Dr. Archontis Giannakidis is a Medical Image Analysis Scientist with the National Heart and Lung Institute (NHLI) of Imperial College London, UK.
He received his BSc in Electrical and Computer Engineering from the Aristotle University of Thessaloniki, Greece, and his MSc (with distinction) in Modern Digital and Wireless Communications from the University of Leeds, UK. In 2010, he was awarded his PhD in Electronic Engineering (area:
economic interdependencies, inverse problems/vector-field tomographic reconstruction) from the University of Surrey, UK.
Dr. Giannakidis has received postdoctoral training in research centres with high global impact (Imperial College London, Berkeley Lab, Johns Hopkins University). He has participated in numerous cutting-edge research projects funded by the European Union (EPSRC, BHF) and the United States of America (NIH, Department of Energy). He has been on the organisation committee for international conferences, and has experience supervising MSc and BSc students. He has won EPSRC scholarship awards due to achieving high academic performance, and is a regular reviewer for major international journals such as IEEE Transactions on Medical Imaging, Journal of Cardiovascular Magnetic Resonance, and IoP.
Archontis possesses teaching experience (private, small groups, and classroom). In the past, he taught Mathematics for 1st year students (small groups) at the Department of Electronic and Electrical Engineering, Imperial College London. He also worked as an IT instructor in Greece, teaching Java, C++.
Dr. Giannakidis's research lies in the area of medical image analysis and machine learning for magnetic resonance imaging (MRI). He has published 30 academic publications.
By the end of this module, students will be able to identify when a particular application they encounter in future studies is ripe for a solution via linear algebra. In practical terms, this module aims to produce students who can perform computations with matrices and large linear systems while at the same time understand the concepts behind these techniques. The students will learn explicit skills such as Gaussian elimination and diagonalisation, in order that vectors and matrices become calculational tools, rather than abstract mathematics.
SKILLS:
- Medical Imaging
- Diffusion Tensor Imaging
- Signal Processing
- Machine Learning
- Pattern Recognition
- Mathematical Modeling
- Matlab
DATE: 27 Nov - 15 Dec, 2017
DURATION: 3 Weeks
LECTURES: 3 Hours per day
LANGUAGE: English
LOCATION: Barcelona, Harbour.Space Campus
COURSE TYPE: Offline
WHAT YOU WILL LEARN
COURSE OUTLINE
ABOUT ARCHONTIS
BIBLIOGRAPHY
HARBOUR.SPACE
In this module, you will be introduced to the fundamental branch of mathematics called Linear Algebra. The three main topics of study, which are closely related to each other, will be matrices, systems of linear equations, and vector spaces. These mathematical structures can be used to model the world around us. It’s no wonder that some experts suggest ‘’when a problem can be reduced to one of linear algebra it is solved". What you learn in this module will be useful in your future studies.
HARBOUR.SPACE UNIVERSITY
DATE: 27 Nov – 15 Dec, 2017
DURATION: 3 Weeks
LECTURES: 3 Hours per day
LANGUAGE: English
LOCATION: Barcelona, Harbour.Space Campus
COURSE TYPE: Offline
Session 2
Inverse Matrix and Powers of Matrices
Session 3
Special Matrices
Session 4
Determinants & Inverse Matrices
Session 1
Matrices
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