CEE 696-003: Deep Learning in Civil and Environmental Engineering and Earth Science

Spring Semester 2023

Final student presentation will be on May 12 2:15 - 4:15 PM following the UH Final schedule.

Students are required to submit their final project slides by 9:00 AM 05/12/2023.

Colab/Jupyter notebook submission for reproducible results is encouraged. All the slides/notebooks will be uploaded here.

Spring 2023 student final projects:

Presenter	Title (click to view slides)
Mostafa Abdelhafeez	Estimating Earthquake Magnitude Using Seismic Data: Exploring Seismic Patterns and Properties
Mohamed Sherif	Damage Classification and Severity Prediction of Buildings due to natural hazards from Aerial Images Using Deep Learning
Shiva Azimi	VDT: Vehicle Detection and Tracking
Ahmadreza Azizzadeh	Traffic Prediction Using GNNs
Wachiranon Chuenchart	Application of Deep Learning in Anaerobic Co-digestion
Miles Drazkowski	Generation of Modified Cam-Clay Soil Parameters Using Neural Networks and Testing Data
Muzammil Khan	Comparative study of shallow and deep neural networks for the prediction of biochar yield
Seyed Majed Noorbakhsh Saleh	A Deep Learning Approach to Forecasting 100-Year Return Period Wave Heights along the US Coastline
Jiawei Shen	Latent diffusion model for channelized reservior characterization
Xiazhi Zhang	Deep Learning-based Travel Mode Detection using GPS Data

Fall 2021 student final projects:

Presenter	Title (click to view slides)
Jichao Bao	Coupling Ensemble Smoother and Variational Autoencoder for Data Assimilation in Channelized Aquifers
Jonathan Chapman	Estimating Atmospheric Instability over the Ocean Using Satellite Data
Po-Cheng Chen	The forecast on U.S. birth rates
Nasrin Eini	Prediction of scour depth around circular single bridge piers
Cristian Flores	Leukemia Image Classification
Bailey Hopkins	Astronomical Tracking Methods
Azadeh Hosseinpanahi	Prediction of Concrete Compressive Strength Using Convolutional Neural Networks
Jianxin Huang	Concrete Crack Identification Using Neural Networks
Helaeh Khoshkam	Forecast of daily reference evapotranspiration using the long short-term memory (LSTM) model
David Luis	Performance of Novel CNNs in Hyperspectral Image Classification
John Maurer	DJ VAEder: Variational Autoencoder using MIDI music loops
Minh Nguyen	Modeling firm performance with linear regression and deep neural networks
Saroj Pathak	Different Temperature Prediction Models for Asphalt Concrete Pavement
Philip Patton	Identifying individual humpback whales from fluke photos
Sarah Popenhagen	Using Deep Learning for Acoustic Rocket Ignition Detection
Thi Trang Tran	A deep learning approach for spatiotemporal imputation of MODIS normalized difference vegetation index (NDVI)
Yiwei Wang	Forecasting Traffic Flow based on Speed Feature using Long-Short Term Memory (LSTM)
Wanxin Yu	Neural network recognizes traffic signs
Robert Lopaka Lee	Lava detection in webcam imagery from Kilauea Volcano

Fall 2020 student final projects:

Presenter	Title (click to view slides)
Abdulrahman Alghamdi	Traffic Signal Recognition
Amr Ghanem	Detection of Concrete crack size using deep learning [notebook]
Harrison Togia	Nearshore Interpolation of Hawaiian Ocean Measures via Neural Network Assessment of Statewide Remote Sensing Data
Jaeho Choi	NDPTC 360 – Detecting Face Mask Use and Social Distancing Compliance in Waikiki
Janet Chan	Crack Detection Using Deep Learning
Jeanalyn Wadsack-Myers	ECG Classification of Normal and Irregular Heartbeats [notebook]
Jonathan Tobin	Deep learning for acoustic UAV detection
Joshua Dyogi	Model Construction of Beam Elements to Analyze Deflective Behavior
Michael Ito	Inverting Solar Spectropolarimetric Observations with Deep Learning
Sushil Khadka	Prediction of temperature in a pavement profile using neural network model
Theodore Uekawa	Predicting wastewater parameters using a neural network trained off synthetically derived data from a generative adversarial network

Fall 2019 student final projects:

Presenter	Title
Ahmed Afifi	Forecasting reference evapotranspiration (ETo) using Recurrent Neural Network (RNN) Long Short Term Memory (LSTM) [notebook]
Brytne Okuhata	Predicting hydraulic head levels with machine learning
Christopher Shuler	Investigation of deep neural networks for filling gaps in hydrologic datasets
Jinwen Xu	Transfer learning using MobileNet for rainbow image recognition [notebook]
Joana Rose Castillo	Forecasting Evapotranspiration with RNN-LSTM [notebook]
Kei Manabe	Detection of calls of Minke whales using deep learning [notebook]
Lauren Ward	Using Deep Learning to determine fault locking depths of earthquakes
Madeline McKenna	Using neural networks to identify polar jet blocking in atmospheric reanalysis data
Runze Yuan	Vehicle detection based on UAV video and Transfer Learning
Samuel Kei Takazawa	Explosion detection with noise [notebook]
Terrence J. Corrigan	Case Study Hurricane Harvey: How Neural Networks can help in forcasting rapid intensification in tropical cyclones [notebook]
Trista McKenzie	Using deep learning to understand drivers and dynamics of submarine groundwater discharge off the Kona Coast
Xi Song	Deep Learning solution for strength prediction of steel CHS X-joints
Xiaole Han	Crack detection on stabilized soil samples [notebook]
Young-Ho Seo	Upscaling hydraulic conductivity using CNN [notebook]