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Ashwith Poojary
Mid-level Software & AI Engineer specializing in Robotics, LLMs, and Reinforcement Learning
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About
Robotics/AI Master's thesis researcher building an LLM-driven workflow to generate and evaluate robot policies before running them in an environment. Also built a local LLM-based real-time target-tracking robot using a pan-tilt camera with LangChain + Ollama, and has hands-on ROS 2/Gazebo experience including URDF-based simulation and a TurtleBot multi-agent chase project.
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Key Strengths
- LLM-driven robotics research (policy generation/evaluation before environment execution)
- Built ROS 2 project simulating a TurtleBot chaser with randomized multi-agent behavior
- Applied DFS maze-solving and inverse kinematics to execute motion plans on a Cobot 600 Pro
- Strong grasp of ROS 2 fundamentals (topics, namespaces, launch/config files)
- Communicates technical concepts via Medium articles
Reference Highlights
- well-versed in robotics software technical abilities
- proficient in robot simulations
- strong at reproducing research results
- effective debugging and finding optimal ways to reproduce results
- strong at reading research and identifying plausible bottlenecks
- innovative in making approaches optimizable
- able to turn ambiguous technical problems into practical plans
- aligns early to avoid confusion
- shares intermediate results
- takes feedback constructively
- documents progress well
- adapts well to fast-paced settings
- creates strong mental models of tasks
- identifies constraints and iterates thoroughly
- strong engineering fundamentals
- strong research instincts
- communicates well and stays aligned to goals
Ashwith's references speak for themselves. Let us connect you.
Experience
Education
Awards
Skills
Languages
Publications
2 publications
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