I'm an Assistant Professor of Electrical Engineering at Louisiana Tech University in Ruston, Louisiana.
I graduated from Embry-Riddle Aeronautical University, Daytona Beach, Florida Campus with a Ph.D. in Electrical Engineering and Computer Science at Dec. 2021 and a M.S. in Electrical Engineering at Dec. 2017. I was advised by Dr. Shuo Pang.
My research involves Robotics, Autonomous Systems, and AI. I focus on developing intelligent decision-making models to navigate/control robots using AI methods.
I'm interested in topics related to the AI and robotics integration, including Computer Vision, Deep Learning, Large Language Models, Reinforcement Learning, Robot Learning, and Tranfer Learning.
My current and past research projects include the following:
AI-based Robotic Odor Source Localization
2018 - Current, Principal Investigator Latech, ERAU
This project leverages various AI techniques to design a navigation model to guide a robot in finding a hidden odor source location with onboard vision and olfaction sensors.
Wildfire Early Detection with Unmanned Aerial Vehicles
2021 - Current, Researcher LaTech, ERAU
The core of this project is to integrate Computer Vision and Robotic Olfaction to enable a robot (i.e., a drone) "see" and "smell" the environment to detect early wildfire locations.
Chemical Plume Tracing with Autonomous Underwater Vehicles
2018 - 2022, Research Assistant ERAU
This project focuses on developing navigation algorithms (i.e., chemical plume tracing algorithms) to control an autonomous underwater vehicle to discover hydrothermal vents within ocean environments.
This project was collaborated with Dr. Guangyu Xu at Applied Physics Laboratory of University of Washington.
Multi-Agent Collaboration and Robot Localization
2020 - 2022, Research Assistant ERAU
This project involves designing Multi-Agent Collaboration Algorithms for controlling a fleet of robots and Sensor Data Fusion Algorithms for Robot Localization.
2024
📝 12-10-2024: Our paper, entitled "Integrating Vision and Olfaction via Multi-Modal LLM for Robotic Odor Source Localization", is published on Sensors.
🔍 08-02-2024: Our project, entitled "Predicting New Thermoset Shape Memory Polymers via Transformers and Graphic Neural Networks", is selected to be funded by Louisiana LAMDA Seed Grant for 1 year $40K.
🎓 06-27-2024: My first Master student, Sunzid Hassan, successfully completed his thesis defense "Robotic Odor Source Localization using Vision and Olfaction Sensing". Congras!
🔍 06-21-2024: Our project, entitled "Deep Learning-Based Aerosol and Ocean Parameter Retrieval from Polarimeter and Lidar Data", is selected to be funded by Louisiana Space Grant Consortium for 1 year $70K.
📝 04-05-2024: Our paper, entitled "Robotic Odor Source Localization via Vision and Olfaction Fusion Navigation Algorithm", is published on Sensors.
📝 04-04-2024: Our paper, entitled "Deep Learning-based Wildfire Smoke Detection using Uncrewed Aircraft System Imagery", is accepted on IEEE UR 2024.
🔍 04-02-2024: Our project, entitled "Advancing Embodied AI for Enhanced Robotic Odor Source Localization", is selected to be funded by Louisiana Board of Regent for 3 years $108K.
🎤 01-12-2024: I give a research talk, entitled "Robotic Odor Source Localization via AI Methods", at the CAR Lab of University of Delaware. Thanks for Dr. Weisong Shi's hosting!
2023
📝 12-11-2023: Our two papers, entitled "Multi-modal Robotic Platform Development for Odor Source Localization" and "Robotic Odor Source Localization via End-to-End Recurrent Deep Reinforcement Learning", are accepted on IEEE IRC 2023 Conference.
📝 06-25-2023: Our paper, entitled "Vision and Olfactory-Based Wildfire Monitoring with Uncrewed Aircraft Systems", is accepted at the IEEE UR 2023.
📝 04-01-2023: Our paper, entitled "Learn to Trace Odors: Robotic Odor Source Localization via Deep Learning Methods with Real-world Experiments", is accepted at the IEEE SoutheastCon 2023.
📝 02-06-2023: Our paper, entitled "Autonomous Underwater Vehicle Based Chemical Plume Tracing via Deep Reinforcement Learning Methods", is published on Journal of Marine Science and Engineering.
2022
🎉 09-01-2022: I start a new position of Assistant Professor of Electrical Engineering at Louisiana Tech University.
Proposed a Hierachical Control framework to control a robot finding the odor source by coordinating obstacle avoidance, vision-based navigation, and olfaction-based navigation behaviors.
Integrated Twin Delayed Deep Deterministic Policy Gradient (TD3) with recurrent neural network (RNN) and implemented in the robotic odor source localization task.
Improved the traditional moth-inspired odor source localization algorithm with a fuzzy inference system to adaptively change search parameters and behaviors.
Designed a robot navigation algorithm for finding a hidden odor source. Two steps are involved: 1. Source & Plume Mapping (fuzzy inference) 2. Path Planning (RL).
Presented a new vision-based wildfire smoke detection from drone's imageries, which involves image segmentationa and object detection to reduce the false alarm rate.
Implemented Extended Kalman Filter and Unscented Kalman Filter to determine AUV locations based on IMU (acceleration), Doppler Velocity Log (velocity), and Short Baseline (position) measurements.
I'm teaching courses related to Control Theories, Artificial Intelligence, and Robotics.
I offer these courses per academic year:
ELEN 471: Automatic Control Systems
Every Fall Quarter 🍂 Electrical Engineering, LaTech
This course is an introduction to automatic control systems. You will learn (i) how to develop mathematic models, (ii) use various numerical methods to analysis control systems, and (iii) develop different controllers to control the system.
ELEN 472/572: Introduction to Digital Control Systems
Every Winter Quarter Electrical Engineering, LaTech
This course focuses on digital control systems. We will cover (i) digital signals, (ii) digital system modeling, (iii) digital control theories, and (iv) real-world examples of digital control systems.
Every Spring Quarter 🌱 Electrical Engineering & Computer Science, LaTech
This course is an introduction of AI, focusing on hands-on experience of various AI techniques. You will learn various AI techniques, covering the past 20-year AI developments. Each topic comes with a real-world example to demonstrate how to use AI techniques to solve real-world problems.
