Agustina Selser
AI & Neural Engineer · Brain-computer interfaces, neural decoding and neuromodulation.
AI to advance neuroscience. Software to sharpen both.
Selected work
Built end to end: clinical tools, walking hardware, and 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.
Neural interfaces
BCI pipelines, neuroprosthetics for hand and arm paralysis, biosignal processing and neural decoding.
Machine learning & LLM systems
PyTorch and scikit-learn pipelines, neural decoding, multi-agent orchestration and retrieval-augmented context.
Software & distributed systems
Go and TypeScript services, React and Next.js interfaces, durable workflows, hexagonal architecture, Kubernetes, observability and CI/CD.
Robotics & control
CAD to hardware, MuJoCo simulation, gait design, PID control and reinforcement learning.
Embedded & IoT
ESP32 and Arduino firmware in C++, Raspberry Pi as the onboard control computer, MQTT telemetry, sensor integration and live dashboards.
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