Ing. Antonie Brožová

EXPERIENCE

March 2021 – present: PhD student, Institute of Information Theory and Automation, CAS, Department of Adaptive Systems

• Studied topics: blind image deconvolution, variational Bayes method, deep learning in image processing, atmospheric inversion, Gaussian processes

April, 2020 – February 2021: Research assistant, Institute of Information Theory and Automation, CAS, Department of Adaptive Systems

• Studied topics: blind image deconvolution

TEACHING

Fall semester 2021, 2022, 2023: labs in Calculus 1, FNSPE CTU

EDUCATION

March, 2021 - present: CTU, Faculty of Nuclear Sciences and Physical Engineering - PhD programme: Mathematical Engineering

2018 – Feb, 2021: CTU, Faculty of Nuclear Sciences and Physical Engineering - master programme: Applied Mathematical Stochastic Methods

• Fall semester 2019: exchange programme at Kansas State University, USA – courses taken: Applied Data Mining/Machine Learning and Predictive Analytics, Mathematics of Data and Networks, Bayesian Inference, Experimental Design for Product Development and Quality Improvement
• Defended thesis: Blind image deconvolution with space variant convolution kernel - study of hierarchical Bayesian models and evidence lower bound optimization for blind image deconvolution.

2015 – 2018: CTU, Faculty of Nuclear Sciences and Physical Engineering – bachelor programme: Mathematical Engineering with focus on Applied Mathematical Stochastic Methods

• Defended thesis: Analyses of scintigraphic image sequences in medical diagnostics

LANGUAGES

English – FCE (B2, 2014), compulsory school course with an exam (C1 Academic English)

German – passive knowledge, compulsory school course (intermediate level)

SKILLS

Actively using: Julia, python (pytorch), MATLAB

Previously used: SAS, R, C++