Professional Summary
Robotics Engineer specializing in autonomy, perception, and embedded AI deployment on NVIDIA Jetson platforms. I design and ship end-to-end robotic systems spanning simulation validation, ROS 2 autonomy integration, real-time vision pipelines, and TensorRT/CUDA optimization under embedded compute constraints. My focus is on measurable performance gains, deployment reliability, and scalable multi-robot software architectures.
Stokes Robotics
Joplin, MO · On-site
- Led autonomy, simulation validation, and embedded perception deployment to support real-time multi-robot field operation.
- Built ROS 2 + simulation workflows (Isaac Sim / MuJoCo / Gazebo) to reduce hardware iteration cycles.
Vistruaz LLC
AI Research Assistant · Remote
- Implemented complex-valued neural networks and model observability tooling for experimental evaluation.
University of Cincinnati
M.S. Mechanical Engineering · Jan 2021 – Apr 2024
- Focus: robotics, autonomy, reinforcement learning, perception.
University of Cincinnati
- Led instructional support and mentoring for engineering coursework, strengthening student outcomes in technical problem-solving.
- Conducted reinforcement learning research contributing to a peer-reviewed AIAA SCITECH 2023 publication.
CattleQuants
Machine Learning Intern · Remote
- Built and optimized U-Net segmentation pipelines and deployed TensorRT inference on embedded Jetson platforms.
Accenture
Hyderabad, India
- Owned delivery of C++ middleware features for enterprise SAP integrations in production environments.
- Improved production reliability via structured testing and failure analysis, collaborating across teams and CI/CD workflows.
Osmania University
B.E. Mechanical Engineering · Aug 2014 – Jun 2018
- Training in mechanics, system design, and engineering analysis foundations.
South Central Railway
Mechanical Engineering Intern · Hyderabad, India · On-site
- Performed mechanical system inspection and maintenance planning within railway operations.
Skills
Robots & Sensors
Publication
Karnam, S., & Sharma, R. (2023).
Q-Learning Based Search of a Ground Target in a Grid with Partial Information
.
AIAA SCITECH 2023, Washington DC.