MSc Project Showcase Rescheduled - North East Data Meetup, October 2022

The Aberdeen Data Meet-up is back!

The season begins with a MSc Student Showcase: six 10-minute presentations from students in the 2021-2022 MSc Data Science Cohort at local universities speaking to us about their summer project.

Expect a mix of industry and academia, technical and business people coming together to network, listen to informative talks, share news, and discuss collaborations.

This is a hybrid event, and we welcome in-person attendees to join us from 6pm for pizza, drinks, and networking. Online attendees can join from 6.15pm, with presentations starting at 6.30pm.

If you wish to attend online, please book a place AND email info@codethecity.org to confirm and a link will be sent to you.

1. Sree Raghav Duvvuri - Facial Emotion Recognition With Augmented Dataset and Evaluation

This project deals aims to build a neural network for facial emotion recognition to classify an image into one of the seven emotions (angry, fear, happy, neutral, sad, disgust and surprise) and evaluate its performance with respect to a fully trained ResNet50 model and another model, which is a RessNet50 model, in which, only the first 101 layers are trained and the rest use weights from imagenet.

Bio: Sree is a student pursuing MSc in Artificial Intelligence at the University of Aberdeen, eager to break into the industry.

2. Ali Hasan - Assessment of Scottish Open Data Policies & Implementation - A Data User Perspective

Ali's talk will provide an overview of the open data movement in Scotland and highlight improvement areas in policy and implementation. The underlining argument is that data users must be the focus when policies are devised and implemented since it is they who derive socio-economic value from open data.

Ali is pursuing an MSc Business Analytics at RGU, and is interested in socio-economic value of open data and all things open in general.

3. Rahul Baburajan: A Creative Writing Collaborative Tool using Large Language Models.

The project attempts to model a conditional language generation model using GPT-Neo that can generate text in the writing style of Robert Burns, Violet Jacobs and Mary Seacole. We compare the results obtained by the conditional model to their separate individually trained models and find that while the conditional model is a more challenging task, it has its benefits in collaborative writing specifically in the case of out-of-context generation.

Rahul is an MSc Artificial Intelligence student at the University of Aberdeen.

4. Michael McCall - Development of Social Media Clustering Algorithms for Capita

The project aims to design a social media text clustering algorithm for Capita to integrate into their wider Social Media and Research Toolkit (SMART). This would allow for faster analysis of incoming social media posts, event detection, and trend analysis. Much of the project focuses on natural language processing, taking social media posts and transforming them into a format suitable for machine learning.

Michael is an MSc Business Analytics student from RGU with a love for all things data – fascinated by its uses from sports to tackling the climate crisis.

5. Chathura Perera - Bridging the gaps in People analytics

Lessons learned as a placement as a People Data Analyst in an oil and gas company based in Aberdeen. How and why do we calculate human resources metrics. Creating and implementing a staff attrition prediction model. Calculating the number of people that will be required to staff vessels in the company for the next year. The latter part will focus on the BI tools (PowerBi) and language libraries in (R programming) I used to achieve these results.

Chathura has been a professional data analyst with 6+ years of experience in various domains such as finance, healthcare and human resources analytics. He has just completed his masters at RGU, studying MSC Data Science.

6. Neha Raj - Outliers in GP's referral data within NHS Grampian
   This project aims to create a tool that will identify the general pattern in GP referrals and detect any anomalies in the pattern every month. The tool has been developed in R programming languages and incorporates Artificial Intelligence. It is a cost-effective, easy way to monitor and evaluate referrals while reducing human effort and hence the human error
   Neha has more than a decade of experience in information management,
   Project planning and management and extensive experience in the content management system. She has recently completed an MSc in Health Data Science with distinction from the University of Aberdeen.

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Please note our policy for reducing the spread of infectious diseases.

The Aberdeen Meet-ups are hosted by Code The City and are supported by The Data Lab, Scotland IS and Opportunity North East.

Photo by Brook Cagle on Unsplash