
Years Experience
Clients Helped
Completed Projects
Areas of Expertise
Areas of Expertice
Software Development
Writing lowlevel and highlevel applications. Using and managing software application. Automation and architecture documentation.
Software Development
Soft Skills:
Advise you how to use software tools.
Advise you what software tools to use and buy.
Handle communication between software tools.
Web development:
Angular
React 4+
jQuery
Vue.js
Nest.js
Node.js
ASP.NET
App development:
Android Studio
Xamarin
Ionic
Cordova
Electron
Node.js
Programming Languages:
JavaScript / Typescript
C / C++
C#
Java
R
F#
Python
PHP
MATLAB
Automation
Identify opportunities for automation within software processes.
Design and execute QA tests using scripts that automatically test functionality.
Run tests for databases, systems, networks, applications, hardware and software.
Identify bugs and quality issues in development, service or business processes.
Install applications and databases relevant to automation.
Collaborate with other business units to understand how automation can improve workflow.
Gather requirements from clients, customers or end-users to develop the best automation solutions.
Creating shareable and reusable virtual development environments in tools like Docker.
Continuous integration with tools like TravisCI.
Automating testing and deployment of code with tools like Jenkins CI.
Embedded Development
Designing simple PCB’s and FGPA’s. Working with different embedded systems. Lowlevel code optimization using assembler instruction sets. Signal and radio processing.
Low-level development
Skills
Design PCB’s and electrical circuits.
Work with analogue and digital (SDR) RF components.
Signal processing using DSP’s
Using FPGA’s to design simple logic.
Handle communication between hardware components.
Work with a wide range of different SOC’s and Embedded Systems.
Code optimization using different Assembler Instruction Sets.
Documenting hardware systems in SysML and according to ISO standards.
Tools and frameworks
Cmake
Make
Conan
Boost
FreeRTOS
MQX
embOS
RiotOS
Embedded Linux Library
Networking
Develop and manage firmware for networking equipment. Lowlevel and highlevel Linux OS development. Cloud computing.
Networking
Skills:
Advise you what networking equipment to buy and how to configure this.
Develop, expand or tune existing firmware of networking equipment.
Low-level and high level OS knowledge of Linux operating system internals, components, APIs, and design.
Experience with kernel-level debugging processes and tools, across multiple distros and kernel versions.
Build middleware applications that provide services for user authentication, VPN, WiFi management, routing and fire walling.
Deploy and manage Linux virtual machines and handle communication between them.
Setting up and managing local or hybrid cloud solutions.
Cloud Computing:
Azure Data Factory
Azure Synapse Analytics
Azure Stream Analytics
CosmosDB
Azure Virtual Machines
Azure Kubernetes
Azure MS SQL
Azure DevOps
Powershell
Azure IoT Hub
Azure Monitor
Azure Functions
Azure Networking Stack*
Azure Active Directory
Azure Key Vault
AWS Networking Stack*
AWS S3
AWS CodeBuild
AWS Athena
AWS Data Pipeline
AWS Glue
AWS Redshift
AWS Lambda
AWS IAM
AWS EBS
Scripting languages
Bash
Powershell
Tools and Frameworks
.NET Core 5
Boost.Asio
Asio Standalone
VM Ware
Virtual Box
QEMU
Security
Setting up and testing network security. Cracking and patching firmware. Finding wireless communication vulnerabilities using SDR hardware.
Security
Networking
OpenSSL
SSO
CORS
OWASP Pen Testing
Auditd
Firmware
Binary Cracking and Byte Patching
Reverse Engineering using Ghidra
Wireless
Sniffing
Replay
Signal deception
Signal Hijacking and Denial of Service
Data Science
Analyzing small or large amounts of data and discovering new insights and strategies. Making future predictions using time series analysis on existing data. Training and creating (deep) neural networks that can detect implementation specific patterns.
Data Analytics
Skills:
Preparing and Analyzing data with tools like NumPy and Pandas.
Working with unstructured, structured and streaming data.
Tuning hyperparameters of models to achieve higher score during evaluation process.
Dimensionality reductions of feature vectors and finding feature set using clustering methods like Mini Batch and Mean Shift.
Describing Qualitative and Quantitative Data.
Numerical Measures of Central Tendency and Variability.
Detecting outliers with Box Plots and Z-scores.
Bivariate Relationships.
Events, Sample Spaces and Conditional Probability.
Binomial Random Variables, Binominal Probabilities Normality, Sampling Distributions.
Inferential Statistics and Hypothesis Testing (ex. Population variance, median, etc.).
Nonparametric Test on two or more populations.
Sample size estimation and optimization.
Using Probabilistic Models and machine learning models
Models:
K-Means
KNN Clustering
Suport Vector Machines
Decision Trees
Linear/Logistic Regression
Time Series
Autoregression (AR)
Moving Average (MA)
Autoregressive Moving Average (ARMA)
Autoregressive Integrated Moving Average (ARIMA)
Seasonal Autoregressive Integrated Moving-Average (SARIMA)
Seasonal Autoregressive Integrated Moving-Average with Exogenous Regressors (SARIMAX)
XGBoost
Long short-term memory (LSTM)
QLearning
Supervised Learning
Transfer Learning
Deep Learning
Tools:
Tableau
SAS (Basic and Advanced)
Power BI (+ DAX)
Google Data Studio
Pandas
Matplotlib
Seaborn
Google Charts
Chart.js
Computing
Designing, wiring and testing computer clusters. Multi-process programming with tools like OpenMP. Writing and optimizing algorithms on the CPU and GPU.
Computing
Skills:
Using high performance computing frameworks to optimize algorithms in parallel applications in OpenMP
Design simple or complex computer clusters and run calculations on them.
Creating 3D simulations in OpenGL and DX11.
Computational physics simulations in OpenCL.
Mathematical fields:
Linear Algebra
Computational Number Theory
Emurative Combinatorics
Topological Combinatorics
Partition Theory
Graph Theory
Statistics
Cryptography
Complex Numbers
Tools:
CUDA
OpenMP
OpenCL
Recommendations

Rosali Steenkamer

Marcel Merkx

Niek Geijtenbeek

Thijmen Koelewijn

Willem Jan Wagenaar

Gerhold ten Voorde

Frank Tamer

Pieter van Leeuwen Boomkamp

Bram Hendriks

Mustafa Kemal Akıllıoğlu

Jeroen de Bel

Marvin da Cruz Laranjeira Fernandes

Pasoon Popal
