Software Engineer from Nottingham Trent University, graduated in 2022. Passionate about computer science, software and embedded hardware development. Currently working in the GIS Industry as a Software Developer at Spatial Days LTD. Prior Experience in the world of Computer Vision, AI/ML, Embedded microelectronics, IoT, robotics, FPGAs and much more.

Big interest in the world of AI and Machine Learning, with applied knowledge in Computer Vision and Image Processing. Experience with specialized Computer Vision equipment, such as the Intel RealSense D435i, Oak-D and many other devices including various other cameras, sensors and actuators. Experience with various AI/ML frameworks and libraries such as Tensorflow, Pytorch, Keras, OpenCV and Scikit-learn

Familiar with the world of cloud computing with the use of various products from AWS, Azure and Google Cloud. Products used include AWS EC2, AWS S3, AWS RDS, AWS App Runner, Azure Gateway, Azure Blob Storage, Azure App Service, Google Cloud Functions, Google Cloud Storage and Google Cloud Run.

Simple IoT storage project working inside Docker Container or standalone. Saving data to sqlite3 database file. Used to store sensor information from GSM/WiFi IoT Devices

Simple people visit counter created for counting library visits in Technical School Slavonski Brod, Croatia. Using Arduino to detect the walk-ins and Flask application to store, process and display data.

Community interaction Management system for Nottinghamshire Police use. Used for managing police-hosted events with community representatives, tracking Management frequency and officer efficiency.

Paper which characterizes the power consumption of heterogeneous devices when performing AI inference on a example of the consumption profile and analysis of the NVIDIA Jetson Nano board while performing object classification.

https://arxiv.org/abs/2207.06150v1

Fruit detection and counting using Xilinx Zynq MPSoC and Vitis-AI. The project utilises capturing a dataset for the training of the neural network, labeling the dataset, training the YOLOv3 CNN on GPU and finally accelerating it using Xilinx Vitis-AI Toolchain. Part of a Field Companion project undertaken while working at Sundance Multiprocessor Technology Ltd.

https://www.hackster.io/sundance-ai/fruit-detection-using-mpsocs-cc0e80

Power profiling of a custom application on Sundance VCS-1 PC/104 Board accompanied with ZU4EV MPSoC module. The example shows a matrix multiplication app running both on the ZU4EV and the ARM Cortex-A9 core of the VCS-1, proceeding to evaluate the power consumption of both.

https://github.com/SundanceMultiprocessor
Technology/XOHWC-SundanceVCS1-Power-Profiling