Data Science & Complexity in Fundamental Physics and the bridge to industry & society

Jun 8, 2026, 9:00 AM → Jun 12, 2026, 6:00 PM Europe/Zurich

Instituto Galego de Física De Altas Enerxías (IGFAE)

ALBA MARTINEZ MIRAS, Cristina Cabo, Lorenzo Cazon (IGFAE-USC), MANUEL REY PAN (IGFAE)

An event that explores the highly demanded field of Data Science in modern society, and creates links with the industry

The conference will take place from 8 to 12 June, 2026, in Santiago de Compostela (Galicia, Spain)

School (8-10 June): Intensive course on Probability, Statistics, Machine Learning and Complexity, focused on PhD students and postdoctoral research staff. The sessions will be led by Glen Cowan (Professor of Physics at the Royal Holloway in London) and Eddie Lee (researcher at the Complexity Science Hub in Vienna).

Symposium (11-12 June): The school will be followed by a symposium focusing on the relationship between fundamental physics and industry, with data science as the nexus.

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Confirmed companies: Anaxa, Bahia Software, CESGA, Clarity AI, Finsa, ITG, FSAS - Fujitsu, Google, Gradiant, Inditex, ITG, Mestrelab, Meta, Navantia, Novartis, Plexus Tech, Quantum Spain, SDG Group.

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During these days, more than 20 representatives from companies and research centres will discuss and share knowledge about the latest trends in the sector, the demands, and practical applications of data science in everyday life.

The event aims to demonstrate the career opportunities within fundamental physics and its synergies with the job market and modern society’s needs. It will include a school covering Data Science techniques used in High Energy Physics (HEP), Nuclear, Astroparticle, and Fundamental Physics, alongside a symposium where companies present their current trends, needs, and daily work related to Data Science.

Additionally, the event intends to establish communication channels with the industry to explore partnerships, joint projects, and international grant opportunities. It will also highlight IGFAE’s research capabilities in Nuclear, High Energy, AstroParticle, and Fundamental Physics in the field of Data Science. By bringing together both sides, this event will create a framework for mutual knowledge exchange and enable the development of practical synergies from Data Science in fundamental physics to Data Science in the industry.

 

Mon, June 8

9:30 AM → 11:15 AM Day 1: Probability & Statistics (Glen Cowan)

11:15 AM → 11:45 AM Coffee break

11:45 AM → 1:30 PM Day 1: Complexity (Eddie Lee)

1:30 PM → 3:00 PM Lunch break

3:00 PM → 5:30 PM Day 1: Hands-on

Tue, June 9

9:30 AM → 11:15 AM Day 2: Probability & Statistics (Glen Cowan)

11:15 AM → 11:45 AM Coffee break

11:45 AM → 1:30 PM Day 2: Complexity (Eddie Lee)

1:30 PM → 3:00 PM Lunch break

3:00 PM → 5:30 PM Day 2: Hands-on

Wed, June 10

9:30 AM → 11:15 AM Day 3: Probability & Statistics (Glen Cowan)

11:15 AM → 11:45 AM Coffee break

11:45 AM → 1:30 PM Day 3: Complexity (Eddie Lee)

1:30 PM → 3:00 PM Lunch break

3:00 PM → 5:30 PM Day 3: Hands-on

Thu, June 11

9:00 AM → 9:30 AM Welcome by USC & IGFAE representatives

Speakers: Prof. Almudena Hospido (USC), Carlos Albert Salgado Lopez (Universidade de Santiago de Compostela (ES))

9:30 AM → 10:00 AM An Overflight of Statistical Methods in High Energy Physics

Statistical methods have for many years played a crucial role in fundamental research such as High Energy Physics, and in the recent Big Data era their importance has continued to increase. I will give a bird's-eye view of the most important tools used to compare theory and experiment in a way that extracts the maximum information from the hard-won data. The talk will touch on foundational questions of statistics and the scientific method, standard tools for used in searches for new phenomena, and the path to the future with modern methods from Machine Learning and Artificial Intelligence.

Speaker: Glen Cowan (Royal Holloway, University of London)

10:00 AM → 10:30 AM When physics meet life

What are complex systems and why do we care about them? The greatest open problems in physics are life at the mesoscale, an understanding of ourselves and the world in which we live. These include the ecosystems in which we are embedded to the higher-order complexities of global society, and such contemplation raises questions about ramifications of such a science and about the role of physicists in its development.

Speaker: Dr Eddie Lee (Complexity Science Hub)

10:30 AM → 11:00 AM TBD (Gregorio Gonzalez Saavedra)

TBD

Speaker: Gregorio González Saavedra (Finsa (Financiera Maderera S.A.))

11:00 AM → 11:30 AM Coffee break

11:30 AM → 12:00 PM TBD (Alejandro Borrallo Rentero)

TBD

Speaker: Jacobo Padin Martinez (Fsas Technologies - a Fujitsu company)

12:00 PM → 12:30 PM Using tools for solving problems

Generating knowledge from data involves more than simply using specific tools such as statistics, machine learning, or simulation. Its true value lies in the ability to transform data into useful information: formulating relevant questions, developing models, assessing uncertainties, and making evidence-based decisions.

Speaker: Dr Ana Garbayo Peon (ITG Technology)

12:30 PM → 1:00 PM Inditex AI Multi-Agent Ecosystem

Inditex’s multi-agent system is a next-generation AI platform designed to deliver smarter, faster, and more specialized support across the business. By combining multiple expert agents instead of relying on a single model, it turns every request into a more precise, scalable, and high-value interaction. I’m part of that ecosystem, orchestrating each conversation so the right capability is activated at the right moment.

Speaker: Dr Javier Diaz Cortes (Inditex)

1:00 PM → 2:30 PM Lunch break

2:30 PM → 3:00 PM TBD (Albert Puig Navarro)

TBD

Speaker: Albert Puig Navarro (Anaxa)

3:00 PM → 3:30 PM TBD (Maria Pereira Martinez)

TBD

Speaker: Maria Pereira Martinez (IGFAE)

3:30 PM → 4:00 PM TBD (Antonio Torrado Gonzalez)

TBD

Speaker: Antonio Torrado Gonzalez (SDG Group Iberia)

4:00 PM → 4:30 PM Coffee break

4:30 PM → 5:00 PM Modeling Human Uncertainty: Predictive Attrition Risk and Pay Equity Through Applied People Analytics

"People Analytics has emerged as a pragmatic application of data science to socio-technical systems in which human behavior, incentives, and organizational structures interact in complex ways. This talk presents two applied modeling problems that illustrate both the potential and the limitations of quantitative approaches when the subjects of analysis are people rather than physical or purely transactional systems.

The first case explores the probabilistic estimation of voluntary attrition risk among high-potential employees over a six-month horizon. Rather than treating attrition as a deterministic outcome, the problem is framed as probability estimation intended to support decision-making under uncertainty. The discussion focuses on problem formulation, data considerations, model choice, and the practical interpretation of predicted probabilities in organizational contexts.

The second case examines the use of multivariate linear regression models for pay equity analysis. Although methodologically simple, this application raises important questions around model specification, interpretation of coefficients, and the communication of results to non-technical stakeholders. The talk emphasizes how statistical outputs are translated into actionable insights while operating under legal, ethical, and organizational constraints.

Taken together, these two use cases position People Analytics as a domain where standard statistical and machine learning tools are embedded in complex adaptive systems. The models are not presented as definitive answers, but as decision-support instruments whose value depends on context, governance, and an explicit acknowledgment of uncertainty and human agency."

Speaker: Dr Miguel Escalona-Moran

5:00 PM → 5:30 PM The Scientific Mindset in Industrial Data Science: From Fundamental Research to Societal Impact

A PhD in physics provides a unique and powerful foundation for industrial data science, reaching far beyond technical expertise alone. The core competencies developed during fundamental research—critical thinking, self-directed learning, and a deep-seated intellectual rigor—translate directly to high-stakes environments where problems are rarely well-defined.

In the current AI landscape, technical proficiency has become a baseline expectation rather than a differentiator. The true value of a scientific background now lies in the ability to apply a scientific mindset to elusive questions that must be navigated with imperfect data. At Clarity AI, this manifests as a commitment to innovation, leveraging advanced modeling architectures to transform noisy, unstructured data into reliable insights that drive societal impact.

Speaker: Luis Reyes Navarrete (Clarity AI)

5:30 PM → 6:00 PM Quantum Data Encodings: Opportunities for High Energy Physics in the NISQ Era

High Energy Physics experiments generate increasingly large and complex datasets, ranging from detector hits and particle tracks to reconstructed particles and full collision events. In the current NISQ era, quantum computing is not yet expected to outperform classical approaches for most practical applications; however, it offers novel methods for representing and processing high-dimensional information through quantum data encodings.
This talk presents several High Energy Physics use cases to illustrate how quantum encoding techniques can capture correlations and geometric structures present in experimental data while providing compact representations of complex feature spaces.
The discussion will focus on the opportunities and challenges of quantum data encodings for scientific machine learning, highlighting their potential role in future quantum algorithms for increasingly complex High Energy Physics analyses. Particular attention will be given to how quantum representations may contribute to addressing scalability challenges as detector complexity and data volumes continue to grow.

Speaker: Irais Bautista Guzman (CESGA)

6:00 PM → 6:30 PM Reimagine Business Finance with AI

" Artificial intelligence is transforming the role of Finance from a function focused on reporting, planning cycles, and negotiation-heavy processes into a strategic partner capable of generating faster, more objective, and more actionable business insights.
This session explores how AI can be applied to reimagine business finance, using practical examples from digital finance transformation in the pharmaceutical industry. It will show how traditional financial planning processes (often highly iterative and resource-intensive) can be transformed into data-driven planning, multi-scenario forecasting or advanced resource allocation."

Speaker: Marc Grabalosa Gandara (Novartis)

7:00 PM → 8:30 PM Social event / Dinner

Fri, June 12

9:00 AM → 9:30 AM TBD (Sara Sellam)

TBD

Speaker: Dr Sara Sellam (Mestrelab)

9:30 AM → 10:00 AM Quantum Machine Learning: How Quantum Computing can enhance classical Machine Learning

Quantum computing has the potential to improve machine learning approaches and unlock new solutions that go beyond the capabilities of classical ML systems. However, fully leveraging this potential requires a clear understanding of the complexities of these models, as well as the adaptation of software so that it can be natively integrated into HPC centers.

Speaker: Diego Beltran Fernandez Prada (Bahia Software)

10:00 AM → 10:30 AM TBD (Yago Gonzalez Rozas)

TBD

Speaker: Yago Gonzalez Rozas (Plexus Technologies)

10:30 AM → 11:00 AM Data science applied to astrophysics: a view within IGFAE

Astrophysical phenomena are rich in information, and increasingly advanced statistical methods are required to extract the relevant data from the noise. The area of Theoretical Astrophysics and Cosmology at IGFAE has a leader contribution in the main observatories across the world, and is actively developing and applying data science techniques in a variety of contexts. In this talk I will present four different examples from our recent work, with an emphasis on the techniques used.

Speaker: Dr Marta Reina (IGFAE)

11:00 AM → 11:30 AM Coffee break

11:30 AM → 12:00 PM From data to ship: AI and Digital Twins

" This presentation addresses how Data Science and Artificial Intelligence are transforming the naval industry, using the development of Digital Twins as the connecting thread and enabling infrastructure. Real-world cases developed at Navantia will be presented, connecting them to the mathematical and statistical foundations of Data Science. The topics covered will be:

    The industrial data challenge in complex naval platforms: Characteristics of operational data in ships and naval systems (non-sensitive).
    AI-oriented Digital Twin architecture: Technology stack (OPC-UA, Node-RED, InfluxDB, MLflow, ONNX Runtime) and DT-Ready architecture for making ML models deployable in OT environments. Digital twin of a cooling system (Unit Cooler).
    Physics-Informed data-driven models: Strategies for incorporating domain knowledge (heat transfer equations, vibration dynamics) into neural networks, reducing data requirements."

Speaker: Dr Ruben Ferreiroa Garcia (Navantia)

12:00 PM → 12:30 PM TBD (Miguel Ferreira Cao)

TBD

Speaker: Dr Miguel Ferreira Cao (Gradiant)

12:30 PM → 1:00 PM Transitioning from a PhD in the LIGO Scientific Collaboration to a Google Sales Account Executive: Exploring Career Paths for Physics PhDs

TBD

Speaker: Miquel Trias Cornellana (Google)

1:00 PM → 1:30 PM Statistics in the software industry: bridging the gap between science and applications

We will discuss the challenges of applying statistics concepts in the software development industry, connecting them to science and reports from other disciplines. Using real-life examples, we will analyze the statistician's role as a product owner, as a service provider and as a "pure stats developer." We will focus on when the data scientist should adopt each role to achieve a fruitful and productive interaction with colleagues.

Speaker: Pablo Alcain