Software Engineer · Microsoft Azure High Performance Computing · diegoiru@stanford.edu / diiruo@gmail.com · Resume
I care deeply about solving problems through engineering and machine learning. I've worked across distributed GPU infrastructure, computer vision, supply chain, finance, and cybersecurity.
Pontifical University of Chile · Recommender Systems Lab
Built a recommender system driven by electroencephalography (EEG) brain signals. Used the DEAP dataset (32 subjects, 32 EEG channels, 128 Hz) to generate topographic brain maps via the MNE library. Fed EEG-derived features into a Transformer encoder with multi-head attention to classify video preferences from brain activity. Constructed user-item interaction matrices and applied collaborative filtering to predict content recommendations. Evaluated with MAP, nDCG, and precision@k.
Pontifical University of Chile · Fluid Mechanics
Designed and 3D-printed a Lagrangian ocean drifter for measuring surface currents. Modeled hydrodynamic drag and vortex shedding using computational fluid dynamics simulations. Fabricated custom components (blades, cylinder, housing) via FDM 3D printing, iterated on geometries to minimize drift error. Validated against in-situ oceanographic measurements.
Twenty Billion Neurons · Company advised by Yoshua Bengio
Worked on deep learning technologies for real-world video understanding and human movement recognition. Developed and deployed production code to analyze video streams, utilizing custom lightweight 3D-CNN architectures to extract spatial-temporal meaning and classify gestures in real-time. TwentyBN authored the foundational "Something-Something" and "Jester" datasets for video understanding. Company acquired by Qualcomm.
University of Texas at Austin · Wireless Networking and Communications Group
Conducted deep learning research on convolutional generative adversarial networks (ConvGANs) under Alex Dimakis. Implemented and trained GAN architectures in PyTorch/TensorFlow for image generation and reconstruction tasks. Explored latent space representations and adversarial training stability.
GPU fleet infrastructure (500k+ NVIDIA H200/GB200) and LLM inference engine for Copilot. Cluster orchestration, GDPR-compliant prompt routing, sub-ms tail latency. Microsoft Certified: Azure AI Engineer Associate.
Optimized phishing detection algorithms, reducing AWS server costs by 75% ($3M in savings). Refactored Go microservices and Terraform infrastructure.
Real-time video ML pipelines for human movement recognition. Company advised by Yoshua Bengio, acquired by Qualcomm.
Seeds for the Future fellow. Sponsored research fellowship to study telecom infrastructure in Shenzhen and Beijing.
Eight-month internship optimizing delivery speed promises across Amazon's EU fulfillment network. Modeled product placement and routing across fulfillment centers, distribution nodes, and last-mile handoffs to minimize delivery time, directly impacting the 1-day and 2-day delivery promises that drive conversion.
Built real-time ETF data visualization tools using D3.js and Python, supporting the launch of new financial products.
Replaced Excel workflows with scikit-learn and Keras models for APR price optimization on SMB transactional data.
Validated a reinforcement learning approach to analog chip design through 50+ customer interviews. Pitched to deep-tech VCs including HAX.
Built a two-sided marketplace for blood donations. Secured 3 government grants, negotiated integration pilots with major hospital networks.
Bootstrapped from high school to $100k ARR and 800+ weekly active users. Orchestrated logistics for amateur sports leagues across Santiago for seven years. $250k+ in cumulative revenue.
Mapped two municipalities using DJI fleets. Models supported a $50k Architecture Award project. Designed and assembled custom UAVs for experimental flight.
Imported and sold 400+ Raspberry Pi microcontrollers, bridging supply gaps in LATAM at high margins.
M.Sc. Computer Science coursework through Stanford SCPD, fully sponsored by Microsoft Education Program.
Full scholarship as AI researcher under Alex Dimakis at the Wireless Networking and Communications Group. First freshman to receive The Bridge grant, traditionally reserved for graduate students.
B.Sc. Computer Science, Minor in Statistics. Three research and entrepreneurship scholarships. TA across eight courses. Chapter author, 'ChatGPT und andere Quatschmaschinen' (Sudmann, 2024).
Technology has been a means to explore the world. I've managed to work and conduct research across very different cultures and companies. Offline, I enjoy freediving, road cycling, and hiking. I've visited 40+ countries and made countless friends along the way. I freedove with humpback whales in French Polynesia and toured Shenzhen and Beijing for free thanks to a cold email. I've also felt immense fulfillment from raising over $300k for charity initiatives. Some photos from these experiences can be found here.
![[Poster]](https://github.com/Iruretagoyena/RecommenderSystemEEGSignals/blob/main/Poster.png){kind=link}