Charles Fefferman is affiliated with Princeton University in the United States and has made contributions primarily in the field of Mathematics. Their research spans several subfields including Mathematical Physics, Atomic and Molecular Physics and Optics, Control and Systems Engineering, Computational Theory and Mathematics, and Statistics and Probability.
The scientist's work broadly covers topics such as Numerical Methods in Inverse Problems, Cold Atom Physics and Bose-Einstein Condensates, Quantum and Electron Transport Phenomena, Machine Learning and Algorithms, Advanced Bandit Algorithms Research, Advanced Control Systems Optimization, and Topological and Geometric Data Analysis.
Frequent collaborators include Matti Lassas, Hariharan Narayanan, Michael I. Weinstein, Arie Israel, and Sergei Ivanov.
Charles Fefferman's recent papers include:
Publication venues where Fefferman has frequently published include:
The scientist has contributed a book titled Fitting Smooth Functions to Data, published by the American Mathematical Society in 2020.
Throughout their career, Charles Fefferman has received several distinctions, including:
C. Fefferman;C. Fefferman;E. M. Stein;E. M. Stein
R. R. Coifman;C. Fefferman
C. Fefferman;E. M. Stein
Charles Louis Fefferman
Charles Fefferman
Charles L. Fefferman
Harold Donnelly;Charles Louis Fefferman
Charles Fefferman
Charles L. Fefferman
Charles Louis Fefferman;C. Robin Graham
Charles Fefferman
Antonio Córdoba;Charles Fefferman
Charles Fefferman
Peter Constantin;Charles Fefferman;Andrew J. Majda
Charles Fefferman
Harold Donnelly;Charles Fefferman
Charles Louis Fefferman;Michael I. Weinstein
Charles Fefferman
Simon Myers;Charles Louis Fefferman;Nick Patterson
Charles L. Fefferman;David S. McCormick;James C. Robinson;Jose L. Rodrigo
If you think any of the details on this page are incorrect, let us know.
For students studying Mathematics in the USA, exploring related online degrees can open diverse career pathways. Many professionals choose to complement their mathematical skills with business or finance education. For example, pursuing an easy online MBA programs can provide valuable leadership and management expertise without the intense time commitment of traditional MBAs.
Those interested in advanced business roles might consider DBA programs online, which offer doctoral-level insights into administration and strategy. This can be especially useful for mathematicians aiming for executive or academic positions.
For a finance-focused career, an master of finance online degree can sharpen quantitative skills and deepen understanding of financial markets, risk management, and investment. These programs often align well with a mathematics background.
If time is a concern, exploring the fastest MBA programs online can enable students to quickly gain essential business knowledge and advance their careers efficiently. Combining math expertise with these degrees can unlock roles in analytics, consultancy, and strategic planning.
Stanford University
National Research Council (CNR)
Chinese Academy of Sciences
The Ohio State University
University of New South Wales
Macquarie University
University of Wisconsin–Madison
Universidade de São Paulo
University of Washington
National Institute of Allergy and Infectious Diseases
Utrecht University
London School of Hygiene & Tropical Medicine
University of Wisconsin–Madison
Atilim University
Claude Bernard University Lyon 1
Helmholtz Centre for Environmental Research