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Master of Science

University of Colorado Boulder

• Computer Science

• Specializing in Robotics and Human-Robot Interaction

Bachelor of Science

The University of Applied Sciences Bingen, Germany

• Computer Science

Bachelor of Engineering

SRM University, Chennai, India

• Computer Science and Engineering

Graduate Researcher

Human Interaction and Robotics Group, CU Boulder

• Implementing contact-aware controllers using ROS and C++ to enhance safety in human-robot collaboration.
• Prototyping algorithms in simulation (Drake, NVIDIA Isaac Sim) to enable robots to differentiate between objects and humans for more intuitive interaction.

Embedded Software Developer

Trinamix GmbH (BASF), Ludwigshafen, Germany

• Led the adoption of a new Rockchip platform, cutting prototyping costs by 90% through hands-on board bring-up, device tree configuration, and low-level hardware debugging (I2C, GPIO).
• Developed Linux V4L2 camera drivers in C/C++ to integrate custom laser sensors, enabling computer vision-based liveness detection for a major German automotive OEM.

Intern, Bachelor Thesis

NXP Semiconductors, Hamburg, Germany

• Implemented novel calibration optimizations for an NXP automotive radar front end, developing C-based test firmware.
• Achieved >50% reduction in calibration time through algorithmic improvements.

SHARD: End-to-End VLM Inference on Rockchip RK3588

• Reverse-engineered undocumented NPU hardware limits (32KB SRAM, 4KB Page) to deploy a VLM that failed with standard vendor tools, creating novel 'Nano-Tiling' and 'Graph Surgery' techniques.
• Achieved <2.0s latency (a 15x speedup over CPU baseline) while maintaining FP32-equivalent fidelity (>0.999 cosine similarity), enabling real-time deployment on commodity hardware.

Neuro-Symbolic VLM for Adaptive Impedance Control

• Designed a system connecting a VLM's scene understanding to a low-level impedance controller for a Franka Emika arm, validated and tested in NVIDIA Isaac Sim.
• Boosted material classification accuracy from 28% (pure visual) to 100% by developing a neuro-symbolic pipeline that combines OpenCV geometric detection with VLM reasoning via scene graphs.

Compliant Explicit Reference Governor (CERG) for Contact-Rich Tasks

• Designed a novel safety filter that enables robots to operate safely during physical contact by placing a hard limit on the total system energy, ensuring provably safe interaction.
• Submitted to IFAC 2026.