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Hello, I'm Newton Kelvin Ollengo 👋

👨‍💻 About Me:

I am a highly skilled Electronics Engineer with over 4 years of experience in developing complex electronic systems and specialized knowledge in medical imaging techniques for Image Guided Therapy. My expertise spans across designing and implementing electronic systems, robust project management, and leading teams in agile environments.

- 🌱 Currently mastering various medical imaging techniques in Image Guided Therapy.
- 🛠️ Skilled in PCB design, microcontroller programming, and signal processing.
- 💼 Electronics Engineer at SurgeonsLab AG in Bern, Switzerland.

🛠 Technologies and Tools:

C++ logo Python logo R logo Matlab logo OpenCV logo

📊 My Stats:

GitHub Streak Stats

📝 Publications:

  • 2022: Water Level and Quality Monitoring System Using Message Queueing and Telemetry Transport System; Nairobi, Kenya.
  • 2022: Same as above presented at IndabaX, Malawi.

🎓 Education:

- 📖 Master of Science in Biomedical Engineering, University of Bern – Specializing in Image-Guided Therapy.
- 🎓 Bachelor of Education in Technology (Electrical and Electronic Engineering), First Class Honors, Dedan Kimathi University of Technology, Kenya.

Kellino's Projects

biobert icon biobert

BioBERT: a pre-trained biomedical language representation model

business_card_pcb icon business_card_pcb

A personal Business Card designed as a PCB. Supports NFC to share data wirelessly on a tap.

dsa-2017 icon dsa-2017

Workshop during Data Science Africe 2017

face-mask-detection-1 icon face-mask-detection-1

Face Mask Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras

iot-practice icon iot-practice

This is a training repository, that is made for guys to practice various IoT projects and using Github Effectively

iotc-device-bridge icon iotc-device-bridge

Sample source code for enabling IoT Central integration with other IoT platforms

lstm-human-activity-recognition icon lstm-human-activity-recognition

Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier

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