Robotics · Physical AI · Neuroscience · Distributed Systems
I am an undergraduate double major in Computer Science and Neuroscience at Northwestern University, with a strong interest in building intelligent, embodied systems that operate reliably in real-world environments. My work sits at the intersection of robotics, biological intelligence, and system-level software engineering, where principles from neural and physical systems inform the design of scalable autonomous agents.
I am particularly drawn to Physical AI (systems that perceive, decide, and act in the world) and to the infrastructure, distributed ML pipelines, and system software that make these systems performant, observable, and dependable.
My projects span robotics, simulation, and machine learning, with an emphasis on tightly integrated systems rather than isolated models:
- Multi-agent robotic simulation using NVIDIA Isaac Sim, ROS2, and Gazebo, with attention to coordination, scalability, and reproducibility
- Brain-computer interface pipelines for real-time neural signal decoding and closed-loop interaction
- Distributed ML systems, including training and evaluation workflows with performance, monitoring, and reliability in mind
- AI-powered platforms leveraging OCR, retrieval-augmented generation, and large language models
- Bio-inspired control systems informed by neuroscience and biomechanics for adaptive locomotion and manipulation
Beyond algorithms, I care deeply about how systems are built and deployed. I enjoy working close to the boundary between systems engineering, cloud infrastructure, and applied machine learning, and I prioritize correctness, performance, and maintainability in the systems I design.
Python | C/C++ | ROS2 | OpenCV | CUDA | PyTorch | Linux
Docker | Cloud APIs | Distributed Systems
Raspberry Pi | React | Django | LangChain