Recent Funding

Studie Entwicklungsstand Quantencomputer
Study development of quantum computer

PI: Rainer Steinwandt

Funding Agency: Saarland University (GER)
German Federal Office for Information Security


Linking Within-Host and Between-Host
Infectious Disease Dynamics

PI: Necibe Tuncer

Funding Agency: National Science Foundation


Emerging Side-Channel Resistant and
Resource-Friendly Elliptic Curve
Algorithms and Architectures 

PI: Reza Azarderakhsh/Co-PI: Koray Karabina

Funding Agency: US Army


Recent Publications

Dr. Tim Ford, has written a new 
textbook entitles, Separable Algebra.
Due to be published on October 20, 2017,
this book presents a comprehensive
introduction to the theory of separable
algebras over commutative rings.
Azumaya algebras, the henselization of
local rings, and Galois theory are
rigorously introduced and treated.
Essential connections are drawn
between the theory of separable
algebras and Morita theory, the theory
of faithfully flat descent, cohomology,
derivations, differentials, reflexive lattices,
maximal orders, and class groups. 

http://bookstore.ams.org/gsm-183/


 

Subject-wise empirical likelihood

inference in partial linear models
for longitudinal data

Lianfen Qian, Suojin Wang

Computational Statistics & Data Analysis


On the Tucker Circles

Sandor Nagydobai Kiss, Paul Yiu

Forum Geometricorum


Connecting Orbits for Compact Infinite 

Dimensional Maps: Computer Assisted 
Proofs of Existence

R. de la Llave, J.D. Mireles James

SIAM Journal on Applied Dynamical Systems


 

See our Calendar

 

 

 

 

 

 

 

 

 

 

 

 

 

Master of Science in Applied Mathematics and Statistics

The purpose of this program is to prepare students for the application of mathematics in industry and scientific research. The three tracks currently offered in the program are biostatistics, cryptology & information security, and financial mathematics.

ADMISSION REQUIREMENTS:

A Bachelor's degree in Mathematics (or equivalent coursework) with at least 3.0 GPA (or equivalent), three letters of recommendation documenting the applicant's prior work in mathematics focusing on preparation and suitability for success in graduate-level mathematics courses,a quantitative general GRE (revised) score of at least 155, computer competency, and approval of the departmental graduate committee. In addition, it is recommended to include scores of the GRE subject test mathematics as part of the application package .

Click here for detailed application steps: application information.

DEGREE REQUIREMENTS:

To complete the M.S. degree in Applied Mathematics and Statistics, the candidate must complete at least 30 credit hours of graduate course work, and satisfy the following criteria in addition to University requirements:

[1] Earn at least 24 credits in courses specified in a degree track, pre-approved by the graduate advisor in mathematics, at least 15 credits of which are at the 6000-level   (for details, see the graduate advisor);

[2]  If pre-approved by the department graduate committee, up to 12 credits of FAU coursework from outside of the Department of Mathematical Sciences may count toward the degree.

[3] Complete a capstone project with the following three options:

  1. Successfully complete and defend a master's thesis, earning at least 6 credits of MAT 6971 (Master's Thesis).
  2. Successfully complete and report on an Industrial Internship, earning at least 6 credits.
  3. Successfully complete a Master’s examination.

DEGREE TRACKS:

Biostatistics Track:

Six Required Courses:

  • STA 6444 Mathematical Probability
  • STA 6326 Mathematical Statistics
  • STA 6208 Regression Analysis
  • STA 6857 Applied Time Series Analysis
  • STA 5195 Biostatistics
  • STA 6177 Survival Analysis

At Least Two Elective Courses:

  • STA 6197 Biostatistics - Longitudinal Data Analysis
  • STA 6206 Statistical Methods for Environmental Sciences
  • STA 6207 Applied Statistical Methods
  • STA 6446 Topics in Probability and Statistics
  • STA 6707 Analysis of Multivariate Data
  • STA 5225 Survey Sampling
  • STA 6505 Analysis of Categorical Data
  • STA 6106 Statistical Computing
  • CAP 6673 Machine Learning and Data Mining 

Cryptology Track:

Three courses from:

  • MAS 5311 Introductory Abstract Algebra 1
  • MAS 5312 Introductory Abstract Algebra 2
  • MAA 5228 Introductory Analysis 1
  • MAA 5229 Introductory Analysis 2
  • STA 6444 Mathematical Probability
  • STA 6326 Mathematical Statistics

 Three required:

  • MAD 5474 Introduction to Cryptology and Information Security
  • MAD 6478 Cryptanalysis 
  • MAD 6607 Coding Theory

 At Least Two Elective Courses

  • MAT 6933 Elliptic Curves
  • MAT 6396 Algebraic Curves
  • MAT 6396 Group Theory
  • MAD 6477 Cryptography
  • MAS 6215 Algebraic Number Theory
  • STA 6444 Mathematical Probability
  • STA 6326 Mathematical Statistics
  • MAS 5145 Linear Algebra
  • COT 5930 Randomized Algorithm
  • COT 6405 Analysis of Algorithms
  • CNT 5008 Computer Network
  • EEL 6532 Information Theory
  • CIS 6370 Computer Data Security
  • MAT 6933 Computational Group Theory
  • MAT 6933 Computational Math
  • MAT 6396 Commutative Algebra
  • MAD 6206 Enumerative Combinatorics
  • MAD 6207 Combinatorics 2
  • MAD 6307 Graph Theory
  • CIS 6375 ‐ Distributed Systems Security
  • CIS 6370 ‐ Computer Data Security
  • COT 6116 ‐ Secret Sharing Protocols

Financial Mathematics Track:

Six Required Courses:

  • MAA 5228 Introductory Analysis 1
  • STA 6444 Mathematical Probability
  • STA 6326 Mathematical Statistics
  • STA 6857 Applied Time Series
  • STA 6907 Financial Mathematics 1
  • STA 6446 Stochastic Calculus

 At least Two Elective Courses:

  • STA 6208 Regression Analysis
  • STA 6908 Financial Mathematics 2
  • FIN 6406 Financial Management
  • FIN 6246 Financial Markets
  • FIN 6525 Portfolio Theory
  • STA 6207 Applied Statistical Methods
  • STA 6446 Topics in Stochastic Processes
  • STA 6106 Statistical Comp
  • STA 6909 Numerical Methods in Finance
  • MAA 5229 Introductory Analysis 2
  • MAS 5145 -- Linear Algebra
  • MAA 5105 -- Multivariable Analysis
  • CAP 6673 Machine Learning and Data Mining 

* As with all degree programs, the authoritative source for the degree requirements is the University Catalog that was in effect for the academic year in which the student entered the University. The information on this page does not supersede the Catalog.

For information about the PHD, MS, and AMST programs contact:
Prof. Yuan Wang, Graduate Director
Department of Mathematical Sciences
Florida Atlantic University
777 Glades RD
Boca Raton, FL 33431