o

m Panchal

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Player Stats

About Player

Name:

Om Panchal

Based:

London

Email:

oapanchal@gmail.com

Log:

Currently in the second year of University, I have a strong interest in Mathematics and Computer Science, particularly in the ML/DL space with experience using modern libraries such as Tensorflow and Keras as well as creating my own projects/models from scratch. My experience in creating web apps using nextJS and tailwindcss has made this website possible and for it to take on its unique theme. I hope you like it :).

Profiles:

GithubLinkedin

Power Ups

Machine Gun:

Massively increased fire rate. The strongest power up in the game.

Triple Shot:

Fires three bullets in a spread instead of one.

Rampage:

Ship destroys asteroids on contact instead of taking damage.

Invincibility:

Asteroids pass through the ship without dealing damage.

[Info]:

Power-ups spawn on screen at random whenever you break the smallest asteroid. Fly into one to pick it up and activate its effect.

Education

‣ University of Warwick [Coventry]

Computer Science Meng
[Triple Shot +2 sec]
First Year Average - 72.6% [First Class]

‣ St Dominic's Sixth Form College [Harrow on the Hill]

Mathematics, Further Mathematics, Computer Science
[Triple Shot +3 sec]
A level Achieved: A*,A*,A*

‣ Bushey Meads School [Bushey]

Maths, L2 Further Maths, English, Science (triple), Spanish, Computer Science, DT
[Machine Gun +2 sec]
GCSEs Achieved (Respectively): 9,9,9,9,9,9,9,9,9,8

Experience

‣ Ace Badminton Club [Harrow]

Level 1 Badminton Coach
[Invincibility +3 sec]
Conducted one-on-one and group coaching sessions
Demonstrated shots to groups of 10 – 20 students

‣ A STAR TUTORS UK LTD [Kenton]

Mathematics Tutor
[Invincibility +4 sec]
Delivered GCSE Maths content to classes of 15
Invigilated and coordinated exams for 100+ students over 5 days
Provided tailored feedback on challenging questions

Projects

‣ Autodiff

Automatic differentiation library — Python & NumPy
[Machine Gun +4 sec]
Calculates partial derivatives of any multivariable function
Builds a binary tree representation of tensor operations via OOP
Dynamically generates functions by traversing the tree
Released open source on PyPI and GitHub

‣ AlexNet

Classic CNN architecture from Scratch using TensorFlow
[Rampage +3 sec]
Implemented the AlexNet architecture, trained on an ImageNet subset
Programmed a fast Local Response Normalisation using Depthwise Convolutions and Data Augmentation Layer

‣ Bren

Autodiff Powered Neural network library — Python
[Rampage +4 sec]
Released open source on PyPI and GitHub
Modeled on TensorFlow/Keras for accessibility
20+ core features: layers, metrics, custom components
Trained on MNIST to 90%+ accuracy
+ More Projects

Controls

W :

Thrust Forward

A/D :

Rotate Left/Right

Q :

Quit Game