Explore the programs and courses offered by Functional Statistics, Probabilities
Browse Programs Admission InformationSubjects taught : Applied Mathematics
Specialty: Functional Statistics, Probabilities,
Program Overview:
The doctoral program in Applied Mathematics aims to train highly qualified researchers capable of making significant contributions to strategic sectors such as energy security, public health, and food security. The program focuses on developing advanced mathematical models, optimization techniques, and statistical analyses applicable to real-world challenges in engineering, natural sciences, economics, and finance. By fostering expertise in these areas, the program supports scientific and technological advancement and addresses critical societal issues.
· Semester 1:
· Dynamical Systems I (1 lecture per week)
· Advanced Optimization
· Wavelet Theory and Applications I (1 lecture and 1 practical session per week)
· Systems of Interacting Particles I (1 lecture per week)
· Functional Statistics I (1 lecture per week)
· Semester 2:
· Dynamical Systems II (1 lecture per week)
· Machine Learning
· Wavelet Theory and Applications II (1 lecture and 1 practical session per week)
· Systems of Interacting Particles II (1 lecture per week)
· Functional Statistics II (1 lecture per week)
Doctoral candidates will engage in advanced research topics, including:
· Enhanced Fisher Discriminant Analysis in Supervised Learning
· Medical Data Analysis using Wavelets and Machine Learning
· Functional Prediction of Electricity Consumption via M-Estimation
· Environmental Risk Prediction through Local Polynomial Estimation
· Two-Scale Contact Processes with Asymptomatic States
· Mathematical Modeling of Glucose-Insulin Systems for Diabetes Management
· Analysis of Obesity's Impact on Public Health: Models and Forecasts
Each topic is designed to address pressing issues in various sectors, promoting interdisciplinary research and innovation.