Daniel Huang's Portfolio

Hi, I am Daniel!

I am a passionate impacts engineer and past leader of several student orgranizations and award-winning projects. I graduated from King's College London with a degree in Computer Science with AI in 2021 and I am currently a grad school student and NLP student researcher at Santa Clara University. I am eager to join your company and make a difference.

What I Can Offer

Areas of Focus

What I Can Offer

Big Data

I have experience in using data framework such as Hadoop and Apache Spark and a sophisticated understanding in SQL and NoSQL databases.

Full-stack Development

I have internship experience in developing the front-end and back-end of websites.
I also have certified experience in Cloud solution development, such as AWS and GCP.

Machine Learning and AI

I frequently explore and develop ML & AI applications.
I am particularly skilled in Natural Languages Processing
along with some experience in Computer Vision, Reinforcement Learning, Brain-Computer Interface and Autonomous Driving Systems.

Moonshot ideas

From re-purposing CO2 emission by converting CO2 waste to solar cells materials, to innovating the idea of food freshness stickers at the MIT Entrepreneurship Bootcamp,
my ability to create moonshot ideas built up the foundations of my impact engineering career

Portfolio

Projects

BCI Application: EEG-ECoG Forward Solutions

A variety of Deep Learning methods (LSTM, Convolutional Autoencoders, EEG-Net) that provides ways to translate EEG brain signal to ECoG in the medical research field

BeatsLandmark

Your personal soundtrack director tailor to every occasion/event.

Secure AI-Blockchain Syndromic Surveillance Network

An advanced syndromic surveillance system that incorporated Blockchain for data collection and machine learning for asymptomatic COVID-19 infection estimation.

Spark-based Provenance Kernel

A higher-performance machine learning graph analytics tool that classifies patterns or strategies within a system using data concept "Provenance" - a technology that tracks the process of how a piece of data is originated or influenced by other elements.