SAMUEL WINBONO-MPAABA

Dynamic Data Science Researcher with a proven track record at the University of Witwatersrand, proficient in Python and advanced statistical analysis to identify critical predictors in health data. Expertise in creating interactive visualizations and optimizing machine learning models enhances the ability to deliver impactful insights in biomedical research. Strong collaboration and problem-solving skills contribute to driving innovative solutions within interdisciplinary teams.

• Reinforcement Learning for Decision-Making, Implemented Deep Q-Network (DQN) and Successive Representation Agents to optimize decision-making in simulated environments., Benjamin Rosman
• Computer Vision for Image Classification, Developed deep learning models (CNNs) using TensorFlow and PyTorch for image classification tasks., Richard Klein
• Brain Tumors Classification with Convolutional Neural Networks, Developed and trained a CNN model to classify brain tumors from medical images., Clint Van Alten
• Chess Agent to Play Against Opposing Agents, Designed a reinforcement learning-based chess agent to compete with various AI models., Steven James
• Photo cartoonization using Generative Adversarial Networks, Built a GAN model to transform real-world images into artistic cartoon representations., Hairong Bau
• Training a Perceptron on a Binary Task Using the MNIST Dataset, Implemented and trained a perceptron model to classify handwritten digits., Annik Yalnizyan-Carson

• Investigating the Potential of Heart Rate Variability as a Potential Biomarker for Dementia, 05/24, Poster presentation at the Wits Innovation Day
• Feasibility of Leveraging Consumer Wearable Devices with Data Platform Integration for Patient Vitals Monitoring in Low-Resource Settings., 05/23, Published in Hindawi International Journal of Telemedicine and Applications
• Training the Perceptron For Binary Classification Using the Mnist Dataset, 05/23, Presented research at IBRO-Simons Computational Neuroscience Imbizo (ISICNI)
• Detection of Brain Tumors Using Deep Learning, 05/23, Presented research at IBRO-Simons Computational Neuroscience Imbizo (ISICNI)
• Orthopedic Wearable Device with Infrared Light to Stimulate Bone Healing, 05/21, Published a YouTube presentation video for the Virtual Internship in Biomedical Engineering.

• Deep Learning Indaba Conference, Dakar, Senegal, 05/24
• Deep Learning IndabaX Conference, Johannesburg, South Africa, 05/24
• Deep Learning Indaba Conference, Accra, Ghana, 05/23
• ISMRM African Chapter Workshop, Accra, Ghana, 05/23
• IBRO-Simons Computational Neuroscience Imbizo (ISICNI), Cape Town, South Africa, 05/23

• Deep Learning Indaba, Workshop Organiser, 05/24, Organized a workshop on NeuroAI.
• Breast Screening Outreach, BME Team Aid, 05/23, Assisted with vital signs measurements.
• Qatar Charity Pediatric Cardiological Interventional Surgery, BME Team Aid, 05/23, Coordinated all medical equipment requirements for the project.

Deep Learning 2024 | September 2024

IBRO-Simons Computational Neuroscience Imbizo | May 2023

Basic Life Support (BLS) | February 2023

Python, Kaggle | July 2022

Intro to Machine Learning, Kaggle | July 2022

Virtual Internship in Biomedical Engineering | July 2021

National Web Development Training Program | September 2020

Google DeepMind Scholarship at the University of the Witwatersrand | 2023