Pablo Matorras-Cuevas

About Me

Dual Spanish-Swiss citizen, bilingual in Spanish and English (B2 French, B1 Italian). My exposure to diverse educational and professional environments has developed strong multicultural communication skills. I'm driven by curiosity about economic and geopolitical issues, frequently analyzing diverse data sources to form independent perspectives.

Technical Skills

Programming: Python, C++, MATLAB, R, ROOT, Coffea
Machine Learning: scikit-learn, TensorFlow, XGBoost
Data Analysis: Pandas, NumPy, ROOT, statistical modeling
Quantitative Finance: Portfolio optimization, time series analysis, backtesting
Computing: Parallel computing (Condor, Slurm), Monte Carlo methods, Quantum computing
Collaboration: GitHub, GitLab, LaTeX, MS Office

Professional Attributes

Proactive, team-oriented problem solver with strong communication skills
Project coordination and stakeholder management experience
Cross-disciplinary research background with proven adaptability

Interests & Activities

Competitive sports background (water polo, swimming, triathlon). Active outdoor enthusiast: padel, hiking, surfing, cycling, running, skiing. These pursuits reflect my commitment to teamwork, discipline, and maintaining a balanced lifestyle.

Featured Projects

Financial-ML: Equity Selection System

Machine learning system for equity selection that predicts S&P 500 outperformers using market data, fundamentals, and sentiment indicators. Achieved 20.2% annual returns and 0.93 Sharpe ratio using time series cross-validation and Random Forest models.

MacroEconomics Dashboard

Interactive dashboard for exploring macroeconomic indicators (inflation, GDP, etc.) across countries. Built with Plotly/Dash and Python, featuring time series analysis and geospatial visualization.

footAI: Football Analytics

End-to-end system predicting match outcomes (home/draw/away) across Europe's top five leagues. Combines Elo ratings with machine learning (RandomForest) achieving 50.5% accuracy on three-class prediction and a 37.4% draw recall. Includes an optional Plotly/Dash visualization.

Work Experience

Graduate Researcher | Instituto de Física de Cantabria (IFCA)

Oct 2019 - Mar 2025 | Santander, Spain & Geneva, Switzerland

Large-scale data analysis: Processed very large CMS detector datasets using statistical modelling, Monte Carlo simulations, and distributed computing to validate collision reconstruction and understand detector performance
Detector R&D (CMS Collaboration, 3000+ scientists): Contributed to testing next-generation muon chambers for CMS upgrade (2026):
- Utilized FLUKA detector simulations to infer expected particle flux in upgraded detector
- Performed testbeam validation of detector behavior under real-world conditions
Monte Carlo validation: Systematically compared data and simulation using kinematic variables (momentum, angular distributions) and machine learning classifiers for particle identification to ensure reconstruction accuracy
CMS detector operations: Participated actively in CMS data-taking operations and contributing to internal review meetings and shift coordination to ensure detector performance
Scientific communication: Presented research findings at international conferences and collaboration meetings on behalf of CMS; contributed to peer-reviewed publications

Teaching Assistant | Universidad de Cantabria

Jul 2021 - Jul 2023 | Santander, Spain

Laboratory course design & instruction: Designed and taught third-year experimental physics courses; created novel experiments and adapted materials to enhance student comprehension
Student assessment & mentorship: Evaluated student work, provided detailed feedback, and mentored students through laboratory projects; strengthened communication and pedagogical skills

Research Assistant | University of Zurich

Jul 2018 - Jul 2019 | Zurich, Switzerland

New physics searches: Assessed detector sensitivity to leptoquark signals by developing simulations for signal and background processes using Python, C++, and ROOT
Pileup studies: Investigated the feasibility of measuring low-energy collision signatures masked by underlying events (pileup); developed simulations to understand signal characteristics and detector response
Publication contributions: Collaborated within a leading research group on peer-reviewed physics publications

Education

My education combined rigorous physics training with strong international exposure and technical breadth. Early coursework in mathematics, programming (Python, MATLAB), and computational methods provided a foundation for later specialisation in particle physics and data analysis techniques.

PhD in Particle Physics | Universidad de Cantabria

Sep 2019 - Mar 2025 | Santander, Spain / Geneva, Switzerland

Thesis: "Search For Supersymmetric Particle Pair Production In Final States With Two Oppositely Charged Leptons And Large Missing Transverse Momentum In Proton-proton Collisions At 13 TeV"
Supervisor: Luca Scodellaro | Cum laude

Beyond the Standard Model physics search: Searched for evidence of supersymmetric particles in CMS collision data; placed the strictest constraints to date on SUSY models, narrowing viable theoretical parameter space
Large-scale data analysis: Processed collision datasets using statistical modelling, machine learning, Monte Carlo simulations, and distributed computing across clusters (Python, C++, ROOT)
International research: Spent 3-4 months annually at CERN; presented findings at several conferences across Europe and North America; published peer-reviewed articles

M.Sc. in Particle Physics | Universidad de Cantabria

Sep 2017 - Sep 2018 | Santander, Spain / Zurich, Switzerland

Thesis: "Higgs production cross section at 13 TeV and prospects on BSM searches for the HL-LHC"

Master thesis research: Improved precision of Higgs production cross-section measurements and conducted Monte Carlo sensitivity studies for HL-LHC detector upgrades, combining research conducted at Universidad de Cantabria and University of Zurich
Technical skill development: Developed expertise in machine learning, Python, and R programming alongside core particle physics coursework

B.A.Sc. in Physics | Universidad de Cantabria

Sep 2013 - Jun 2017 | Santander, Spain / London, UK / Pittsburgh, USA

Bachelor thesis research: Conducted ATLAS detector particle physics analysis using Monte Carlo simulations; provided first exposure to C/C++, ROOT, and experimental high-energy physics methods. Complemented core physics coursework with mathematics, philosophy, and programming (Python, MATLAB)

International Exchanges

During my Bachelors and Masters, I also participated in several exchange programs that enhanced my international perspective, including:

Erasmus+	University College London, UK	(Sep 2015 - Jun 2016)
	University of Zurich, Switzerland	(Jul 2018 - Jul 2019)
USA Exchange	University of Pittsburgh, USA	(Aug 2015 - May 2016)

CERN Summer Student | Geneva, Switzerland | Jun – Sep 2017

Participated in the CERN Summer Student Programme, which combined specialised lectures from leading scientists with hands-on project work. Worked with the RD50 R&D group developing automated analysis for silicon sensor testing results ( Capacity-Voltage and Current-Voltage measurements).

Summer Schools

Participated in specialised summer schools advancing expertise in particle physics, machine learning, and quantum computing:

Baltic School of High-Energy Physics and Accelerator Technologies | Latvia, Summer 2021 | 35 hours
Seventh Summer School on Machine Learning in High Energy Physics | Remote, Summer 2021 | 92 hours
Focused on latest machine learning algorithms and their application to particle physics
BENASQUE TAE 2022 – International Workshop on High Energy Physics | Spain, Summer 2022 | 60 hours
Ciencia y Tecnologías Cuánticas | Spain, Summer 2025 | 20 hours
Summer course on foundations of quantum computing instructed by Ignacio Cirac

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