Nice to meet you! I am Oluwabukola Grace, a child of God with a passion for technology and making positive impact.

My name is Oluwabukola (Grace) Adegboro, a Ph.D. student at Dublin City University, and an alumni of Ontario Tech University, AIMS Rwanda (AMMI), and Elizade University. My research interest lies in the area of Machine Learning, Computer Vision and AI. I have been opportuned to learn and gain well-rounded experiences in the field of Machine Learning (ML) using supervised, unsupervised and deep learning algorithms. I am passionate about developing ML solutions to solve challenging problems, promote user satisfaction, and drive innovation and impact.

News

2024 Highlight

• Excited to participate in the Black Googler Network (BGN) Hackathon at Google Ireland in October 2024.
• Pleased to co-organize Deep Learning Indaba under the Travel Committee in September 2024.
• Happy to have our second IMVIP paper, "XAI-ResUNet: Analysing the Impact of Pre-training in ResUNet Architectures for Multiple Sclerosis Lesion Segmentation using EigenGradCAM" receive the Best Poster Award.
• Excited to present our paper, "XAIMed-Net: Towards Explainable Brain Tumour Detection in 2D T1-Weighted CE-MRI Images using Transfer Learning" at IMVIP conference in August 2024.
• Grateful to attend the 1st African Computer Vision Summer School in July 2024. (ACVSS).
• Delighted to attend CVPR conference in June 2024.
• Ecstatic to co-organize the 2024 ML-Labs summer school, hosted at Dublin City University in May 2024.
• Elated to be selected as a finalist for the 2023 DCU Tell it Straight Competition.
• Thrilled to participate in the UCC AI Quest Challenge with a wonderful team, and also awarded as the Top Woman of Influence in February 2024.



2023 Highlight

• Grateful to be awarded the Cadence Women in Technology Ireland scholarship .
• Joyful to start my Ph.D. program at Dublin City University in September and awarded a scholarship via the ML-Labs program.
• Happy to co-organize the Computer Vision For Africa (CV4Africa) workshop at the 2023 Deep Learning Indaba.
• Excited to co-organize the 2023 Deep Learning Indaba under the Accessibility, Safety and Inclusion (ASI) team.
• Glad to share that our paper, "Incremental Learning-Based Algorithm for Anomaly Detection Using Computed Tomography Data" was published in July 2023.
• Delighted to co-organize the 1st (Member-led) Black in AI social at CVPR conference in June 2023.
• Ecstatic to join the 2023 cohort of the AI4Good lab in May as an ML trainee .
• Excited to share that I have graduated from Ontario Tech University.



2022 Highlight

• Glad to present at the 2022 (CNS DIET) conference.
• Happy to give a poster presentation and volunteer for the computer vision workshop held during the 2022 Deep Learning Indaba.
• Joyful to be awarded the Google Travel and Conference Grant in 2022.
• Grateful to partake in the IBM Future Women in Tech Mentorship pilot program offered in collaboration with AHF.
• Elated to participate in a Machine Learning (ML) course offered by Vector Institute.
• Excited to engage in the Accelerate Her Future (AHF) 2022 Fellowship Circle, a career accelerator for black, indigenous, and women of colour in business and STEM.



2021 Highlight

• Glad to provide support to WiML participants as a volunteer at the ICML 2021 and NeurIPS 2021 workshops.
• Thrilled to participate in a 12-week Google CS research mentorship program (CSRMP).
• Pleased to be awarded the Deans Graduate Scholarship at Ontario Tech University.
• Delighted to join the Smart Energy Systems Lab (SESL) at Ontario Tech University as a Graduate Research Assistant / Masters student.



2020 Highlight

• Hurray! Presented a poster at the WiML NeurIPS 2020 workshop.
• Engaged as a volunteer at the Women in Machine Learning (WiML) NeurIPS 2020 workshop, and highlighted some interesting sessions on Twitter.
• Pleased to engage in the Machine Learning Summer School (MLSS 2020). See video :)
• Glad to give a presentation at the Women in AI Ignite social at ICML conference in 2020.
• Happy to be involved as a volunteer at the following virtual conferences; ICML 2020 and WiML UnWorkshop 2020.
• Volunteered to test run the CVPR 2020 virtual website to promote smooth running of the event.
• Excited to partake in the ICLR 2020 virtual conference as an attendee and volunteer.



2019 Highlight

• Excited to be awarded a fully-funded masters scholarship funded by Google & Meta, via the AMMI program.

Portfolio

Understanding the Amazon Forest from Satellite Imagery

The goal is to devise machine learning methods for understanding deforestation trends in the Amazon from satellite imagery.

Instance Segmentation on a custom dataset with Mask RCNN

Instance segmentation was carried out on a nuts custom dataset that was trained on an object detection library (Detectron2).

Object Tracking System

A simple object tracking system detects objects on all video frames on predictions from a detectron model and links these predictions across time frames.

Development of an Image Classification System with Deep Learning

An image classifier which recognizes a wide range of flower species is developed using PyTorch deep learning framework.

Predicting potential donors for CharityML using Supervised ML

A machine learning model is built and optimized to predict the highest donation yield which would help the organization to contact more potential donors using donation letters.

Identifying Customer Segments using Unsupervised ML

Potential customers within a population segment that are more likely to increase the company's revenue are identified using unsupervised machine learning methods.

• Full Portfolio

Invited Talks / Presentations

• Thrilled to present our paper titled, "XAIMed-Net: towards explainable brain tumour detection in 2D T1-weighted CE-MRI images using transfer learning" at IMVIP conference in August 2024.
• Happy to present at the 2022 Canada Nuclear Society Disruptive Innovative Emerging Technologies (CNS DIET) conference on "Incremental Learning for Anomaly Detection Applied to Computed Tomography Scans".
• Elated to present a poster at the 2022 Deep Learning Indaba on "Incremental Learning Based Anomaly Detection For Computed Tomography (CT)."
• Pleased to give a poster presentation at the WiML NeurIPS 2020 workshop on "Understanding the Amazon Forest Using Satellite Imagery."
• Excited to present at the Women in AI Ignite ICML social 2020 program on "Machine Learning in Deforestation."