Dillon Hicks Email & Phone Number

Bridgeport, West Virginia, US

Moffett Field, California, US

• Implemented machine learning models with Keras, Tensorflow, and XGBoost along with Optuna hyperparameter optimization for multiple regression of a synthetic dataset of over one million samples.
• Employed data visualization tools including Matplotlib, Seaborn, Plotly, and Pandas to illustrate the performance of trained regression machine learning models, demonstrating their feasibility with Jupyter Notebook.
• Designed and implemented ETL workflows using Xarray, Dask, and GeoPandas to process GeoJSON andNetCDF data, helping manage restrictions of real-world airspace based on flight conditions.
• Managed a SQLite database to store airspace information and created queries to update it from a separate REST API.
• Independently developed a C# Unity environment and Python backend utilizing NumPy and WebSockets,deployed using Docker and AWS EC2 with S3 to simulate dense air spaces of UAVs.
• Developed an automated Python testing suite to unit test simulation parameters and ensure proper initialization of the simulation environment.

• Spearheaded data science projects as a Research Lead, collaborating with a team of researchers to utilize cloud computing and deep learning with geospatial imagery for remote sensing and conservation of mangroves.
• Experimented with state-of-the-art deep-learning segmentation algorithms such as DeeplabV3 with PyTorch to segment aerial imagery.
• Developed a classification and visualization dashboard using Dash, Plotly, and Xarray, incorporating Scikit-learn for automated data acquisition and classification to track long-term trends in mangrove extent.
• Applied tree-based ensemble models and feature engineering techniques with LightGBM and Random Forest to classify satellite imagery, deploying on AWS Sagemaker.
• Developed a CNN-MLP hybrid deep-learning image classification network with TensorFlow and Keras to detect mangrove areas using geospatial imagery data fusion, achieving an accuracy of 95%.
• Produced machine learning reference datasets for mangrove remote sensing applications, leveraging NumPy and Dask to format labels and imagery in HDF5 format.

La Jolla, CA, US

• Created curriculum and instructed students for an undergraduate course on subjects including introductions to Python, OpenCV, and Laser Cutting
• Assisted students with group class projects involving machine learning, computer vision, and mechanical design

Waltham, MA, US

• Implemented and tested RNN and Transformer-based classifiers such as BERT in Tensorflow and Keras with NLTK to classify incoming IT emails using fastText embeddings. The final LSTM model was deployed on AWS Lambda.
• Created an NLP Sentiment Analysis tool using Scikit-learn and Word2Vec embeddings to classify the sentiment of over 1000 internal social media posts daily, inserting the sentiment into a PostgreSQL server for proactive.

La Jolla, CA, US

• Implemented a Convolutional Neural Network utilizing the InceptionV3 architecture to classify mangrove UAV imagery to achieve 93% accuracy
• Implemented SVM and K-means baselines for mangrove image classification and clustering using Scikit-learn
• Utilized ArcGIS and Agisoft Metashape to generate imagery from raw drone images for Deep Learning tasks

Master Of Science - Ms, Machine Learning And Data Science

Bachelor Of Science - Bs, Electrical Engineering: Machine Learning And Controls