Networked Autonomous Intelligent Learning (NAIL)

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Welecome to NAIL Lab! The lab’s goal is to develop resilient and sustainable intelligent networked autonomous systems capable of operating in highly dynamic, uncertain, and adversarial environments. The lab integrates expertise in machine learning, control and optimization, wireless communication, and human factors to design advanced algorithms and practical testbeds for cyber-physical systems, human-AI autonomy, and the Internet of Things (IoT).

• Vehicular Networked Control Systems
• Embodied AI
• Autonomous Robotic Systems
• Smart Manufacturing Automation
• Networked Power Systems and Smart Grids

Current Team Members

Dr. Bin Hu

PI & NAIL Lab Director

Ph.D. Students

Richie Ryulie Suganda

ECE (Spring 2024)

Learning-based Control & Optimization

Developing safe learning algorithms for layered autonomous systems and integrating large language models for intelligent robotic control applications

Shaharyar Ahmed Khan Tareen

ECE (Spring 2024)

Robust Embodied AI

Advancing robust AI perception systems for autonomous robotics with focus on computer vision and environmental adaptation capabilities

Benedictus Christo Geroda Cinun

ECE (Spring 2025)

Machine Learning & Robotics

Investigating safe reinforcement learning algorithms for quadruped robot locomotion and dynamic environment navigation systems

Immanuel Raynaldo Santjoko

ECE (Fall 2025)

Trustworthy Human-AI Collaboration

Building reliable and transparent AI systems for effective human-AI collaboration through trust mechanisms and explainable AI frameworks

Master Students

Tony Tran

Engineering Data Science (Fall 2024)

Efficient Tiny ML & Embedded AI

Edge computing, model compression, IoT systems

Undergraduate Students

AI-powered Drone Project

Team Project

LLM based Drone Navigation and Control

AI-powered Race Car Project

Team Project

Learning based Car Racing

Alumni

Previous Master Students

• Pooyan Ghodrati (2025, M.S. Engineering Data Science, RA funded by NASA at UH, now Data Scientist at Toyo Financial Group)
• Jahanvi Hitesh Dave (2023, M.S. Computer Science, RA funded by NSF at UH, now at Goldman Sachs)

Previous Undergraduate Students

• Victor Le (2025, AI-powered Drone Project at UH)
• Angel Gomez (2025, AI-powered Drone Project at UH)
• Hieu Le (2025, AI-powered Drone Project at UH)
• Nicolas Upshaw (2025, AI-powered Drone Project at UH)
• Yosef Abushaaban (2025, AI-powered Race Car Project at UH)
• Muhammad Ansari (2025, AI-powered Race Car Project at UH)
• Damian Castillo (2025, AI-powered Race Car Project at UH)
• Asaad Elsayed (2025, AI-powered Race Car Project at UH)
• Alejandro Zamarron (2025, AI-powered Race Car Project at UH)
• Javier Caudle (2024, Captone project-Advance Surveillance Drone at UH)
• Steven Comayagua (2024, Captone project-Advance Surveillance Drone at UH)
• Leandra Guzman (2024, Captone project-Advance Surveillance Drone at UH)
• Weijie Huang (2024, Captone project-Advance Surveillance Drone at UH)
• Edward Perez (2024, Captone project-Advance Surveillance Drone at UH)
• Kristof Siska (2019–2022, RA funded by NSF, now Master’s student at Old Dominion University)
• Jacob Michalick (2022, RA funded by DoD at ODU)
• Skye Taylor (2021, RA funded by NSF REU, now Master’s student at University of Virginia)
• Joshua Smith (2021, RA funded by NSF at ODU)
• Andrew Vecerkauskas (2020, RA funded by ONR at ODU)
• Jeremy Sklute (2020)
• Teresa Trinh (2019, RA funded by ONR at ODU)
• Zachariah Garvin (2019, RA funded by ONR at ODU)
• Thomas Sexton (2019, RA funded by ONR at ODU)
• Bryan Holland (2019, RA funded by ONR at ODU)
• Matthew Kersey (2019, RA funded by ONR at ODU)
• Victor Ortiz (2018)

Join Us

We are always looking for talented and motivated individuals passionate about cutting-edge research in intelligent and networked autonomous systems. If you’re interested, please contact Dr. Bin Hu for opportunities.

Acknowledgment

We gratefully acknowledge the support from our funding agencies, including the National Science Foundation (NSF), the National Aeronautics and Space Administration (NASA), and the Office of Naval Research (ONR), for enabling our research in intelligent and networked autonomous systems.