Joaquin Mas@masjoaquin72

Events attended

Submissions made

Argentina

2+ years of experience

About me

I’m a Mathematics graduate with a strong drive to turn complex ideas into practical, impactful solutions. My experience spans Functional Analysis, Finance, commercial roles (including buyer-side perspective), and serving as a CTO—giving me a true end-to-end vision: from understanding problems deeply to executing both technically and strategically. I specialize in connecting analytical thinking with real-world decision-making. I can translate business needs into clear models, assess financial viability, understand market dynamics from a buyer’s perspective, and guide teams from concept to a working product. What I bring to a hackathon: • Strong problem-solving skills under pressure • Technical leadership and team coordination • Ability to turn ideas into viable, scalable products • Financial and commercial insight (including buyer mindset) • Focus on building solutions with real market fit and impact I’m looking to join a team that wants to build something meaningful, innovative, and grounded in reality. If you need someone who combines math, finance, commercial strategy, and execution—let’s connect.

Socials

🤝 Top Collaborators

Ever Allende

I am a cybersecurity auditor, full-stack builder and AI systems researcher focused on turning complex technical ideas into usable products. My work sits at the intersection of security, compliance, automation, blockchain infrastructure and applied AI. I build prototypes that are practical, auditable and designed for real-world deployment, not just demos. For this hackathon, I created RAE DecisionOps, an open-core trust layer for AI-assisted decisions. The goal is simple: help teams reduce overconfidence in noisy data environments and turn uncertain signals into clearer operational recommendations. I am especially interested in building AI-native infrastructure that can scale from local execution to cloud and GPU-backed workflows, while keeping reproducibility, security and business value at the center.

Cynthia Ortiz Oviedo

🤓 Latest Submissions

RAE DecisionOps AI for High-Stakes Decisions

RAE DecisionOps is an entropy-regulated trust layer for AI agents and business decision workflows. It helps teams convert noisy, incomplete or conflicting data into simple operational recommendations: act, observe or escalate. The system connects structured inputs, APIs, OCR outputs, market feeds, enterprise data and blockchain oracles through a modular pipeline. Before allowing a recommendation to be treated as reliable, RAE evaluates uncertainty, signal quality, confidence degradation, warnings and reproducibility metadata. The goal is not to build a magical predictor. The goal is to reduce overconfidence in weak-data environments and make AI-assisted decisions safer, explainable and audit-ready. The demo exposes a user-friendly interface where operators can define an Execution Context Matrix with variables, values, weights, confidence levels and notes. Business users receive a clear recommendation, while technical users can inspect regulated confidence, uncertainty, warnings and reproducibility hashes. For the AMD Developer Hackathon, RAE demonstrates how AMD infrastructure can support scalable AI-native workflows where performance, reproducibility and trust matter. The architecture is open-core: the public demo, technical walkthrough and reproducible runtime are available for validation, while production-grade decision matrices, scoring templates, enterprise connectors and deployment playbooks remain commercial modules. RAE can be applied to cybersecurity triage, compliance automation, market simulation, enterprise AI governance, agentic workflows and blockchain-connected data systems.

Hackathon link

10 May 2026

👌 Attended Hackathons

AMD Developer Hackathon

Grab your ideas, spin up compute, and start building what’s next! Start with $100 in AMD Developer Cloud credits and begin building right away. Get access to hands-on tutorials, workshops, and curated learning resources to help you build faster and go further. To unlock credits and join the hackathon, sign up for the AMD AI Developer Program. 🤝 Go solo or team up — ship something real. 💰 $21,500+ total prize pool & 1 × AMD Radeon™ AI PRO R9700 GPU up for grabs. 📍 On-site Venue (May 9-10): MindsDB SF AI Collective 3154 17th St, San Francisco, California, USA 📍On-site participation is by invitation only. Travel and accommodation expenses will not be covered. 🧑‍💻 Developers, builders, and innovators - bring your boldest ideas and let’s turn them into real AI systems on AMD.