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2d-box-dodger

This is an endless 2D mobile/computer game where the user will control a player to avoid all the obstacles.

3d-box-dodger

This is a short 3D mobile/computer game where the user will control a player to avoid all the obstacles. The project is developed through unity and music is produced by Red Garland Trio.

3d-models-and-lighting

Rendering using modern OpenGL; 3D Model Loader; Mouse control; Define Lights and Materials; Interactive Light Controls

breast-cancer-cell-detection

In the current Medical field, deciding a cancer cell is benign or malignant takes more than a day to complete. It requires medical workers to take a sample from the suspicious cancer cell; then lab workers need to perform cell culture for more than 24 hours before deciding whether the cell is cancerous or not. If the cell is malignant, every minute and every second count; thus for this project, we are planning to train a Convolutional Neural Network to classify the cell is invasive or non-invasive within seconds.

brick-shooter

deap-granger-causality-emotion-classification

The basic idea of old JRP idea is the calculation of the synchronization index which describes the generalized synchronization between two systems. Between VAR and granger Casualty, the VAR can be considered as a means of conducting causality tests, or more specifically Granger causality tests. The VAR model shows that one EEG channel has an influence on the other given channel; however Granger causality really implies a correlation between the current value of one variable and the past values of others, it does not mean changes in one variable cause changes in another.

deap-jrp-emotion-classification

Emotional Classification with the DEAP dataset using EEGLAB, matlab and python. Currently in the status of developing a more efficient and high accuracy method for emotion classification using EEG data regardless of number of channels.

ensemble-classifier-and-binary-classification

using random forest, Adaboot, gradient boosting, bagging with k-nearest neighbor and bagging with decision tree to test on five different datasets for the overall best ensemble classification method

eradication-game

Created by David D. and Haoqi W. Some detailed blog descriptions could be found: https://digitalfinalproject.home.blog/ by David OBJ file parsing, cubic mapping, trackball, shadow mapping, bezier curve, fragment shader and vertex, and procedural modeling. https://cse167finalp.blogspot.com/ by Haoqi and David Procedural Modeled City, Shadow Mapping, Sound effect and Particle Effect.

flow

Fight disorder and distractions online with Flow

go_projects

Learning Go Practices

machine-translation-with-ibm-model

neuropy-python3.0

I updated NeuroPy to Python version 3.*. NeuroPy library written in python to connect, interact and get data from neurosky's MindWave headset. This library is based on https://pypi.org/project/NeuroPy/

neurosky-lightswitch

The goal of this project is to use the focus and meditation level calculated through EEG to turn or off a light bulb. The implementation used NeuroPy and NeuroSky.

pneumonia-covid19-classification

pytorch-chatbot

I explored a couple different ways to implement a chatbot. I have tried with seq-2-seq neural network, I have used prebuilt RAASA models and so forth.

radix

A simple radix tree implement by Golang

rendering-point-clouds

Read 3D Points from Files; Display the Points; Fit the Model to the Screen

rman-cohesity

roller-coaster

Sky Box; Sphere with Environment Mapping; Track; Control Handles; Bezier curves

sequence-tagging-hmm

skiplist

A SkipList data structure implement in Go

tech_challenge_2019

This application is created to aid LEAD program members, BPM, and AL in the rotation selection process. The goal is to move away from the traditional excel sheets and build an AWS web application to reduce the time spending on selections; thus further improves the efficiency.

text-arousal-and-valence-classification

Two binary classifications regarding the input text data. The first classification is detecting the text’s valence level. Valence can be interpreted as the subject’s pleasant or unpleasant experience regarding the aspect or the topic of the text. If the text is positive in valence, that means the user who inputs the text is having a positive or pleasant attitude towards the subject matter; on the other hand, if the text is negative in valence, this means that the user is displeased or annoyed by the material. The other classification is regarding the arousal level. Arousal means the intensity of the stimulus to the subject. Positive arousal means that the subject matter might boost more adrenaline or higher blood pressure; negative arousal can be interpreted as tired, calm or other similar emotions. In all, using these two classifications, we can do a multi-class classification. We improved from the traditional binary emotion classification to the better quaternary emotion classification.

text-classification-nlp

Semi supervised and supervised NLP classification

textures-scene-graphs-and-culling

Textured Robot Torso; Scene Graph Engine; Walking Android Robot; Robot Army; Culling

trc-nmp-design

This repository contains the 3 teams OpenRocket simulation and design and an estimate design for the ideal optimized rocket design based on the material provided.

trigram-nlp-model