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Hello there!

  • 🌱 I am currently working as a Technical Consultant at Daintta. Daintta specialises in cybersecurity, AI data intelligence, and communications security.
  • 🔭 In my spare time I like to build FOSS. I am currently working on the WYX-CLI project, a customisable CLI in bash enabling developers to easily automate daily workflows in the terminal.

Harry Wixley's Projects

ascii-art-generator icon ascii-art-generator

A python script to transform images into ASCII art in your terminal. Nick Cage DLC included.

bi-coursework-1 icon bi-coursework-1

Using DNA sequence alignment tools (ie. BLAST) to detect the existence of the GULO gene (used to biosynthesise vitamin-C) in varying different organisms.

bi-coursework2 icon bi-coursework2

Using DNA sequence alignment tools (ie. BLAST) to detect the relation between SFARI genes and Autism Spectrum Disorder (ASD).

chatgp-tea icon chatgp-tea

A CLI for talking to ChatGPT, saving conversation logs, and turning code blocks (language agnostic) from it's responses into executable shell commands.

drone-route-planner icon drone-route-planner

A drone air-quality mapping system. The drone's movement is constrained to moving in fixed increments, and only angles of 10. The system retrieves drone air-quality stations, and no-fly-zones as Geo-JSON objects from a webserver. The system then uses these to find an optimal route to pass through all the stations without going into any no-fly-zones

drphil-app icon drphil-app

iOS App for monitoring and sending commands/message to an autonomous door handle sanitisation robot

emnist-neuralnet-regularisation-experiments icon emnist-neuralnet-regularisation-experiments

A study of the problem of overfitting in deep neural networks, how it can be detected, and prevented using the EMNIST dataset. This was done by performing experiments with depth and width, dropout, L1 & L2 regularization, and Maxout networks.

fall-detection-app icon fall-detection-app

Commercial iOS fall detection app. Connects to a Polar H10 device for triaxial acceleromter and ECG signals. These signals are passed to a trained ResNet152 model using Tensorflow background processes for live inference.

fall-detection-data-collection-server icon fall-detection-data-collection-server

A localhost server to ensure secure and private data collection for fall detection data. This server uses IP-based whitelisting for security. This server streams ECG & Accelerometer data in chunks using a circular buffer to mitigate data loss.

fall-detection-dataset-generator icon fall-detection-dataset-generator

An iOS fall detection data collection system. It uses CoreMotion for retrieving accelerometer, magnetometer, and gyroscope sensors, and interfaces with a PolarH10 chest strap for ECG data using the Polar SDK.

fall-detection-deep-learning icon fall-detection-deep-learning

Preprocessing my fall detection dataset using data standardisation and sliding windows, and splitting this data into train/validation/test sets. Modelling performed on PyTorch using LSTM and CNN networks. The final models were exported to `.tflite` files to be run on a mobile phone. The best performing model was the ResNet152 with 92.8% AUC.

fnlp-coursework2 icon fnlp-coursework2

Supervised and semi-supervised training of Hidden Markov Models using the Viterbi algorithm

github-stats icon github-stats

An automated workflow for generating visualizations of my GitHub stats

iaml-cwk1 icon iaml-cwk1

Introductory Applied Machine Learning - Coursework 1: simple machine learning model development, and analysis using Sci-Kit Learn and Numpy

iaml-cwk2 icon iaml-cwk2

Introductory Applied Machine Learning - Coursework 2: development and analysis of machine learning models on the FashIonMNIST dataset using SciKit-learn

ilp-cwk1 icon ilp-cwk1

Informatics Large Practical - Coursework 1: Rendering air-quality maps by parsing air-quality geo-json data from a local webserver.

ilp-cwk2-report icon ilp-cwk2-report

Informatics Large Practical - Coursework 2 Report: Developing pathplanning software for a drone and mapping it's route on a map that avoids no-fly-zones parsed as Geo-JSON objects.

inf2b-coursework1 icon inf2b-coursework1

Task1 - data analysis & classification with multivariate Gaussian classifiers

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