We are a private consultancy, however here are some of our areas of expertise:

Machine Learning

  • Model and Evaluation - Cross validation with model training and testing.
  • Supervised learning - Decision trees, support vector machines (SVM), and regression.
  • Unsupervised learning - clustering and principal component analysis (PCA) 
  • Reinforcement learning - markov decision processes (MDP) and game theory
  • Deep Learning - neural networks, logistic classifiers, and multi layer convolution neural networks including filters, stride, and pooling (Keras with Theano or TensorFlow).
  • Transfer Learning - utilizing pre-trained networks to solve problems.


  • Computer vision - Classifications using support vector machines (SVMs), decision trees, histogram of gradients (HOG) and deep neural networks (DNNs).
  • Sensor fusion - Applying Kalman filters, extended Kalman filters, and unscented Kalman filters to combine lidar and radar data together.
  • Localization - Markov localization using a bayesian filter, egomotion, and using a particle filter.
  • Control - core algorithms of linear quadratic regulators and classic closed-loop control (PID).

Mechanics and Electronics

  • Simulations - Computational Fluid Dynmaics (CFD), Finite Element Analysis (FEA), and Thermal Analysis.
  • PCB design and component programming - EagleCAD, SPICE, etc.
  • Rapid Prototyping - SLS, SLA, Scanning, etc.
  • Digital manufacturing and design (DM&D) - based on the Digital Manufacturing Commons (DMC) at opendmc.org and Model-Based Systems Engineering (MBSE)


Languages - C++, Python, Go

Frameworks - ROS, Keras (AI prototyping), TensorFlow, Caffe2, MXnet, Theano, CNTK, Deeplearning4j, Chainer, etc.

Simulations - Siemens NX, Catia, Turtlesim, PR2, etc.

Computer vision - OpenCV including use of Point Cloud Library (PCL) and Random Sample Consensus (RANSAC) packages.

Hardware - custom FPGA system development in VHDL or Verilog (System) using Quartus Prime