Student Showcase - Aberdeen Data Meetup 03 Oct 2023

Welcome to our annual Student Showcase where postgrad students from RGU and University of Aberdeen showcase their projects from their Data Science and other Masters degrees.

We should have around 6 students each talking for 10 minutes on their project from 6.30 pm. Networking with pizza and drinks start at 6pm.

The following speakers (in no particular order) have confirmed so far:

Kathryn Caizley

Finding Patterns in Ecological Data

An investigation into the spatial and temporal patterns of: i) phytoplankton biomass in the northern North Sea using chlorophyll-a as a proxy indicator; and ii) the net primary production – the difference between the amount of carbon captured by the phytoplankton during photosynthesis and the amount of carbon emitted during respiration.  Bio: Aspiring Data Scientist with a desire to work in environmental protection

Ikechukwu Dike

Estimating Deprivation Indices and Obesity Prevalence with Grocery Shopping Data: A Rapid Approach

A study to develop and validate a rapid estimation methodology that utilizes streamlined grocery shopping data to infer deprivation indices and child obesity prevalence within an area.

Bio: Experienced analytics professional, a passionate Data Science enthusiast and MSc graduate, bringing data-driven insights to life

Nana Aisha Mahmood

*Compassionate Recovery: Transforming Lives through the Heal Together website. *

Heal Together recognises the destructive effects of addiction on families, including trust erosion, emotional turmoil, financial strain, and child neglect. Our mission centers on compassionate recovery, merging recovery and empathy to inspire action and alleviate suffering. The website underwent a transformation using AI tools and a collaborative approach, resulting in a safe space for individuals and families facing addiction.

Bio: MSc Global health and management student, passionate about psychology and people centred work.

Steven Wallace

Histogram-Based Gradient Boosting Transfer Learning for Underwater Image Quality Assessment

No reference underwater image quality assessment (IQA) is a challenging problem under development that predicts an output regression quality score for each input image. Deep learning algorithms trained on benchmark datasets such as ImageNet and fine-tuned on IQA datasets are a way to develop transfer learning systems that can improve the overall performance of existing methods. The Histogram-Based Gradient Boosting algorithm was used to improve the overall performance of IQA transformer-based deep neural networks and one metric-based algorithm for underwater IQA. The transfer learning system design improved the overall Spearman Rank Correlation Coefficient (SRCC) over existing methods on the UID2021 dataset of underwater images.

Bio: Steven was an MSc AI student at the University of Aberdeen who completed his final MSc Project thesis on deep learning for Underwater Image Quality Assessment (UIQA). In October 2023, he will commence his PhD in computer vision with multimodal data to analyse climate change at the University of Aberdeen.

Chioma Adeomi

A snapshot analysis of the data governance job market in the United Kingdom

Data governance has become increasingly critical to the success of organisations that utilise data. The study examines the data governance job market in the United Kingdom, using LinkedIn job postings to identify key trends, the common job titles and analyse the most frequent terms

Bio: MSc Business Analytics "soon to be" graduate and aspiring data governance professional seeking to help organisations establish data governance standards that drive organisational efficiency

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This event is orgnanised by a charity - Code The City. We are grateful to ScotlandIS for their generous sponsorship of the Aberdeen Data Meet-ups from June 2023 onwards.

CTC suggests a small donation to help with charity admin costs, but if this is a barrier please just change the ticket price to what you can afford.

We're now back to running physical events (with an online option via Zoom).

If you select a physical ticket and it happens that we can not meet physically you will have to attend the Zoom session. If you choose a physical ticket and it goes ahead you will have to comply with any conditions of attendance (eg masks or social distancing) that the venue operators demand at the time.

Those attending the physical space meetup should attend at 6pm for pizza and drinks. The talk will be from 6.30pm. Doors will be locked from 6.30pm.

**If tickets are sold out please do not attend as you will be refused entry without a ticket. **

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