Zuzana Fernandes

Passionate Junior Developer in the final year of my Interdiciplinary BASc Degree. I am passionate about creating positive impact through the intersection of technology and other industries, especially Ai/ML.
I am working for a Tech start-up in healthcare and in my spare time enjoy bouldering. My soft skills such as project coordination have been developed through various part-time jobs. Fluent in Slovak and proficient in French. :)

Bachelor Of Arts and Sciences

The London Interdiciplinary School | Sept 21 - Jun 24

Specialised in Data Science. During my interdisciplinary degree, I homed in on my problem solving and collaboration skills while being a proud captain of our football team. During my 2nd year, I carried out an independent research project on language learning and AI, developing a chrome extension as a final product. For my dissertation, I am researching the effectiveness of LLMs to simplify hospital terminology.

Theoretical Physics

King's College London | Sept 19 - May 20

Finished the first year with a 1st, gaining a Certificate of Higher Education, before deicing to switch paths. Acquired skills in problem solving, fundamental computational mathematics and statistics.

Junior Developer

RemixReal, Remote

Sept 23 - Ongoing

  • Working for a U.S.-based tech start-up, actively incubating a new project.
  • Gaining experience in tools such as Azure DevOps, Git, and Linux. Prgramming mainly in Python and Typescript.
  • Following SOLID principles and peer-programming.


Software Developer Intern

TenWest, London/UK

Jun 23 - Sept 23

  • I was involved in researching and developing proof-of-concept features for an emerging AI-powered tech stack.
  • I utilised LangChain to build multi-agent systems. Leveraged Hugging Face diffusion models for video generation.
  • Key Achievement: Designed and implemented file management systems tailored for vector store databases.


Project Support Officer

London Borough of Tower Hamlets, London/UK

Jun 22 - Sept 22

  • I worked on a recycling project, focusing on collecting and analyzing data on food waste.
  • I created a live map to facilitate easy data collection in the field.
  • Key Achievement: Improved project co-ordination by establishing effective communication with building project developers .


Youth Worker

Unitas Youth Zone, London/UK

May 19 - July 21

  • I led and executed weekly programming for groups of diverse youth, ages 8-19, in areas such as sports, art, music, and cooking.
  • I was constantly adapting sessions on the fly to accommodate for varying attendance and participant needs, including those with special education needs and disabilities (SEND).


Skills

Pyhton

Javascript

Html | Css

Secondary Coding Languages

Typescript | SQL

LangChain

NumPy | Pandas

Git

Django

Overview

This is a google chrome extension I made to faciliate langauge learning through YouTube videos. I am working to expand this project (hence no link to repository).

Features

  • Video Identification: This chrome extension identifies which video you are watching and extracts metadata.
  • Language Insights: Presented using easy to read bars and gradients, insights are provided about the video.

Technologies used


  • Text-to-Video Creator Using HuggingFace and GPT-4
  • Github

Overview

This project creates videos with audio seamlessly by integrating a text-to-video diffusion model with OpenAI's GPT-4. It is designed to produce captivating videos from textual descriptions, beginning with the creation of detailed briefs and culminating in the generation of multiple videos which are stringed together by moviepy complete with an audio background.

Features

  • Customisable Video Creation: Allows for the creation of personalised videos based on user-inputted text briefs.
  • Audio Integration: Supports adding an audio track to the generated video.
  • Google Colab Compatibility: Designed to run efficiently on Google Colab with extra RAM.
  • Hugging Face open source model: Utilizes a diffusion model to transform text descriptions into engaging video content.

Technologies used


  • Emotional Diary Streamlit App
  • Github

Overview

Reflect is an experimental application built using Streamlit, aimed at helping users maintain an emotional diary. It asks users questions about their current emotional state. Then by using an AI chatbot to pose interactive questions, they receive emotional insights at the end.

Features

  • Interactive AI Chatbot: Utilising OpenAI API, the bot engages users with thought-provoking questions.
  • User-Friendly Interface: Built on Streamlit, the app offers an intuitive and easy-to-navigate user experience.
  • Confidentiality and Privacy: Users must provide their own API Key, ensuring user responses are kept private.

Technologies used

Get in Touch

Address

Central London, UK

Email

zuzana.fernandes@yahoo.co.uk

Phone

Email for more