About Me

Hi, I'm Walter Arredondo, a final-year Computer Science student at UNAM in Mexico City. I enjoy working at the intersection of computer networks, cloud infrastructure, automation and robotics, anywhere software has to talk to the physical or networked world and actually behave reliably.

Recently, I was part of the UNAM team that won 1st place in the Huawei ICT Competition 2024–2025 (Mexico, Network Track), where we designed and troubleshooted end-to-end network scenarios under time pressure. That experience solidified my interest in network engineering and showed me how much impact good infrastructure design and automation can have.

During my degree I've split my time between software engineering, systems and applied research. I collaborated as a Robotics Software Engineer Intern at the Facultad de Ciencias, where I develop C++ control software for an autonomous human-sized robot, integrate sensors and actuators, and maintain a simulation environment that lets us test changes safely before deploying them to the real hardware. Earlier, at the Instituto de Ingeniería (UNAM), I worked on a seismic response evaluation project, building and automating data workflows that pulled information from geotechnical databases, refined and processed accelerograms to obtain response spectra and related metrics, and organized the outputs for final reporting.

On the infrastructure side, I'm a daily Linux (especially NixOS) user and enjoy building reproducible environments, containers and CI/CD pipelines that make development less fragile and more predictable. I'm comfortable moving across the stack—from low-level systems programming to scripting and tooling in Python, to wiring things together with Docker, Git and basic cloud services. I have foundational experience with Google Cloud Platform (virtual machines, storage and networking) and I'm particularly interested in how cloud-native patterns can be applied to networking and security.

Security is another thread in my profile. Through the Cisco Junior Cybersecurity Analyst training and Huawei Security/WLAN tracks, I've developed a solid grounding in topics such as network monitoring, firewalls, VPN concepts, access control and incident response. I like thinking about systems not only in terms of performance and reliability, but also in terms of threat models and risk.

Beyond pure infrastructure, I'm fascinated by learning systems and AI/ML. I've studied AI/ML fundamentals and deep neural networks, and I've used PyTorch and CUDA in small projects. A lot of my learning process is driven by experimentation and by building tools for myself—one of those tools is Ankidemy, an open-source spaced-repetition platform for structured learning that I help develop and actively use to study complex subjects.

In short, I enjoy solving problems where networks, cloud, automation and data meet, and I'm always looking for opportunities to work on systems that are technically challenging, useful to others, and built with care.