Hi, I'm Aldrich Fernandes

Artificial Intelligence Student @ King's College London (KCL)

About Me

I am a 3rd year student studying Artificial Intelligence BSc at King's College London. I've explored diverse areas of computer science from artificial intelligence and robotics to game development in Python and Java.

Personal Projects

Mortgage Application Risk Classifier

Developed a machine learning model utilizing logistic regression and neural network concepts to evaluate and predict the risk strength of mortgage applications.

Skills: Python, Machine Learning, Neural Networks, Data Structures, Git

GitHub

Classic Game Clones: Chess & Pong

Engineered fully playable clones of classic arcade and board games, implementing core game logic, state management, and rendering.

Skills: Python, Pygame, Object-Oriented Programming (OOP), Game Development

GitHub

Situational Music Recommender

Built a containerized, microservice-based application that generates personalized music recommendations by analyzing image context and processing LLM conversations.

Skills: Docker, Docker Compose, FastAPI, Python, MongoDB, Git, CI/CD, Pytest, RabbitMQ, SSL

GitHub

Academic Projects

ROS Object Recognition & Retrieval Robot

Designed a robot using YOLOv4 for object detection, room classification, and voice-controlled item retrieval.

Skills: ROS noetic, Python, Computer Vision, YOLOv4, Voice Control, State Machines, Gazebo

Super Lario (JavaFX Platformer)

Created a 2D platformer game using JavaFX withing a collaborative environment with 3 other developers.

Skills: Java, JavaFX, Team Collaboration, Game Development, Git


Education

King's College London | 2024 - 2028

BSc Artificial Intelligence

Key Modules (to name a few):

  • Cloud Computing for Artifical Intelligence
  • Web and Internet Systems
  • Machine Learning
  • Introduction to Robotics
  • Introduction to Professional Practice
  • Logic and Knowledge Represenation
  • Mathematics and Statistics for Artifical Intelligence

St Ignatius College | 2017 - 2024

A-levels: A*, A, A (Maths, Further Maths, Computer Science)
GCSEs: 9 subjects with average grade of 8.2

Experience

King's Undergraduate Research Fellow (KURF) | King's College London

Duration: June 1, 2026 - July 5, 2026

Completed an undergraduate research fellowship under Dr. Matteo Leonetti on "Robots for Healthy Ageing: Engineering Socially Assistive AI." Focused on agile development for the PAL Robotics TIAGo platform, physical deployment validation, and international research presentation.

  • Developed autonomous HRI (Human-Robot Interaction) behaviors:
    • Programmed guest-seating behaviors utilizing computer vision to dynamically identify available seating.
    • Implemented gesture-controlled bag handover and placement using real-time body keypoint detection.
    • Developed a robust person-following algorithm equipped with autonomous recovery behaviors.
  • Physically deployed and tested the team's simulation-based GPSR algorithm for RoboCup 2026, building the task state machine and integrating essential codebase skills.
  • Contributed to migrating the open-source codebase from EOL ROS Noetic to LTS ROS Humble, resolving complex dependency updates and documenting syntax changes.
  • Showcased research outputs and competed at RoboCup 2026 in Incheon, presenting findings to international robotics teams.

Skills: ROS2 (Humble), Python, Human-Robot Interaction (HRI), Computer Vision, State Machines (YASMIN), Agile Development, Empirical Research, PAL TIAGo API

Learning Autonomous Service Robots (LASR) | Sensible Robots Research Lab @ KCL

Duration: October 2025 - Present

Core member of the competitive robotics team representing King's College London internationally at RoboCup@Home.

  • Helped system architecture migration from ROS 1 (Noetic) to ROS 2 (Humble), modernizing the entire codebase ahead of RoboCup 2026 in Incheon, South Korea.
  • Engineered the comprehensive HRI "Receptionist" task software, seamlessly chaining bag-carrying, person-following, and guest-seating subsystems.
  • Assisted in the deployment testing and expansion of a natural-language-to-task-planning pipeline to automate executable command parsing for the GPSR task.
  • Co-presented the lab's peer-reviewed research poster to international robotics teams and industry experts.
  • Onboarded and mentored new student members on codebase standards, version control, and ROS.

Skills: ROS (Noetic / Humble), Python, YASMIN (State Machines), Task Planning, Robot Manipulation, Gazebo Simulation, Linux (Ubuntu), Git & Agile, Mentoring