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

Fall Semester 2021
  • Final student presentation will be on Dec 13 7:30 - 9:30 AM following the UH Final schedule. We will use the class zoom link.

  • Students are required to submit their final project slides by 7:30 AM 12/13/2021.

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

Fall 2021 student final project:

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




Previous Projects

Fall 2020 student final project:

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 project:

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]