Kendall Niles

As a computer scientist at the Geospatial Research Laboratory (GRL) with a distinguished track record of success at the US Army Engineer Research and Development Center, I possess a wide range of skills spanning project management, software development, sensor integration, contracting (COR), proposal writing, and customer development. I have a proven ability to develop and execute innovative strategies that reduce costs, enhance efficiency, and produce results in projects that involve sensor systems, robotics, additive manufacturing, civil works, and more.

• Operational Scenario-Driven DHS Mission-Based Model – Adversarial Model
• Forward Operating Base (FOB) Unmanned Aerial System (UAS) Detection and Defense Planning
• Monitoring for Analytes through LoRa and LoRaWAN Technology
• Dual-Stream Attention Transformers for Sewer Defect Classification
• Deep Learning Approach for Accurate Segmentation of Sand Boils in Levee Systems
• Encryption for Edge Computing Applications
• Towards Trustworthy AI: A Review of Ethical and Robust Large Language Models
• Widened Attention-Enhanced Atrous Convolutional Network for Efficient Embedded Vision Applications under Resource Constraints
• Application of Deep Learning for Segmenting Seepages in Levee Systems
• Leveraging artificial intelligence and machine learning (AI/ML) for levee culvert Inspections in USACE Flood Control Systems (FCS)

• Award for Outstanding Achievement in Student Outreach K-12 - ERDC AWARD - AUG 2024
• Civilian Service Achievement Medal - DOD ERDC AWARD - MAR 2022
• Individual Monetary Award - ERDC AWARD - NOV 2022