GG

Gianluca Guadagni

Assistant Professor
Assistant Professor, Department of Engineering and Society
Unit: School of Engineering and Applied Science
Department: Department of Engineering and Society
Office location and address
156 Engineer's Way
Charlottesville, Virginia 22903
APMA 2130: Ordinary Differential Equations
Credits: 4
First order differential equations, second order and higher order linear differential equations, reduction of order, undetermined coefficients, variation of parameters, series solutions, Laplace transforms, linear systems of first order differential equations and the associated matrix theory, numerical methods. Applications. Prerequisite: APMA 2120 or equivalent.
BME 2315: Computational Biomedical Engineering
Credits: 3
Introduces computational techniques for solving biomedical engineering problems & constructing models of biologic processes. Numerical techniques include regression, interpolation, differentiation, integration, root finding, systems of equations, optimization and approaches to ordinary differential equations. Applications include bioreactors, biotransport, pharmacokinetics & biomechanics. Prereq: APMA 2120 & CS 1110; recommended co-req APMA 2130.
STS 2500: Science and Technology in Social and Global Context
Credits: 3
This course invites students to explore the implications of STS core concepts within a specific topical or disciplinary area, drawing out the implications of STS 1500 in depth. The course explores the social and global context of engineering, science and technology. Although writing and speaking skills are emphasized, more attention is given to course content and the students' analytical abilities. Prerequisites: STS 1500 or an equivalent STS course.
APMA 3150: From Data to Knowledge
Credits: 3
This course uses a Case-Study approach to teach statistical techniques with R. Basic statistical techniques include confidence intervals, hypotheses tests, regression, and anova. In addition, the course covers major statistical learning techniques for both supervised and unsupervised learning. Supervised learning topics cover regression and classification while unsupervised learning topics cover clustering and principal component analysis.
APMA 3501: Special Topics in Applied Mathematics
Credits: 1–4
Applies mathematical techniques to special problems of current interest. Topic for each semester are announced at the time of course enrollment.
APMA 4501: Special Topics in Applied Mathematics
Credits: 3
Applies mathematical techniques to special problems of current interest. Topic for each semester are announced at the time of course enrollment.
APMA 4993: Independent Reading and Research
Credits: 1–3
Reading and research under the direction of a faculty member. Prerequisite: Fourth-year standing.
APMA 5070: Numerical Methods
Credits: 3
Introduces techniques used in obtaining numerical solutions, emphasizing error estimation. Includes approximation and integration of functions, and solution of algebraic and differential equations. Prerequisite: Two years of college mathematics, including some linear algebra and differential equations, and the ability to write computer programs in any language.
MAE 6430: Statistics for Engineers and Scientists
Credits: 3
Role of statistics in science, hypothesis tests of significance, confidence intervals, design of experiments, regression, correlation analysis, analysis of variance, and introduction to statistical computing with statistical software libraries. Cross-listed as APMA 6430. Prerequisite: Admission to graduate studies or instructor permission.
APMA 6548: Special Topics in Applied Mathematics
Credits: 1–3
Topics vary from year to year and are selected to fill special needs of graduate students.
APMA 8897: Graduate Teaching Instruction
Credits: 1–12
For master's students.
APMA 9897: Graduate Teaching Instruction
Credits: 1–12
For doctoral students.