of Words and Images in the Transformation of Istanbul: The Case of Ayazma.”
• Courtney Coffman, “Addressing Architecture and Fashion: On Simulacrum, Time and Poché.”
• Joseph Ebert, “Prolegomena to a Poiesis of Architectural Phenomenology.”
• Jamie Aron, “Women Images: From the Bauhaus Weaving Workshop to the Knoll Textile Division.”
• Gustave Heully, “Moldy Assumptions.”
• Brigid McManama, “Interventions on Pacoima Wash: Repurposing Linear Infrastructure into Park Spaces.”

MA Typical Study Program

Phd in architecture.

This program prepares students to enter the academic professions, either in architectural history, architectural design, or other allied fields. PhD students are trained to teach courses in the history and theory of architecture while also engaging in studio pedagogy and curatorial work. In addition to the colloquium, PhD students take a series of approved courses both at UCLA Architecture and Urban Design and across campus. They select these courses in relation to their own research interests and in consultation with their primary advisor. The priorities for selection are breadth of knowledge and interdisciplinary experience that retains a focused area of expertise. To this end, the students identify Major and Minor Fields of study. The Minor Field is generally fulfilled by satisfactorily completing three courses given by another department and the Major Field by five courses offered by UCLA Architecture and Urban Design.

Once coursework is completed, PhD students move to the Comprehensive Exam, Qualifying Exam, and the writing of a dissertation, and final defense, if deemed appropriate by the doctoral committee. In the transition from coursework to exams, PhD students work on one paper beyond its original submission as coursework. The paper begins in the context of a departmental seminar, but often continues either in the context of an independent study, summer mentorship, or a second seminar with faculty consent. Upon the research paper’s acceptance, students begin preparing for their comprehensive exam. Before their third year, students must also satisfactorily complete three quarters of language study or its equivalent according to University standards. The particular language will be determined in consultation with the Standing Committee. The Comprehensive Exam is administered by at least two members of the Standing Committee and at most one faculty member from another Department at UCLA, also a member of the Academic Senate.

The Comprehensive Exam tests two fields: the first covers a breadth of historical knowledge—300 years at minimum—and the second focuses on in-depth knowledge of a specialization that is historically and thematically circumscribed. Students submit an abstract on each of these fields, provide a substantial bibliography, and prepare additional documentation requested by their primary advisor. These materials are submitted to the committee no less than two weeks before the exam, which occurs as early as the end of the second year. Students are encouraged to complete the Comprehensive Exam no later than the end of their third year of study.

The Comprehensive Exam itself consists of two parts: an oral component that takes place first, and then a written component. The oral component is comprised of questions posed by the committee based on the student’s submitted materials. The goal of the exam is for students to demonstrate their comprehensive knowledge of their chosen field. The written component of the exam (which may or may not be waived by the committee) consists of a written response to a choice of questions posed by the committee. The goal of this portion of the exam is for students to demonstrate their research skills, their ability to develop and substantiate an argument, and to show promise of original contribution to the field. Students have two weeks to write the exam. After the committee has read the exam, the advisor notifies the student of the committee’s decision. Upon the student’s successful completion of the Comprehensive Exam, they continue to the Qualifying Exam.

Students are expected to take the Qualifying Exam before the beginning of the fourth year. The exam focuses on a dissertation prospectus that a student develops with their primary advisor and in consultation with their PhD committee. Each student’s PhD committee consists of at least two members of the Standing Committee and one outside member from another department at the University (and a member of the Faculty Senate). Committees can also include faculty from another institution. All committees are comprised of at least three members of UCLA Academic Senate. The prospectus includes an argument with broad implications, demonstrates that the dissertation will make a contribution of knowledge and ideas to the field, demonstrates mastery of existing literature and discourses, and includes a plan and schedule for completion.

The PhD dissertation is written after the student passes the qualifying exam, at which point the student has entered PhD candidacy. The dissertation is defended around the sixth year of study. Students graduating from the program have taken posts in a wide range of universities, both in the United States and internationally.

Recent PhD Dissertations

• Marko Icev, "Building Solidarity: Architecture After Disaster and The Skopje 1963 Post-Earthquake Reconstruction." ( Read )
• Anas Alomaim, "Nation Building in Kuwait, 1961-1991."
• Tulay Atak, “Byzantine Modern: Displacements of Modernism in Istanbul.”
• Ewan Branda, “Virtual Machines: Culture, telematique, and the architecture of information at Centre Beaubourg, 1968–1977.”
• Aaron Cayer, "Design and Profit: Architectural Practice in the Age of Accumulation"
• Per-Johan Dahl, “Code Manipulation, Architecture In-Between Universal and Specific Urban Spaces.”
• Penelope Dean, “Delivery without Discipline: Architecture in the Age of Design.”
• Miriam Engler, “Gordon Cullen and the ‘Cut-and-Paste’ Urban Landscape.”
• Dora Epstein-Jones, “Architecture on the Move: Modernism and Mobility in the Postwar.”
• Sergio Figueiredo, “The Nai Effect: Museological Institutions and the Construction of Architectural Discourse.”
• Jose Gamez, “Contested Terrains: Space, Place, and Identity in Postcolonial Los Angeles.”
• Todd Gannon, “Dissipations, Accumulations, and Intermediations: Architecture, Media and the Archigrams, 1961–1974.”
• Whitney Moon, "The Architectural Happening: Diller and Scofidio, 1979-89"
• Eran Neuman, “Oblique Discourses: Claude Parent and Paul Virilio’s Oblique Function Theory and Postwar Architectural Modernity.”
• Alexander Ortenberg, “Drawing Practices: The Art and Craft of Architectural Representation.”
• Brian Sahotsky, "The Roman Construction Process: Building the Basilica of Maxentius"
• Marie Saldana, “A Procedural Reconstruction of the Urban Topography of Magnesia on The Maeander.”
• David Salomon, “One Thing or Another: The World Trade Center and the Implosion of Modernism.”
• Ari Seligmann, “Architectural Publicity in the Age of Globalization.”
• Zheng Tan, “Conditions of The Hong Kong Section: Spatial History and Regulatory Environment of Vertically Integrated Developments.”
• Jon Yoder, “Sight Design: The Immersive Visuality of John Lautner.”

A Sampling of PhD Alumni and Their Pedagogy

Iman Ansari , Assistant Professor of Architecture, the Knowlton School, Ohio State University

Tulay Atak , Adjunct Associate Professor, Pratt School of Architecture

Shannon Starkey , Associate Professor of Architecture, University of San Diego

Ece Okay , Affiliate Research, Université De Pau Et Des Pays De L'adour

Zheng Tan , Department of Architecture, Tongji University

Pelin Yoncaci , Assistant Professor, Department Of Architecture, Middle East Technical University

José L.S. Gámez , Interim Dean, College of Arts + Architecture, UNC Charlotte

Eran Neuman , Professor, School of Architecture, Tel Aviv University

Marie Saldana , Assistant Professor, School of Interior Architecture, University of Tennessee - Knoxville

Sergio M. Figueiredo , Assistant Professor, Eindhoven University of Technology

Rebecca Choi , Assistant Professor of Architecture History, School of Architecture, Tulane University

Will Davis , Lecturer in History, Theory and Criticism, Department of Architecture, National University of Singapore

Maura Lucking , Faculty, School of Architecture & Urban Planning, University of Wisconsin - Milwaukee

Kyle Stover , Assistant Professor, School of Architecture, Montana State University

Alex Maymind , Assistant Professor of Architecture and Director of Undergraduate Studies in Architecture, University of Minnesota

Gary Riichirō Fox , visiting faculty member at Southern California Institute of Architecture (SCI-Arc) and lecturer at USC School of Architecture

Randy Nakamura , Adjunct Professor, College of Arts and Sciences, University of San Francisco

Aaron Cayer , Assistant Professor of Architecture History, School of Architecture + Planning, University of New Mexico

Whitney Moon , Associate Professor of Architecture, School of Architecture & Urban Planning, University of Wisconsin - Milwaukee

Todd Gannon , Professor of Architecture, the Knowlton School, Ohio State University

Dora Epstein Jones , Professor of Practice, School of Architecture, the University of Texas at Austin

Sarah Hearne , Assistant Professor, College of Architecture and Planning, University of Colorado Denver

PhD Typical Study Program

*The choice of language to fulfill this requirement must be discussed with the Ph.D. Standing Committee

Our Current PhD Cohort

AUD's cohort of PhD candidates are leaders in their fields of study, deepening their scholarship at AUD and at UCLA while sharing their knowledge with the community.

Adam Boggs is a sixth year Ph.D candidate and interdisciplinary artist, scholar, educator and Urban Humanist. His research and teaching interests include the tension between creativity and automation, craft-based epistemologies, and the social and material history of architecture at the U.S.-Mexico border. He holds a BFA in Sculpture Cum Laude from the Ohio State University, and an MFA in Visual Art from the State University of New York at Purchase College. Prior to joining the doctoral program at UCLA he participated in courses in Architecture (studio and history) at Princeton University and Cornell University. His dissertation analyzes the history of indigenous labor during the Mexican baroque period to form a comparative analysis with the 20th century Spanish revival architecture movement in Southern California and how the implementation of the style along the U.S.-Mexico border might function as a Lefebvrian “thirdspace” that disrupts binary thinking. In Spring 2024 he will teach an undergraduate seminar course at AUD on the history of architecture at the U.S.-Mexico border as part of the CUTF program.

Hanyu Chen is a second-year doctoral student at UCLA AUD. Her research focuses on the intersection between (sub)urban studies, heritage conservation, and the genders of the space. Specifically, it concerns the dynamics of genders in (sub)urban areas and how these dynamics are conserved as heritage. Born and raised in China for her first 18 years, Hanyu chose the conservation of comfort stations in China as her master's thesis at the University of Southern California, where she earned her master’s degree in Heritage Conservation and officially started her journey in architecture. Her thesis discusses the fluidity and genders of comfort stations and how they survive in contemporary China’s heritage conservation policies.

Hanyu also holds a Bachelor of Science degree in AMS (Applied Mathematics and Statistics) and Art History from Stony Brook University.

Yixuan Chen

Yixuan Chen is an architectural designer and a first-year doctoral student in the Department of Architecture and Urban Design at UCLA. Driven by an impulse to demystify both the grand promises and trivial familiarities of architecture, her research embarks on the notion of everydayness to elucidate the power dynamics it reveals. She investigates the conflicts between these two ends and focuses on modernization across different times and places.

Prior to joining UCLA AUD, she was trained as an architect and graduated from the University of Nottingham's China Campus with a first-class honors degree. Her graduation project “Local Culture Preservation Centre,” which questioned the validity of monumental architecture in the climate crisis, was nominated for the RIBA President's Medal in 2016.

She also holds a Master of Arts degree with distinction in Architectural History from the Bartlett School of Architecture, University College London. Her dissertation, “Shijing, on the Debris of Shijing,” explores the vanishing shijing places, or urban villages, where rural migrant workers negotiate their urban identity in Chinese cities, revealing shifting power relations. Additionally, she authored an article in Prospectives Journal titled "Architectural Authorship in ‘the Last Mile,’" advocating for a change to relational architectural authorship in response to the digital revolution in architecture.

Pritam Dey is an urban designer and second-year doctoral student at UCLA AUD. His research interest lies at the intersection of colonial urbanism, sensorial history, and somatic inquiries. His architecture thesis investigated the crematorium and temple as sensorial infrastructure, and was presented at World Architecture Congress at Seoul in 2017. Previously Dey worked in the domain of urban design, specifically informal markets, as a shaper of urbanism in Indian cities. Prior to joining the AUD doctoral program, his past research focused on investigating the role of informal and wholesale markets in shaping up urbanity in the Indian city cores and co-mentored workshops on Urbanity of Chitpur Road, Kolkata with ENSAPLV, Paris which was both exhibited at Kolkata and Paris. He also co-mentored the documentation of the retrospective landscape of Hampi with the support of ENSAPLV and French Embassy. His investigations on the slums of Dharavi title ‘The tabooed city’ was published in the McGill University GLSA Research series 2021 under the theme: the city an object or subject of law?

An urban designer and architect, Pritam Dey pursued his post graduation from School of planning and Architecture, Delhi. During his academic tenure at SPA, he was the recipient of 2018 Design Innovation Center Fellowship for Habitat design allowing him to work on the social infrastructure for less catered communities in the Sub Himalayan Villages. In 2022 He mentored a series of exhibitions on the theme of Water, Mountains and Bodies at Ahmadabad.

He was the 2022-23 Urban Humanities Initiatives Fellow at UCLA and recipient of 2023 UCLA Center for India and South Asia fellowship for his summer research.

Carrie Gammell

Carrie Gammell is a doctoral candidate working at the intersection of architectural history, property law, and political economy. Her research focuses on claims, investments, and intermediary organizations in the United States, from the Homestead Act of 1862 to the Housing Act of 1934.

Carrie is also a Senior Research Associate at cityLAB UCLA, where she studies state appropriations for California community college student housing. In the past, she contributed to Education Workforce Housing in California: Developing the 21st Century Campus, a report and companion handbook that provides a comprehensive overview of the potential for land owned by school districts to be designed and developed for teachers and other employees.

Prior to joining AUD, Carrie worked as an architectural designer in Colombia and the United States, where she built a portfolio of affordable housing, multi-family residential, and single-family residential projects as well as civic and cultural renovations and additions. She holds a Bachelor of Architecture from Rice University and a Master in Design Studies (Critical Conservation) from the Harvard Graduate School of Design.

Chi-Chia Hou

Chi-Chia Hou is a doctoral candidate in his sixth year at UCLA AUD. His working dissertation, “New Frontier: Architecture and Service 1893-1960,” explores his interest in architecture and wealth, changing ideas of profit and management, and social scientific discourses for measuring work and worker, self and others, and values of landed property.

His research locates moments of theorizing methodologies to manage income-generating properties in schools of agriculture, home economics, and hotel studies. The schools taught their students theories, while instilling the imminence of faithful direction of oneself, of self-as-property. The pedagogies, existing beyond the purview of Architecture, were of immense architectural consideration.

Chi-Chia Hou took a break from school in the previous academic year to learn from his daughter and has now returned to school to learn from his brilliant cohorts.

Adam Lubitz

Adam Lubitz is an urban planner, heritage conservationist, and doctoral student. His research engages the intersection of critical heritage studies and migration studies, with an emphasis on how archival information can inform reparations. His community-based research has been most recently supported by the Columbia GSAPP Incubator Prize as well as the Ziman Center for Real Estate and Leve Center for Jewish Studies at UCLA.

Prior to joining AUD, Adam worked at World Monuments Fund within their Jewish Heritage Program, and taught GIS coursework at Barnard College. His master's thesis applied field research with experimental mapping techniques in the old town of a municipality in Palestine. Adam holds MS degrees in Historic Preservation and Urban Planning from Columbia University and a BA in Urban Studies from New College of Florida.

José Monge is a PhD candidate in the Department of Architecture and Urban Design. His dissertation, titled Maritime Labor, Candles, and the Architecture of the Enlightenment (1750-1872) , focuses on the role that whale-originated illuminants, specifically spermaceti candles and oil, played in the American Enlightenment as an intellectual project and the U.S. as a country. By unravelling the tension between binaries such as intellectual and manual labor–the consumers that bought these commodities and the producers that were not able to afford them–the project understands architecture as a history of activities that moved from sea to land and land to sea, challenging assumptions about the static “nature” of architecture.

Kurt Pelzer

Kurt Pelzer is a fourth-year PhD candidate at UCLA AUD. Their research explores the relational histories, material flows, and politics of land in and beyond California in the long nineteenth century during the United States parks, public lands, and conservation movements.

Their current scholarship traces the settler possession and exhibitionary display of a Giant Sequoia (Sequoiadendron giganteum) in the 1850s; an act that contested the ways Miwok peoples ancestral to California's Sierra Nevada knew and related to life and land. Their broader interests include histories of colonialism and capitalism in the Americas, environmental history, and Blackness and Indigeneity as a methodological analytic for political solidarities and possibilities.

Prior to arriving at UCLA, Pelzer worked at the San Francisco Museum of Modern Art in the Architecture and Design Curatorial Department participating in exhibitions, programming, and collections work. Pelzer completed a Master of Advanced Architectural Design in the History, Theory, and Experiments program from California College of the Arts in San Francisco, and earned their Bachelor's degree in Landscape Architecture from the College of Design at Iowa State University.

Shota Vashakmadze

Email Shota Vashakmadze

Shota Vashakmadze is a sixth-year PhD candidate at UCLA AUD. His dissertation traces the conjoined histories of architectural computing, environmental design, and professional practice in the late 20th century, adopting critical approaches to architecture’s technical substrates—the algorithms, softwares, and user protocols of computation—to examine their social and political dispositions. In his scholarship and pedagogy, he aims to situate forms of architectural labor within the profession’s ongoing acculturation to environmental crisis. Most recently, he has been leading the development of the interdisciplinary “Building Climates” cluster, a year-long course sequence at UCLA, and co-organizing an initiative dedicated to fostering discourse on climate change and architecture, including a two-day conference entitled “Architecture After a Green New Deal.”

His research has been supported by the Canadian Centre for Architecture and appeared in journals including Architectural Theory Review , The Avery Review, and Pidgin Magazine. He is currently completing a contribution to a collection on landscape representation and a chapter for an edited volume on architecture, labor, and political economy.

Shota holds an MArch from Princeton University and has a professional background in architecture, landscape, and software development. Before coming to UCLA, he researched methods for designing with point cloud data and wrote Bison, a software plugin for landscape modeling.

Alexa Vaughn

Alexa Vaughn (ASLA, FAAR) is a first year PhD student in Architecture + Urban Design and a Eugene V. Cota-Robles Fellow , from Long Beach, California. She is a Deaf landscape designer, accessibility specialist, consultant, and recent Fellow of the American Academy in Rome (2022-23). She is a visionary speaker, thought leader, prolific writer and researcher, and the author of “ DeafScape : Applying DeafSpace to Landscape,” which has been featured in numerous publications.

Her professional work is centered upon designing public landscapes with and for the Deaf and disabled communities, applying legal standards and Universal Design principles alongside lived experience and direct participation in the design process. She is an expert in designing landscapes for the Deaf community (DeafScape) and in facilitation of disabled community engagement. Prior to joining the A+UD program, Alexa worked for several landscape architecture firms over the course of six years, including OLIN and MIG, Inc.

Through a disability justice lens, her dissertation will seek to formally explore the historical exclusionary and inaccessible design of American urban landscapes and public spaces, as well as the response (activism, policy, and design) to this history through the present and speculative future. She will also actively take part in activist- and practice-based research with cityLAB and the Urban Humanities Institute .

Alexa holds both a BA in Landscape Architecture (with a minor in Conservation and Resource Studies) and a Master’s degree in Landscape Architecture (MLA) from the University of California, Berkeley, with specialization in accessible and inclusive design. Much of her work can be found at www.designwithdisabledpeoplenow.com and on Instagram: @DeafScape.

Yashada Wagle

Yashada Wagle is a third year PhD student in Critical Studies at UCLA AUD, and a recipient of the department's Moss Scholarship. Her research focuses on imperial environmental-legislative regimes in British colonial India in the late nineteenth century. She is interested in exploring questions around the histories of spaces of extraction and production as they network between the metropole and the colony, and their relationship with the conceptions of laboring bodies therein. Her master's thesis focused on the Indian Forest Act of 1865, and elucidated the conceptualization of the space of the ‘forest’ through the lenses of its literary, legislative, and biopolitical trajectories, highlighting how these have informed its contemporary lived materiality.

Wagle holds a Bachelor in Architecture (BArch) from the Savitribai Phule Pune University in India, and a Master in Design Studies (History and Philosophy of Design and Media) from the Harvard Graduate School of Design. She was previously a Research Fellow at the Kamla Raheja Vidyanidhi Institute for Architecture and Environmental Studies (KRVIA) in Mumbai, India.

In her spare time, Wagle enjoys illustrating and writing poetry, some of which can be found here .

Dexter Walcott

Dexter Walcott is a registered architect currently in his fifth year with the Critical Studies of Architecture program at UCLA. His research focuses on the Latrobe family and early nineteenth century builders in the Mississippi and Ohio river valleys. He is interested in the role of the built environment in histories of labor, capitalism, steam-power, and industry.

Born and raised in Hong Kong, Joy is a fifth-year PhD student in architecture history. Her research explores geology as antiquity from early 19th – 20th century British colonial Hong Kong and China. She holds a B.A. in Comparative Literature with a focus in German from Middlebury College in 2017, and is a graduate of The New Normal program at Strelka Institute, Moscow in 2018. Previously, she has taught in the Department of Architecture at University of Hong Kong, as well as the Department of Design at Hong Kong Polytechnic University.

After working as a curatorial assistant at Tai Kwun Contemporary in 2019, she has continued the practice of art writing and translation, collaborating with many local Hong Kong artists as well as international curators such as Raimundas Malašauskas. In her spare time, she practices long-distance open water swimming. In 2022, she completed a 30km course at the South of Lantau Island, Hong Kong.

The MA and PhD programs welcome and accept applications from students with a diverse range of backgrounds. These programs are designed to help those interested in academic work in architecture develop those skills, so we strongly encourage that you become familiar with fundamental, celebrated works in the history and theory of architecture before entering the program.

Applicants to the academic graduate programs must hold a Bachelor’s degree, or the foreign equivalent. All new students must enter in the fall quarter. The program is full-time and does not accept part-time students.

Applications for the MA and PhD programs (Fall 2024 matriculation) will be available in Fall 2023, with application deadline of January 6, 2024; please revisit this page for updates. Accepted candidates who wish to enroll must file an online Statement of Intent to Register (SIR) by April 15, 2024.

How to Apply

Applying to the MA and PhD programs is an online process via the UCLA Application for Graduate Admission (AGA).

Completing the requirements will take some time, so we strongly recommend logging in to the AGA in advance to familiarize yourself with the site and downloading the documents and forms you will need to complete your application.

You can also download this checklist to make sure you have prepared and submitted all the relevant documents to complete your application.

Your Statement of Purpose is a critical part of your application to the MA and PhD programs. It is your opportunity to introduce yourself and tell us about your specific academic background, interests, achievements, and goals. Our selection committee use it to evaluate your aptitude for study, as well as consideration for merit-based financial support.

Your statement can be up to 1500 words in length. Below are some questions you might want to consider. You don’t need to answer every question; just focus on the elements that are most relevant to you.

• What is your purpose in applying to the MA or PhD program? Describe your area(s) of research interest, including any areas of concentration and specialization.
• What experiences have prepared you for this program? What relevant skills have you gained from these experiences? Have your experiences led to specific or tangible outcomes that would support your potential to contribute to this field (e.g. performances, publications, presentations, awards or recognitions)?
• What other information about your past experience might help the selection committee in evaluating your suitability for this program? E.g. research, employment, teaching, service, artistic or international experiences through which you have developed skills in leadership, communication, project management, teamwork, or other areas.
• Why is UCLA Architecture and Urban Design the best place for you to pursue your academic goals?
• What are your plans for your career after earning this degree?

Your Personal Statement is your opportunity to provide additional information to help the selection committee evaluate your aptitude for study. It will also be used to consider candidates for UCLA Graduate Division fellowships related to diversity. You can read more about the University of California Diversity Statement here .

Your statement can be up to 500 words in length. Below are some questions you might want to consider. You don’t need to answer every question; just focus on the elements that are most relevant to you.

• Are there educational, personal, cultural, economic, or social experiences, not described in your Statement of Purpose, that have shaped your academic journey? If so, how? Have any of these experiences provided unique perspective(s) that you would contribute to your program, field or profession?
• Describe challenge(s) or barriers that you have faced in your pursuit of higher education. What motivated you to persist, and how did you overcome them? What is the evidence of your persistence, progress or success?
• How have your life experiences and educational background informed your understanding of the barriers facing groups that are underrepresented in higher education?
• How have you been actively engaged (e.g., through participation, employment, service, teaching or other activities) in programs or activities focused on increasing participation by groups that have been historically underrepresented in higher education?
• How do you intend to engage in scholarly discourse, research, teaching, creative efforts, and/or community engagement during your graduate program that have the potential to advance diversity and equal opportunity in higher education?
• How do you see yourself contributing to diversity in your profession after you complete your academic degree at UCLA Architecture and Urban Design?

A Curriculum Vitae (résumé of your academic and professional experience) is recommended but not required.

Applicants must upload a scanned copy of the official transcripts from each college or university you have attended both in the U.S. and abroad. If you are accepted into the program you will be required to submit hard copies. These can either be sent directly from each institution or hand-delivered as long as they remain in the official, signed, sealed envelopes from your college or university. As a general rule, UCLA Graduate Division sets a minimum required overall grade-point average of 3.0 (B), or the foreign equivalent.

As of this Fall 2023 cycle, the GRE is NOT required as part of your application to UCLA AUD. No preference will be given to those who choose to submit GRE scores as part of their application.

However, if you do take the GRE exam and wish to include it as part of your application: More information on this standardized exam can be found at www.ets.org/gre . In addition to uploading your GRE scores, please direct ETS to send us your official score sheets. Our ETS codes for the GRE are below:

UCLA Architecture and Urban Design Institution Code: 4837 Department Code: 4401

We recommend you take the exam at least three weeks before the application deadline as it usually takes 2-3 weeks for ETS to send us the test scores.

If you have received a Bachelor’s degree in a country where the official language of instruction and primary spoken language of daily life is not English, you must submit either a Test of English as a Foreign Language (TOEFL) or an International English Language Testing System (IELTS). Exempt countries include Australia, Barbados, Canada, Ireland, Jamaica, New Zealand and the United Kingdom. This is a requirement that is regardless of your visa or citizenship status in the United States.

To be considered for admission to the M.Arch. program, international students must score at least a 92 on the TOEFL or a 7 on the IELTS exam. Because processing, sending, and receiving TOEFL and IELTS scores can take several weeks, international students must schedule their exam no later than October 31 in order to meet UCLA deadlines. TOEFL scores must be sent to us directly and uploaded as part of the online submission. Our ETS codes for the TOEFL are below:

UCLA Architecture and Urban Design Institution Code: 4837 Department Code: 12

If your score is less than 100 on the TOEFL or 7.5 on the IELTS, you are also required to take the English as a Second Language Placement Examination (ESLPE) on arrival at UCLA. The results of this test will determine any English as a Second Language (ESL) courses you need to take in your first term of residence. These courses cannot be applied towards your minimum course requirements. As such, you should expect to have a higher course load than students not required to take ESL courses.

If you have earned a degree or completed two years of full-time college-level coursework in the following countries, your TOEFL / IELTS and ESLPE requirements will be waived: U.S., U.K., Canada (other than Quebec), Australia, and New Zealand. Please provide official transcripts to demonstrate course completion. Unfortunately, we cannot accept any other documentation to demonstrate language proficiency.

Three (3) letters of recommendation are required. These letters should be from individuals who are familiar with your academic and professional experiences and can evaluate your capacity to successfully undertake graduate studies at UCLA. If you do not have an architecture background please note that we are looking for letters that evaluate your potential as a graduate student, not necessarily your architecture experience.

Letters of recommendation must be sent electronically directly to UCLA by the recommender. When logged in, you can enter the name and email address of each of your recommenders. They will be contacted by email with a request to submit a letter on your behalf. You can track which letters have and have not been received. You can also send reminders to your recommenders to send their letters.

Writing samples should illustrate an applicant’s capacities for research, analytical writing and scholarly citation. Texts may include seminar papers, theses, and/or professional writing.

Please complete and submit the Department Supplement Form to confirm your intention to apply to the MA or PhD program.

Master of Science in Mathematics and Applied Statistics

At California State University Long Beach

The Department of Mathematics & Statistics at CSULB offers four Master of Science programs .

Teaching & Graduate Assistantships provide students with funding and with college teaching experience.

Graduates have found employment in both technical and academic workplaces. Many have obtained tenure-track community college professorships. Others have gone on to PhD programs.

MS in Mathematics, General Option

Study and explore concepts in areas including analysis, algebra, topology, and geometry, as well as the   deep connections between and among these subjects.

MS in Mathematics, Option in Applied Mathematics

Study applied math methods with an emphasis on computational skills.

MS in Mathematics, Option in Mathematics Education for Secondary School Teachers

A flexible program that includes coursework in mathematics and in mathematics education research & theory.

MS in Applied Statistics

Using conceptual foundations and statistical software packages ( SAS , R , and Python ), students are trained to analyze real world data appropriately and communicate their findings effectively. The tools learnt here will open the door for careers in data science and analytics, or prepare you for a PhD in a variety of related fields.

More Information & Application Instructions

Apply for Teaching and Graduate Assistantships

Contact Us with Questions

Dr. John Brevik, Pure Mathematics Graduate Advisor, [email protected]

Dr. Paul Sun, Applied Math Graduate Advisor, [email protected]

Dr. Xuhui Li, Mathematics Education Graduate Advisor, [email protected]

Dr. Kagba Suaray, Statistics Graduate Advisor, [email protected]

Applied Computation

The Computational Science and Engineering (CSE) master’s program, led by faculty from Computer Science, Applied Math and the Engineering Sciences, provides rigorous training in the mathematical and computational foundations of CSE. The master’s program offers students experience with mathematical techniques for modeling and simulation of complex systems; parallel programming and collaborative software development; and methods for organizing, exploring, visualizing, processing and analyzing very large data sets.

The Data Science master’s program, jointly led by the Computer Science and Statistics faculties, trains students in the rapidly growing field of data science. The program offers strong preparation in statistical modeling, machine learning, optimization, management and analysis of massive data sets, and data acquisition. The program focuses on topics such as reproducible data analysis, collaborative problem solving, visualization and communication, and security and ethical issues that arise in data science.

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AMATH 383 A: Introduction to Continuous Mathematical Modeling

Summer 2024 Full-term View in MyPlan View in Time Schedule Meeting: MWF 12:00pm - 1:00pm / SIG 134 SLN: 10059 Section Type: Lecture INSTRUCTOR TBD - TAUGHT IN PERSON. Catalog Description: Introductory survey of applied mathematics with emphasis on modeling of physical and biological problems in terms of differential equations. Formulation, solution, and interpretation of the results. Prerequisite: either AMATH 351, MATH 136, or MATH 207. Offered: AWS. GE Requirements Met: Natural Sciences (NSc) Credits: 3.0 Status: Active Last updated: April 10, 2024 - 9:28 pm

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