I started the journey with the study Mechatronics at The Hague Applied Sciences (focus on machine learning, robotics and computer vision). After my graduation, I worked part-time at a company, and working on my pre-master, at the TU Delft for the master computer engineering (started in February 2019). Hopefully, I will finish my master before September 2020.
I am working on my thesis in Spiking Neural Networks see following link blog post
This is a list of master topics that I followed:
- Network Security (Parts of Advance Network Security and crypto)
- Deep Learning, Computer Vision
- CPU design: caches, core, ALU (like a 2-cycle multiplier)
- GPU, FPGA, Multi-data instructions
- Operating systems
- ADHOC networks focus on mesh-networks
- Web data management
- Entrepreneurship, business plan
The main focus of my career is the field of Artificial Intelligence (Machine Learning, Deep Learning, Spiking Neural Networks). I believe that the first thing that needs to be done is using non Artificial Intelligence algorithm. The field is quite large with many focus points, therefor I made a small list with AI methods that I have been working with.
|Adaboost, Bagging, Stumping|
|PCA, SOM, many more|
|Viola and Jones|
|Learning methods: Momentum, Rprop, Adams|
|Heat-maps and other data validation techniques|
|Small evolutionary algorithm with fitness function|
The following list is for deep learning.
|RESNet and variants|
|VGG and variants|
|Inception and variants|
|C++ implementation of a CNN|
|Framework Keras (see paper-blog for source code)|
The following list is for spiking neural networks.
|Spiking Neural Networks|
|digital ANN to analog SNN|
|Leaky-integrate and fire|
|LSM (just touched)|