Sean Wade

Machine Learning Engineer

• Built recommender sytems and predictive models to imporve guest experience
• Used big data and real time processing tools like Hadoop, Spark, NiFi, and Kafka
• Built real time dashboards and visualizations to explore complex ML systems

Computer Vision / Machine Learning Engineer

• Used drone imaging to construct 3D models of buildings and homes
• Created novel algorithms to segment 3D models, detect damage, and identify roof features
• Applied and scaled machine leaning research to industry

Research Intern

• Researched within Lidar and active optical systems
• Created pipeline to process massive multidimensional point clouds
• Implemented and analyzed many clustering and machine learning techniques

Software Engineer

• Developed mathematical models to highly improve eye tracking algorithms
• Optimized embedded computer vision algorithms with over 10x speedup

GPA: 3.8

Reinforcement Learning

Currently researching the combination of control theory and reinforcement learning. In addition looking at choosing decision policies over adaptive temporal horizons.

Healthcare

Researched machine learning techniques for survival analysis, disease prediction, and cost analysis in healthcare. Applied new methods for training gradient boosted trees and recurrent neural networks to large healthcare datasets. Also developed high dimensional disease embeddings based on the field of natural language processing.

• Forward Thinking: Building and Training Neural Networks One Layer at a Time
• Code2Vec: Embedding and Clustering Medical Diagnosis Data

Graph Theory

Explored graph symmetries and automorphisms. This is used to model the redundancies and patterns of large scale networks, allowing for both forecasting and separation of dynamical systems.