Agustina Selser
Biomedical Engineer · Brain-computer interfaces, neuroengineering & robotics.
I build systems that read, decode and respond to signals from the body, from neural interfaces to walking robots.
Selected work
From neural signals to walking hardware to agents that ship code.
About
Decoding signals, then building the hardware that answers them.
I graduated with honors in BS/MS Bioengineering from ITBA (Buenos Aires) and am currently pursuing an MSc in Biomedical Engineering at Columbia University, where I focus on brain-computer interfaces (BCI) and neuroengineering applications.
I completed a four-month research internship at Polytechnique Montréal on a neuroprosthesis project for hand and arm paralysis, and later continued for a year as an external consultant, which solidified my passion for neural interface technologies.
I also worked at the Cognitive Neuroscience Center (CNC) of Universidad de San Andrés, contributing to neuroscience research through signal analysis and data processing, with a particular emphasis on decoding neural signals.
Most recently I spent a summer at Terrace as an AI engineer intern, remote from Buenos Aires, where I was the primary author of an autonomous coding agent in Go: it takes a Linear ticket or a Slack mention, runs a coding agent against the repository inside a durable workflow, and returns a pull request that has already been built, linted, tested, reviewed and pushed through CI. At its peak it was among the company's top three contributors by merged lines of code.
Software & distributed systems
Go and TypeScript services, React and Next.js interfaces, durable workflows, event-driven microservices, Kubernetes, observability and CI/CD.
Machine learning & LLM systems
PyTorch and scikit-learn pipelines, foundation-model embeddings, neural decoding, multi-agent orchestration and retrieval-augmented context.
Neural interfaces
BCI pipelines, neuroprosthetics, biosignal processing and neural decoding.
Robotics & control
CAD to hardware, MuJoCo simulation, gait design, PID control and reinforcement learning.
Embedded & IoT
ESP32 and Arduino firmware in C++, MQTT telemetry, sensor integration and live dashboards.




