Computer science graduate in Manchester. I build mobile, embedded and AI projects: an app with 50K+ downloads, and a year at Thales.
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I worked on MMCM, a mine countermeasures programme for the French and Royal Navies — starting in SI&T, then moving into software engineering to test the system and fix defects.
Life of an intern
The same equipment behind every test procedure and defect above — the TSAM, deployed from the USVs pictured earlier.
"A genuine, obvious enthusiasm for working with computers and software is a real asset. Clearly someone who has built a reputation in a short time of being a reliable asset to the project."
- Line Manager
"I was really impressed with what you did with the app development and see that you could be (are) a really good software developer. I think that software development will be where your future in Thales belongs"
- Matrix Manager
"Friendly quick learner that quickly integrated and became one of the main points of contact for the SI&T team, building a wide network amongst interns, developers and graduates."
- Apprentice
"Faheem has fitted into the team and interfaced with other teams very well. I would be happy to work with Faheem in the future should the opportunity arise."
- A cool guy :)
A companion app for VALORANT I've built solo since 2021 — live matches, rank, store and loadouts, plus its own chat and widgets, for PC and console. 50K+ downloads across the Play Store and GitHub.
Free · Android · grab the latest APK straight from GitHub Releases.
Dynamic colour per account, drawn from your equipped player card.
Global chat, a "looking for game" board, profiles and friend requests.
Agents, ranks and party info the moment you load in, with a round-replay minimap.
Equip skins, sprays, cards and buddies, and save presets.
Your shop, friends and rank, right on your home screen.
Wishlist a skin, get alerted the second it hits your store.
Thousands of lineups by map and agent, with inline video.
PC, Xbox and PlayStation, with multi-account switching built in.
A look inside the app
My final-year BSc dissertation (85%). Most AI agents that "beat" Pac-Man just memorise one maze — this one tests whether an agent can handle mazes it's never seen, and whether how it learns changes the answer. I built the game and a Gymnasium environment from scratch, then trained DQN and NEAT under identical conditions and tested both on 100 unseen mazes.
Built from scratch in Python & Pygame · DQN trained on an RTX 4060, NEAT evaluated across six CPU worker processes.
Maze, pellets, power-ups and four ghosts — Python and Pygame, no pre-built RL environment.
A fresh maze every episode, BFS-validated so memorisation is impossible.
A Dueling DQN vs. a NEAT population evolving weights and topology — same 29-D environment.
No learning signal from scratch, so difficulty ramps across 8 stages, each gated by a rolling win rate.
Blinky chases, Pinky intercepts, Inky flanks and Clyde switches by distance — all via A* pathfinding.
CSV logging, fixed-seed benchmarks and Mann–Whitney U testing to compare both approaches honestly.
An offline Quran companion built with .NET MAUI — reader, AI verse search, prayer times, Qibla compass and verse scanner, on Android, iOS, macOS and Windows from one codebase.
Built with .NET MAUI · one codebase across Android, iOS, macOS and Windows.
Three Arabic scripts, three translations and eight reciters, all offline.
Search in plain English, ranked on-device with MiniLM embeddings.
Daily Salah schedule with a live countdown to the next prayer.
A live compass that points towards Mecca as you turn.
Point the camera at a page and jump straight to that ayah.
Bookmark any verse and jump back to it in context.
Four themes including OLED black, plus font size, script and reciter options.
One download on first launch, then it runs without a connection.
My screen's colours, mirrored on my smart bulbs in real time. A threaded Python script grabs screen regions, averages the colour and sets the lights over the local network.
It's been a side project for five years: it started as a weather-to-wallpaper script and grew into a full lighting rig with a screen mode, a weather mode and Discord control.
Grabbed with mss, fast enough to feel live.
Each region is reduced to a single RGB value.
Straight to the bulbs over my network, no cloud round-trip.
Capture never waits on the network, and it reconnects if a bulb drops.
Scrapes the weather and swaps my desktop wallpaper to match.
A bot that sets the bulb's power, colour and temperature from chat.
The Tuya bulbs follow the weather, or whatever is on screen.
RGB LEDs on PWM pins, driven by pyFirmata over serial.
Threaded capture with mss, local API and auto-reconnect.
I run a server with my mates, so I kept building bots for it — game stats, PC builds, quizzes and even my room lights.
VALORANT rank, live matches, agents, weapons and patch news, with stats as generated player cards.
-MMR-live-agent
Search parts, pull live Amazon and eBay prices, and assemble a build.
!cpu!ram!motherboard
A multi-language VALORANT encyclopedia with fuzzy search.
.search.version
CS and Maths questions, with answers scored by meaning.
.q.mafs
Player stats, with Discord accounts linked to in-game IDs.
!search!s
Power, colour and temperature of my room lights, from chat.
.lights red
My first big bot: moderation, mini-games, utilities and smart-home control.
.gif.kick
A selection of side projects across AI, hardware and the web.
Mostly played Minecraft and Need for Speed
Parrs Wood High School
9 GCSEs with English, Maths and Science
Xaverian College
Computer Science, Maths and Physics :')
Manchester Metropolitan University
First-Class BSc (Hons) Computer Science · 82%
Achieved 86%
Programming, Computer Architecture, Web Development, Mathematics, Databases
Achieved 80%
Networking, Data Structures and Algorithms, Operating Systems, Software Development,
Ethical Hacking
Worked at Thales as an IVVQ Engineer for my placement year!
Graduated with First-Class Honours (82%) 🎉
Project, Research Methods, Artificial Intelligence, Mobile Development
University of Manchester
Currently in the taught modules — diving into AI & machine learning
Open to roles, collaborations or just a conversation. Email is the quickest way to reach me, but I'm around on these too.
faheemsaleemsq@gmail.com
