background
Here I explain the specific topics that I worked on or studied during my previous education. These topics are also my areas of interest.
PhD in Computational Neuroscience (Neuroscience)
Neural coding (encoding) using extracellular recordings(spikes and LFP)
Novel Spike train analysis and Local field potentials (Phase-of-firing)
Modelling Local Field Potentials
Estimation of mutual information for continuous signals (with focus on signals with large ranges of temporal correlations)
Bias correction methods I(S;R)
PhD Thesis: "Quantifying sensory information in continuous brain signals" (January 2014)
MSc in Scientific Calculations (Computer Science)
Non-linear Optimization (Lagrange multipliers, KKT conditions, DFP, trust region, etc)
Numerical Linear Algebra
Non-smooth optimization
Computability, and Computational complexity
Master Thesis: "Global optimisation methods for the Protein Folding problem"
BSc in Software Engineering (Computer Engineering)
Algorithms design
C++ and Java programming
Numerical methods
Computer architecture and hardware design
Many other topics (including Computer Graphics, Computer Simulation)
BSc Thesis: "A real-time audio processing toolbox in C++".
Other research: Also during my research at IPM, I studied and presented the following topics among others:
Simplified neuron models (e.g. Jolivet & Gerstner 2007, or Eggert & van Hemmen 2001)
Conductance based neural modelling (phase plane analysis of bursting models)
Design of Psychophysics tasks (I designed a task for discrimination of grammar through tactile modality)
Perceptual Decision Making (esp. research by Michael Shadlen )
The reward system (and value based decision making)
Pattern recognition and Machine learning (advanced ML, including Dempster-Schafer theory)
During my master I also contributed to a paper in which we designed the first "asymmetric quantum cloning machine" (Quantum Information Theory). The result was published in Physics Letters A: http://dx.doi.org/10.1016/j.physleta.2004.12.015