Laxminarayana Vadnala

Ph.D in Computer Science

University of Notre Dame, South Bend, IN

lvadnala@nd.edu

laxminarayana.vadnala1997@gmail.com

View Resume

Bio

I am an upcoming Ph.D Student in Computer Science, at Univeristy of Notre Dame, South Bend, IN. I am currently working as a Graduate Research Assistant at the sUAS—Human-Centered Computing Lab (sUAS HCC) , advised by Dr. Ankit Agarwal, in collaboration with the Cooperative Computing Lab , advised by Prof. Dr. Douglas Thain from the University of Notre Dame. Prior to my Master's studies at SLU, I worked as a Solution Architect at Southwest Airlines, a Senior Software Engineer at Qualcomm, and in other roles across different companies for over 4 years.

My current research interests focus on integrating High-Performance Computing with Human-Computer Interaction, specifically in the context of simulation or real-world applications.

  1. Currently working on Small Unmanned Aircraft Systems (sUAS) simulations, but I am eager to apply the benefits of High-Performance Computing to other Human-Computer Interaction systems as well.
  2. Focusing on the Computer Vision advancements and integrating these advancements to improvise the Human-Computer interaction systems at high scale
  3. Am also focusing on improving the capabilities of currently exisiting approached of High Performance Computing.

Education

Univeristy of Notre DameAug. 2025 - Present

Ph.D. in Computer Science

High-Performance Computing

Saint Louis UniversityAug. 2023 - May 2025

M.Sc. in Computer Science

News

  • April., 2025     Got Admission confirmation for Ph.D at University of Notre Dame in Department of Computer Science under Professor Douglas Thain in stream of High-Perfromance Computing.
  • Jul., 2024     Joined sUAS—Human-Centered Computing Lab (sUAS HCC) under Dr. Ankit Agarwal as Graduate Research Assistant at SLU.
  • Aug., 2023     Started at SLU as M.Sc. in Computer Science Student.

    • Projects

    Safety Aware Drone Ecosystem's Back end and Front end (SADE)

    SLU Graduate Research Assistant (July 2024 - Present)

    Safety Aware Drone Ecosystem's Back end and Front end (SADE) Description

    • Implemented the whole back end from scratch with MQTT and Database integration to facilitate the transfer of drone configuration configured by user to SADE simulation stack which comprises of PX4, Gazebo and Unreal Game Engine to enable simulation.
    • Optimized the existing front end to support real time changes from user for butter smooth experience. Also integrated Cesium JS components to enable Google Maps 3D tiles for precise location configuration for better user experience.
    • Worked with Tech Stack Python, Fast API, Mosquitto MQTT, Mongo DB, Docker, GitHub Actions, React JS, Cesium JS, Docker Compose
    Safety Aware Drone Ecosystem (SADE) Simulation Plugins

    SLU Graduate Research Assistant (July 2024 - Present)

    Safety Aware Drone Ecosystem's Simulation Plugins

    • Developed and Managing the Gazebo physics engine plugins like Real time Terrain Loaders when drone fly using the terrain information from the 3D tiles of Cesium for simulating precise taking off, landing, obstacles for real time collision and more physics operation
    • improvised the existing wind plugin from PX4 Gazebo as per the SADE project requirements in real time while applying the continuous wind force on the simulated drones in simulation.
    • Developed a Drone Pose sender (Gazebo Plugin) and Receiver (CLI tool) which basically sends the Pose of Drone from gazebo in real time as UDP packets and Pose Receiver will be receiving the UDP packets in real time. This includes real time Endian encoding and decoding.
    • Worked with Tech Stack C++ 11, SDF, Gazebo 11 C++ library, ROS Noetic, Linux Bash Scripts
    Safety Aware Drone Ecosystem (SADE) Workflow Management

    SLU Graduate Research Assistant (July 2024 - Present)

    Safety Aware Drone Ecosystem's Workflow Management

    • Developed the workflow management system for integrating and scaling of Unreal Engine Pods, Unreal Pixel Streaming Pods, GUI and Back end Pods, PX4 Auto Pilot Pods and Gazebo Pods.
    • Unreal Engine Pods share the GPU resources, we achieved this using NVIDIA Container toolkit, and streaming the display over network via Pixel Streaming to Front end.
    • Worked with Tech Stack Python, Shell Script, Docker, Docker compose
    Drone Response (DR) Live Camera feed pipeline

    SLU Graduate Research Assistant (July 2024 - Present)

    Safety Aware Drone Ecosystem's Workflow Management

    • Implemented the whole back end from scratch with MQTT and Database integration to facilitate the transfer of drone configuration configured by user to SADE simulation stack which comprises of PX4, Gazebo and Unreal Game Engine to enable simulation.
    • Optimized the existing front end to support real time changes from user for butter smooth experience. Also integrated Cesium JS components to enable Google Maps 3D tiles for precise location configuration for better user experience.
    • Worked with Tech Stack Python, Fast API, Mosquitto MQTT, Mongo DB, Docker, GitHub Actions, React JS, Cesium JS, Docker Compose

    Publications

    Most recent publications on Google Scholar.
    * indicates equal contribution.

    Working on it!

    Mentee

    Dr. Ankit Agarwal (Saint Louis University), Jul 2024 - Present

    Vitæ

    Full CV in PDF.

    Laxminarayana Vadnala
    lvadnala@nd.edu