Chris Winsor

Machine Learning, Industrial IoT, Machine Vision, Robotics

I am a software developer focused on Industrial IoT, machine vision, robotics and machine learning. My toolset includes PyTorch, Torch Geometric, transfer learning, pretrained models, Colab, Django and Precise Automation robotics.

I like to keep on top of the latest ML techniques and “kick the tires” through proof-of-concept experiments. I’m always looking for projects like the ones below so free to reach out!

Chris  (

Graph Neural Network using PyG (Pytorch Geometric) In this project we model topic evolution on social media using a Twitter dataset of Covid-19 tweets. We use PyTorch Geometric, Sequence Encoder, HeteroConv and a BERT language model.

Whole-image Classification using Kiras/Tensorflow: This is a self-driving car that (in realtime) classifies images from a front-mounted camera.  It is an end-to-end CNN deployed to Raspberry Pi.

StarChaser: This is a web-app to demonstrate Machine Learning integrated into an every-day Website/app.  It uses Django, Postgres and a little JavaScript.  PresentationGame 

Markov Logic Network is a new and exciting technique for modeling systems that have structure but are inherently probabilistic.

Kaggle PLAsTiCC: A survey of approaches for classification of an aperiodic timeseries dataset from Kaggle.

Tri-Training: Use unlabeled data for supervised learning! The paper is from an Amazon researcher in Cambridge MA and was used for wake-word detection but the approach can be applied anywhere.

The Bootstrap: A principled technique to establish statistical significance to test results. Combined with T-tests this is important to have in the tool belt.

Machine Learning

Industrial Internet-of-Things (IIOT)

Probabilistic Graphical Models

Speech Recognition and Synthesis

Machine Vision