Welcome to my website. I am a tech enthusiast, theoretical physicist, and software engineer.
About Me
Latest Projects
SCI4ALL - Decentralized Research on the Ethereum blockchain
A decentralized application (Dapp) for science research on the Ethereum blockchain. Developed for ETHWaterloo with Truffle, Solidity, Node, Web3.js, and Ganache.
New
SCI4ALL is an initial proof of concept dapp which associates an Ethereum address with each research project to be funded. Scientists submit grant proposals and stake holders vote for their preferred choice. The blockchain-based system improves crediting and funding among researchers. Imagine a world where scientists can collaborate, and trust is given without limitations.
Ms.Robot Fashion Modelling - Training a Variational Autoenconder with Fashion MNIST dataset
Trained a variational autoenconder (VAE) using TensorFlow.js on Node on the Fashion MNIST dataset. Data compression algorithm with functions where user defines the parameters. Created a generative model which means it can be used to generate new fashion pieces for Ms.Robot by scanning the latent plane, sampling the latent points at regular intervals, to generate new fashion pieces for each point.
Results show that the generative model with parameters of a probability distribution (VAE) is capable of achieving results on a highly challenging dataset of over 60,000 fashion set images using machine learning.
Yeezy Taught Me Text Generation - Train Next Character Prediction using Long Short Term Memory Model (LSTM)
Developed a web application for AI model training and text generation. Trained LSTM model to generate text based on patterns in a given text corpus. Yeezy's Model makes probability predictions of the character that follows the input sequence. Process is repeated in order to generate a character sequence of a given length hence the "text generation" part of the project.
Input file takes input text data. Model saved in IndexedDB database. User inputs Yeezy's model parameters to train model: [model layer size, number of epochs, examples per epoch, batch size, validation split, or learning rate].
Stochastic SoundCloud : Lucy’s New Mozart Mixtape. Machine Learning Generative Music using RNN LSTMs.
Music is an art with a temporal and hierarchical structure. The determined musical state is partially determined by the preceding musical state where the concrete musical state n+2 follows after the state n+1 only.
Music generation with three novel recurrent neural networks (basic, lookback, and attention RNNs) using Magenta from Google's Tensorflow AI. Using a RNN LSTM model ~10 stochastically generated "output.mid" music files are composed and can be opened up on Mac's Garageband.
En Français Si Vous Plait? French-English Natural Language Processing (NLP)
Vision of connecting people through language and advancing a barrier free society for billingual speakers. As a Canadian citizen, ensure respect for English and French as the offical languages of Canada and have equality of status, rights, and privileges.
French-English translations using PyTorch’s Transformer model and paper implementation of "Attention is All You Need”. Led the development of the machine language translation transformer model uses encoder-decoder attention mechanisms in a sequence-to-sequence model. "On the WMT 2014 English-to-French translation task, model establishes a BLEU score of 41.8 after training for 3.5 days on eight GPUs, a small fraction of the training costs of the best models from the literature"
Salty Wet Man - Not Suitable for Work (NSFW) Image Classification using VGG16 Neural Network
Developed a Not Suitable for Work image classification using Keras and Tensorflow.js trained on ImageNet dataset. Defining NSFW material is subjective and the task of identifying these images is non-trivial. Salty-Wet-Man identifies images into two categories: [SFW] positively trained for neutral images that are safe for work [NSFW] negatively trained for pornographic images involving sexually explicit images.
VGG16 CNN for large-scale image recognition model implementation achieves 92.7% top-5 test accuracy on ImageNet. NSFW Object Recognition functionalities include Content-Based Retrival via Localization, Image Detection, and Segmentation, and Image Region Proposal Cropping.
Other Projects
Amazon Developer as Low Apps In Skill Purchasing
Published developer with multiple Amazon Alexa applications on the Alexa Skills Store. Low Apps integrated with Voice User Interface (VUI) and In-Skill Purchasing (ISP). ISP allows developers to enrich in-skill experiences, drive deeper customer engagements.
Juypter Notebook: Data Analysis of Udacity Student Engagements
Data Analysis with Python and Jupyter Notebook on Udacity Student Engagement data with CSV data cleansing on files enrollments.csv, daily_engagement.csv, project_submissions.csv. Correlations between Udacity project completion rates and the following factors: minutes engaged, lessons completed, and days visiting the classroom.
Hack Princeton - Microsoft Word + Audio Parsing Free
Developed a Node.JS application using the Word Javascript API for Hack Princeton. User records audio from their browser and the data is automatically parsed into Microsoft Word using the JS add-on.
Juypter Notebook: Data Analysis of New York Subway and Weather Data. Working with 2D data with numpy and pandas.
Data Analysis with Python and Jupyter Notebook on New York Subway and Weather Data. Compared NYC subway map to find high ridership numbers in clusters from longitude from - 73.95 to -74.03 and latitude from 40.70 to 40.79.
B00m-h3adsh0t! - Neural Network Aimbot for FPS games with Custom Training Mode ︻デ═一 Free
Developed a Neural Network Aimbot for FPS games with custom training mode written in C++ providing a fast and efficient framework with scripting support. Includes customizable predictions and dynamic speed settings. Recognizes game objects in a certain range, then aims at the objects using game physics by hooking into the FPS game engine to use game data to auto-aim without altering gaming files.
Juypter Notebook: Gapminder Data Analysis
Data Analysis with Python and Jupyter Notebook on Gapminder data with information on employment rates (%), life expectancy (years), GDP/capita (US$ and inflation adjusted), primary school completion (% of boys), or primary school completion (% of girls) data collection.
Course Credits
- Computational Physics
- Computer Science 1 & 2
- Data Structures & Algorithms
- Geometrical & Physical Optics
- Mathematical Physics
- Differential Equations
- Multi-Variable Calculus