Lingxiao Wang

I'm an Assistant Professor of Electrical Engineering at Louisiana Tech University (LaTech) in Ruston, Louisiana.

I graduated from Embry-Riddle Aeronautical University (ERAU), Daytona Beach, Florida Campus with a Ph.D. in Electrical Engineering and Computer Science at Dec. 2021 and a M.S. in Electrical and Computer 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.

profile photo

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.

Sponsors
BOR Logo FUEL Logo LAMDA Logo LaSPACE Logo
NASA EPSCoR Logo DOTD Logo KEEN Logo COES Logo

2025

July 2025
  • 📄 07-03: Our Paper on polymer recovery stress prediction is accepted on Polymer
  • 🎤 07-14: We host a Robotic Summer Camp at LaTech in 2025.
  • June 2025

    🎤 06-02: I gave a Research Talk at the IEEE Shreveport Section for Robotic Odor Source Localization. Thanks to Dr. Prasanthi Sreekumari for hosting!

    April 2025
    March 2025
    February 2025
    • 🔍 02-28: Our Project on Workforce Development is selected to be funded by NSF FUEL. Thanks!
    • 📄 02-15: Our Two Papers were accepted on IEEE Southeastcon 2025.
    January 2025
    • 🔍 01-13: Our Project on robotic-based gas monitoring is selected to be funded by NSF FUEL. Thanks!
    • 📝 01-11: Our Paper on LLM-based Odor Source Localization is published on Robotics and Autonomous Systems.

    2024

    December 2024

    📝 12-10: Our Paper on Multi-Modal LLM for robotic Odor Source Localization is published on Sensors.

    August 2024

    🔍 08-02: Our Project on AI-based polymer prediction is selected to be funded by Louisiana LAMDA Seed Grant. Thanks!

    June 2024
  • 🎓 06-27: My first Master student, Sunzid Hassan, successfully completed his Master thesis defense. Congras!
  • 🔍 06-21: Our Project on AI-based satellite data retrieval is selected to be funded by Louisiana Space Grant Consortium. Thanks!
  • April 2024
  • 📝 04-05: Our Paper on odor source localization is published on Sensors.
  • 📝 04-04: Our Paper on wildfire smoke detection is accepted on IEEE UR 2024.
  • 🔍 04-02: Our Project on Embodied AI for odor source localization is selected to be funded by Louisiana Board of Regent. Thanks!
  • January 2024

    🎤 01-12: I give a research talk at the CAR Lab of University of Delaware. Thanks for Dr. Weisong Shi's hosting!

    2023

    December 2023

    📝 12-11: Our Two Papers are accepted on IEEE IRC 2023 Conference.

    June 2023

    📝 06-25: Our Paper on wildfire monitoring with drones is accepted at the IEEE UR 2023.

    April 2023

    📝 04-01: Our Paper on reinforcement learning-based odor source localization is accepted at the IEEE SoutheastCon 2023.

    Feburary 2023

    📝 02-06: Our Paper on chemical plume tracing is published on Journal of Marine Science and Engineering.

    2022

    September 2022

    🎉 09-01: I start a new position of Assistant Professor of Electrical Engineering at Louisiana Tech University.

    January 2022

    🎉 01-12: I start a new position of Visiting Assistant Professor of Electrical Engineering at Embry-Riddle Aeronautical University.

    2021

    December 2021

    🎓 12-30: I obtain my Ph.D. in Electrical Engineering and Computer Science from Embry-Riddle Aeronautical University.

    📂 AI-based Odor Source Localization

    A Knowledge-driven Framework for Robotic Odor Source Localization using Large Language Models
    Khan Raqib Mahmud, Lingxiao Wang, Sunzid Hassan, Zheng Zhang
    Robotics and Autonomous Systems, 2025

    We present a Knowledge-Driven framework to use large language models to process olfactory sensor data in odor source localization problems.

    PDF | Citation
    Integrating Vision and Olfaction via Multi-Modal LLM for Robotic Odor Source Localization
    Sunzid Hassan, Lingxiao Wang, Khan Raqib Mahmud
    Sensor, 2024

    Developed a multi-modal navigation system that employs an LLM to process both visual and olfactory sensor readings to find a hidden odor source.

    PDF | Project Page | Citation
    Robotic Odor Source Localization via Vision and Olfaction Fusion Navigation Algorithm
    Sunzid Hassan, Lingxiao Wang, Khan Raqib Mahmud
    Sensors, 2024

    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.

    PDF | Citation
    Multi-Modal Robotic Platfrom Development for Odor Source Localization
    Sunzid Hassan, Lingxiao Wang, Khan Raqib Mahmud
    IEEE International Conference on Robotic Computing (IRC), 2023

    Presented a robotic platform developed for the odor source localization task with both visual and olfactory detecting capabilities.

    PDF | Citation
    Robotic Odor Source Localization via End-to-End Recurrent Deep Reinforcement Learning
    Lingxiao Wang, Shuo Pang
    IEEE International Conference on Robotic Computing (IRC), 2023

    Integrated Twin Delayed Deep Deterministic Policy Gradient (TD3) with recurrent neural network (RNN) and implemented in the robotic odor source localization task.

    PDF | Citation
    Learn to Trace Odors: Robotic Odor Source Localization via Deep Learning Methods with Real-world Experiments
    Lingxiao Wang, Ziyu Yin, Shuo Pang
    IEEE SoutheastCon, 2023

    Designed a Deep Learning model for End-to-End control of a mobile robot in finding the odor source location.

    PDF | Citation
    Robotic Odor Source Localization via Adaptive Bio-inpsired Navigation using Fuzzy Inference Methods
    Lingxiao Wang, Shuo Pang
    Robotics and Autonomous Systems, 2022

    Improved the traditional moth-inspired odor source localization algorithm with a fuzzy inference system to adaptively change search parameters and behaviors.

    PDF | Citation
    Learn to Trace Odors: Autonomous Odor Source Localization via Deep Learning Methods
    Lingxiao Wang, Shuo Pang, Jinlong Li
    IEEE International Conference on Machine Learning and Applications (ICMLA), 2021

    Trained two neural networks, FNN and CNN, using Supervised Learning to control robots in finding odor source locations.

    PDF | Citation
    Olfactory-based Navigation via Model-based Reinforcement Learning and Fuzzy Inference Methods
    Lingxiao Wang, Shuo Pang, Jinlong Li
    IEEE Transactions on Fuzzy Systems, 2020

    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).

    PDF | Citation
    An Implementation of the Adaptive Neuro-Fuzzy Inference System (ANFIS) for Odor Source Localization
    Lingxiao Wang, Shuo Pang
    IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020

    Designed an End-to-End robot control model for finding odor source location using ANFIS.

    PDF | Citation

    📂 Wildfire Early Detection with Unmanned Aerial Vehicles

    Enhancing Wildfire Detection via Trend Estimation Under Auto-Regression Errors
    Xiyuan Liu Lingxiao Wang, Jiahao Li, Khan Mahmud, Shuo Pang
    Mathematics, 2025

    Enhance wildfire detection via predicting bounding boxes locations of smokes using the trend estimation.

    PDF | Citation
    Deep Learning-based Wildfire Smoke Detection using Uncrewed Aircraft System Imagery
    Khan Raqib Mahmud, Lingxiao Wang, Xiyuan Liu, Jiahao Li, Sunzid Hassan
    IEEE International Conference on Ubiquitous Robots (UR), 2024

    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.

    PDF | Project Page | Citation
    Vision and Olfactory-Based Wildfire Monitoring with Uncrewed Aircraft Systems
    Lingxiao Wang, Shuo Pang, Mantasha Noyela, Kevin Adkins, Lulu Sun, Marwa El-Sayed
    IEEE International Conference on Ubiquitous Robots (UR), 2023

    Equipped a drone with both olfactory (smoke detector) and visual (camera) sensors to detect wildfire existence.

    PDF | Citation

    📂 Chemical Plume Tracing with Autonomous Underwater Vehicles

    Autonomous Underwater Vehicle Based Chemical Plume Tracing via Deep Reinforcement Learning Methods
    Lingxiao Wang, Shuo Pang
    Journal of Marine Science and Engineering, 2023

    Present a deep reinforcement learning-base decision-making model to combine bio-inspired and engineering-based odor source localization algorithms.

    PDF | Citation
    3-Dimensional Hydrothermal Vent Localization based on Chemical Plume Tracing
    Lingxiao Wang, Shuo Pang, Guangyu Xu
    IEEE Oceans, 2020

    Designed a 3-D hydrothermal vent localization algorithm using moth-inspired navigation method for using on autonomous underwater vehicles.

    PDF | Citation
    Chemical Plume Tracing using an AUV based on POMDP Source Mapping and A-star Path Planning
    Lingxiao Wang, Shuo Pang
    IEEE Oceans, 2019

    Design a chemical plume tracing algorithm for locating hydrothermal vents using A-star and POMDP source mapping algorithms.

    PDF | Citation

    📂 Multi-Agent Collaboration and Robot Localization

    Coordination of Distributed Unmanned Surface Vehicles via Model-based Reinforcement Learning Methods
    Runlong Miao Lingxiao Wang, Shuo Pang
    Applied Ocean Research, 2022

    Designed a multi-agent coordination algorithm for controlling multiple unmanned surface vehicles in detecting moving objects.

    PDF | Citation
    AUV Navigation Based on Inertial Navigation and Acoustic Positioning Systems
    Lingxiao Wang, Shuo Pang
    IEEE Oceans, 2018

    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.

    PDF | Citation

    📂 Deep Learning-based Applications

    Deep Learning-Based Aerosol and Ocean Data Retrieval from Satellite Polarimeter Measurements
    Lingxiao Wang, Snorre Stamnes, Sunzid Hassan, Alexander Isiani, Cheston Sturdivant, Hoang My Le
    IEEE SoutheastCon, 2025

    Develop deep learning models to replace time-consuming vector radiative transfer (VRT) calculations in polarimeter sensor data retriveal.

    PDF | Citation
    Comparative Analysis of Deep Learning Approaches for Predicting Thermomechanical Behavior of Shape Memory Polymers
    Khan Raqib Mahmud, Lingxiao Wang, Jinyuan Chen, Xiyuan Liu, Sunzid Hassan
    IEEE SoutheastCon, 2025

    Developed and compared multiple deep learning models for predicting physical properties of polymers.

    PDF | Citation
    A Graph Neural Network based on Deep Learning Framework for Predicting the Thermomechanical Behavior of Thermoset Shape Memory Polymers
    Khan Rqqib Mahmud, Lingxiao Wang, Jinyuan Chen, Sunzid Hassan.
    Polymer, 2025

    Developed a Graphic Neural Network-based time-series prediction model to predict Thermomechanical of thermoset shape memory polymers.

    PDF | Citation

    Teaching is a cornerstone of my academic career. I'm teaching courses related to Control Theories, Artificial Intelligence, and Robotics. I offer the following courses per academic year:

    ELEN 471: Automatic Control Systems

    Every Fall Quarter 🍂
    Electrical Engineering, LaTech

    Syllabus: 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.

    Teaching Evaluation: 4.0/4.0 (Reports: 2022 | 2023 | 2024)

    ELEN 472/572: Introduction to Digital Control Systems

    Every Winter Quarter
    Electrical Engineering, LaTech

    Syllabus: 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.

    Teaching Evaluation: 3.9/4.0 (Reports: 2022 | 2023)

    ELEN 451/CSC 499: Hands-on AI and Robotics

    Every Spring Quarter 🌱
    Electrical Engineering & Computer Science, LaTech

    Syllabus: 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.

    Teaching Evaluation: 4.0/4.0 (Reports: 2023)

    🎓 Graduate Students (as 2025)

    profile photo

    Khan Mahmud

    Ph.D. in CS

    profile photo

    Alexander Isiani

    M.S. in CS

    profile photo

    Sunzid Hassan

    Ph.D. in CS

    profile photo

    Hoang My Le

    Ph.D. in EE

    🧑‍🎓 Undergraduate Students (as 2025)

    profile photo

    Hannah McPherson

    B.S. in EE

    profile photo

    Norma Olinde

    B.S. in EE

    profile photo

    Nathaniel Gremillion

    B.S. in EE

    profile photo

    Jayden Toussaint

    B.S. in EE

    profile photo

    Tuan Tran

    B.S. in EE

    profile photo

    Ty Davis

    B.S. in CE

    profile photo

    💼 Alumni (as 2025)

    profile photo

    Luke Roger

    2023 B.S. in EE
    Now at NASA

    profile photo

    Cheston Sturdivant

    2025 M.S. in EE
    Now at CLP Engineering

    profile photo profile photo

    Updated in 07-03-2025 | Website Template