Student Showcase - Aberdeen Data Meetup 01 Oct 2024

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 talks in no particular order are:

1. Developing a Multilingual Legal Advisory Chatbot (MLAC) Using Retrieval-Augmented Generation (RAG) for Criminal Law in England, Wales, Scotland, and Northern Ireland (A PROOF OF CONCEPT) - Adebowale Odufuwa

This topic explores the development of an MLAC using RAG to provide criminal law guidance across the UK’s jurisdictions. Leveraging large language models and natural language processing, the chatbot aims to improve accessibility, streamline legal processes, and deliver legal information in multiple languages.

Adebowale Odufuwa is a seasoned sales and customer service professional with extensive experience in the Telecoms, Banking, and Manufacturing sectors. Currently transitioning into Data Analytics and Business Intelligence, he is proficient in Python, Tableau, Power BI, and SQL, with a strong foundation in data governance and machine learning. Adebowale is currently a Data Engagement Analyst with Aberdeen Cyrenians an appointment he got just halfway through his studies at RGU. With over two decades of leadership experience, he has a proven track record of driving significant business growth and fostering innovation across diverse industries.

2. "School Uniforms- Upcharge and Poverty" - Hritaban Roy

How we developed a service that offers generic alternative to branded school uniforms for schools across the UK. Exorbitant upcharge on branded clothing across the UK affects economically disadvantaged households. Collecting and consolidating UK data. Challenges with data collection, scalability and natural language processing.

Roy is a Bachelors student and a CS demonstrator at the University of Aberdeen. As an undergraduate researcher, he worked on a range of projects including developing a large-scale web application. His work involved using cutting-edge tools like NextJS, PostgreSQL, and Natural Language Toolkit to process vast datasets efficiently. His passion lies at the intersection of technology and data science, and he is particularly interested in leveraging his skills to solve real-world problems in fields like FinTech and computational modelling.

3. Solar Potential of a Building using Detectron2. - Suman Deb

This was a Computer Vision -based project to estimate the amount of energy a household can generate by installing solar panels.

Suman is a Software developer with a Master's in AI from University of Aberdeen and 5 years of experience in designing, building, and deploying ML models and algorithms, as well as automating processes using RPA. His experience includes extensive data-prepossessing, organizing large datasets, algorithm selection, model training, hyper-parameter tuning, and collaborating with cross-functional teams to integrate AI/ML solutions into applications.

4. Seeing Beneath the Surface - Applying Computer Vision in Subsea Decommissioning - Jared Scott The global increase in oil and gas decommissioning projects has highlighted the real shortfalls of past data recording at the time of installation. This project explored applying computer vision to identify unrecorded infrastructure and minimise the quantity of manual effort required to support decommissioning projects.

Jared studied BSc (Hons) Cyber Security at RGU and part of this course was ML for Cyber Security which got him really interested in the data warehousing and the ML aspect of cyber security, which led to his undertaking an MSc in Data Science. During his studies, he completed summer placements as a cyber security training programme coordinator and is now working as a Graduate Cyber Security Analyst.

5. Currency Fluctuations and International Postgraduate Student Enrolment in Scottish Universities - Ugochi Ugbomeh

This study uses data analysis and machine learning to explore how changes in currency exchange rates affect the number of international students enrolling in postgraduate programs at Scottish universities. The goal is to help universities understand these trends and improve their recruitment strategies. The inspiration for the study stemmed from a significant postgraduate dropout rate in Ugochi's cohort, which prompted her to investigate the impact of currency markets on enrolment.

Ugochi holds an MSc in Information Technology from the University of Glasgow (2011) and an MSc in Data Science from Robert Gordon University (2024), where she focused on the impact of currency fluctuations on international student enrolment. Her data science interest developed while working as a Junior Resource Planner & Real Time Analyst, where she managed data and created real-time performance dashboards. She is currently a Business Intelligence & Operations Lead, developing custom ERP systems that incorporate machine learning and data analytics.

6. Applying Computer Vision in Space research - Riddhi Nilesh Gujarathi

Applying computer vision in space research using YOLO (You Only Look Once) involves leveraging its real-time object detection capabilities to analyze images and videos from space missions. YOLO can be used to: Satellite Image Analysis: YOLO can detect and classify objects like spacecraft, debris, and celestial bodies in satellite images, helping with space object identification and debris tracking.

Riddhi recently graduated with a degree in Artificial Intelligence and Data Science and has experience working on various projects related to machine learning. She is also actively involved in communities like Microsoft Learn Student Ambassadors and Women Techmakers, where she contributes to technology education and mentorship. She is currently at UoA pursuing MS Artificial Intelligence.

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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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