Alejandro
Martínez Ronda

Double-degree Mathematical & Computer Engineer focused on post-quantum cryptography and its mathematical foundations.

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Who I am & what I've studied

A snapshot of my background — profile, studies and hands-on experience. Swipe right for experience →

Alejandro Martínez Ronda
Profile

I pair mathematical rigor with software to build secure, verifiable systems. My bachelor's thesis implements a lattice-based (LWE) scheme from scratch and studies the NIST standards ML-KEM and ML-DSA, backed by real experience in data engineering and machine learning.

Education
B.Sc. Mathematical Engineering
2022 – 2026
Universidad Alfonso X el Sabio (UAX), Madrid · Degree completed
B.Sc. Computer Engineering
2022 – 2027
Universidad Alfonso X el Sabio (UAX), Madrid · Final year
International Exchange — Investment Project Evaluation
Jan – Jun 2026
Universidad Nacional de Río Cuarto, Argentina
LanguagesSpanish (native) · Catalan (native) · English — C1 Advanced (CAE)
CertificationsIronhack Data Analytics Bootcamp · Microsoft Power BI · Storytelling (Coursera)
Experience
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Data Architecture & Engineering Intern
Havas Media Group — Madrid
Dec 2025 – Feb 2026
  • Built cloud data pipelines and advanced data modeling on Google Cloud with Dataform.
  • Wrote complex SQLx transformation logic and led BigQuery optimization to cut query cost and runtime.
  • Managed GitLab version control and resolved incidents in automated, high-availability data flows.
Data & Modeling Intern
DeNexus — Madrid
Nov 2024 – Feb 2025
  • Built an end-to-end pipeline extracting cybersecurity incidents from SEC Form 8-K filings (scraping SEC EDGAR).
  • Classified incidents with ML and NLP/LLM models (BERT, LLaMA) and generated semi-automated reports on Databricks.
Project Management Intern
Havas Media Group — Madrid
Sep 2025 – Nov 2025
  • Owned task definition and validation, delivery tracking and deliverable review to keep timelines on schedule.
Sales Manager & Teller
BBVA — Alicante
Summers 2023 & 2024
  • Managed banking operations and financial-product support in a high-volume branch.

Learning With Errors (LWE)

Post-quantum, lattice-based cryptography

My bachelor's thesis in Mathematical Engineering studies how one idea — adding a little calibrated noise to plain linear algebra — turns into hardness that resists even quantum computers, and how that hardness is the foundation of the new NIST post-quantum standards.

What the thesis covers
  • The quantum threat — why Shor's algorithm breaks RSA and ECC.
  • Lattices — a new kind of hardness (SVP / CVP, good vs. bad basis).
  • Learning With Errors — linear algebra made hard by calibrated noise.
  • Theoretical guarantee — Regev's worst-case to average-case reduction.
  • From theory to standards — Regev encryption, ML-KEM (Kyber) and ML-DSA (Dilithium).
  • Implementation & experiments — a scheme built from scratch and the noise / modulus / dimension trade-off.
b₁b₂

Personal projects

A selection of things I've built, grouped by focus. Swipe sideways within a row to see more.

Cryptography & Security

2

Rainbow Table Attack

A rainbow-table attack on MD5 password hashes, built from scratch — reduction functions, chain construction and a collision analysis of the time–memory trade-off.

CryptographyHashingPython

Financial Model — QuantumVault

5-year financial model (DCF, NPV, IRR, Monte Carlo) for a zero-knowledge, post-quantum cloud-security concept.

Monte CarloFinancial ModelingPython

Machine Learning & AI

5

CNN — Melanoma Detection

A CNN in PyTorch classifying skin lesions as melanoma vs. benign — custom architecture, early stopping, 92.7% test accuracy. (Academic project, not a medical tool.)

PyTorchCNNDeep Learning

RAG — WWII Chatbot

Retrieval-Augmented Generation chatbot on WWII: a FAISS index over a curated corpus feeds a local Llama 3.1 (8B) via Ollama, with a Streamlit UI.

RAGFAISSLlama 3.1Streamlit

RNN — Stock Price Prediction

Recurrent neural network for time-series forecasting of stock prices — sequence modeling with deep learning.

Deep LearningRNNTime Series

Patient Survival Prediction

A feedforward neural network (Keras/TensorFlow) predicting patient survival from clinical, genetic and lifestyle data, with SMOTE balancing and a written report.

TensorFlowKerasDeep Learning

Purchase Propensity Model

A Gradient Boosting model scoring each customer's probability to purchase from demographic, product and campaign data.

Gradient Boostingscikit-learnPython

Data & Analytics

2

CLTV — Data Integration

End-to-end Customer Lifetime Value pipeline: ETL from Azure SQL, a star-schema warehouse, logistic-regression retention and Power BI dashboards.

Azure SQLSQLPower BI

PCA & Clustering

Unsupervised segmentation with PCA and clustering, profiled and visualised in an interactive Power BI dashboard.

PCAClusteringPower BI

Mathematical Foundations

1

Simple Random Walks

Simulation and statistical analysis of simple random walks — foundations of stochastic processes and Brownian motion.

Stochastic ProcessesProbabilitySimulation

What people say

Recommendation letters from the people I've worked with. Swipe sideways for more.

His most exceptional quality is a strong commitment to achieving results, paired with a structured, analytical mindset — a valuable team player in a multicultural, multidisciplinary organization.

Romy R. Ravines
Head of Research & Modeling Strategies · DeNexus
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Few early-career profiles combine technical ability, professional performance and future projection like Alejandro — an asset of immediate value to any organization.

Juan Guerrero
Technical Director · Havas Media Group
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A reliable profile with a real capacity for work and a very positive attitude within technical teams — someone who keeps timelines consistently on track.

Luis Monje
Project Manager · Havas Media Group
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Let's talk. I'm open to
opportunities and collaborations.

martinezrondaalejandro@gmail.com Download CV alejandromtnz alejandromartinezronda
Cryptography & Security
Post-Quantum Cryptography, Lattice-Based Cryptography, Learning With Errors, ML-KEM, ML-DSA, Cybersecurity
Mathematics
Applied Mathematics, Probability, Statistics, Linear Algebra, Optimization
Programming
Python, SQL, Java, JavaScript, Bash
AI & Data
Machine Learning, Deep Learning, NLP, LLMs, Google Cloud, BigQuery, Databricks
Tools
Git, GitHub, GitLab, Linux, Agile
Madrid, Spain© 2026 Alejandro Martínez Ronda

My everyday tools

Small utilities I use often, built to work instantly without leaving the page.

Word → PDF

Convert a .docx document to PDF, keeping the formatting.

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Images → PDF

Combine one or more images (JPG/PNG) into a single PDF.

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More, coming soon

This space grows with you: compress PDFs, merge/split, format converters… added as new cards.