Robotics, Physical AI, multimodal AI and systems-engineering work spanning deployed software, autonomous-system modules, physical hardware integration, research prototypes and ongoing development.
Featured
A 28-week Physical AI creation and engineering project focused on building a physical, language-conditioned autonomous delivery platform.
A deployed robot-vision system that converts natural-language instructions into localized visual targets across still images, recorded video and browser-camera inputs.
Physical demo video coming soonBuilt a complete ROS 2-to-hardware control path for a physical robotic arm, integrating higher-level robot software with embedded firmware and physical actuation.
Multi-phase autonomous-delivery robotics work integrating ROS 2 navigation, robot perception, localization, manipulation and environment interaction.
Built a reproducible evaluation pipeline for benchmarking vision-language models across standardized multimodal question-answering datasets.
Supporting technical work
Computer Vision · Temporal ML
End-to-end video-recognition prototype using WLASL data, MediaPipe hand landmarks, temporal PyTorch models and a deployed Streamlit interface.
The application supports curated clips and exploratory uploaded videos, returning top-k predictions, confidence values and extracted landmark information.
Visual Grounding · Benchmarking
Referring-expression grounding experiment comparing a lightweight CLIP-based regression model against Grounding DINO across 1,150 test pairs.
Evaluation included Acc@0.5, mIoU, Acc@0.75, center error, inference time and category-level analysis.
RL · Control
Implementations of dynamic programming, Monte Carlo control, SARSA, Q-learning, Expected SARSA, Tree Backup and REINFORCE across FrozenLake, CartPole and MountainCar.
Data · Cloud · ML
Distributed-data and machine-learning work spanning Hadoop, PySpark, Spark MLlib, Azure Data Factory, Stream Analytics, IoT pipelines and Azure ML.
LLMs · RAG · Analytics
Applied AI strategy project combining market and policy analysis with a multi-agent retrieval-augmented generation system using OpenAI embeddings, FAISS, LangChain and CrewAI.
Systems Engineering · Live Environments
Scoped, procured, installed and integrated a complete church audio, video, display and livestream system for weekly services.
