01⌁
Machine Learning
& Deep Learning
Predictive modelling, neural architectures and data-driven methods for structured, tabular and image data.
DATA SCIENCE · MACHINE LEARNING · APPLIED AI
Turning data into
meaningful intelligence.
I'm Víctor Toscano Durán, a Data Scientist and AI Researcher with a background in Statistics. I work at the intersection of machine learning, topological data analysis and real-world applications — particularly in healthcare.
∑DATA
×
STRUCTURE
×
STRUCTURE
CURRENT FOCUSNeurovascular
AI research↗
AI research↗
RESEARCH TOOLKITML · TDA · XAI
Víctor Toscano DuránSeville, Spain+
+
BASED IN SEVILLE, SPAINSCROLL TO EXPLORE ↓OPEN TO RESEARCH COLLABORATIONS
01 / PROFILE
From statistical foundations to intelligent systems — combining rigorous analysis, computational methods and practical engineering to solve complex problems.
A LITTLE ABOUT ME01
Curiosity driven.
Evidence led.
I am a statistician specialised in Artificial Intelligence, currently working as a researcher in a Neurovascular Research Group. My work brings together statistical analysis, machine learning and deep learning to support research in stroke and healthcare.
My research path has also taken me into computational topology, explainable AI and energy-aware machine learning. I enjoy moving between theory and implementation: understanding the structure behind data, building models, communicating results and turning methods into usable applications.
I hold a Bachelor's Degree in Statistics and a Master's Degree in Logic, Computation and Artificial Intelligence, both from the University of Seville.
2023—25REXASI-PRO researcher
2025Research stay · AIDOS Lab
75%Less training data in a research study
WHAT I WORK ON02
Research & expertise
Connecting mathematical ideas, machine learning methods and applications with real impact.
Machine Learning
02◌
Topological
Data Analysis
Persistent entropy, Euler Characteristic Transforms and topological representations for learning and data analysis.
03◎
Explainable &
Trustworthy AI
Interpretable models, reliability assessment and topological safety regions for complex decision systems.
04✳
Healthcare
& Medical AI
Applying statistical learning and AI to clinical research, neurovascular studies and computational healthcare.
05⌘
Data Applications & Engineering
From data preparation and analysis to interactive dashboards, research applications and deployment. I am also expanding this engineering layer through containerised workflows and self-hosted services.
SELECTED SCIENTIFIC OUTPUT03
Selected publications
A selection of peer-reviewed work, conference contributions and preprints. See my academic profiles for the complete record.
2026
JOURNAL · EUROPEAN STROKE JOURNAL
↗Validation of a machine learning model to predict patient clinical outcome 90 days after stroke
V. Toscano-Duran et al. · European Stroke Journal, 11(Supplement 1), i647–i648.
2026
BOOK CHAPTER · MOLECULAR MACHINE LEARNING
↗Molecular machine learning using Euler characteristic transforms
V. Toscano-Duran, F. Rottach & B. Rieck · pp. 391–405.
2025
BOOK CHAPTER · EXPLAINABLE ARTIFICIAL INTELLIGENCE
↗Safe and efficient social navigation through explainable safety regions based on topological features
V. Toscano-Duran et al. · Springer Nature Switzerland, pp. 396–421.
2025
PREPRINT · arXiv
↗Barycentric neural networks and length-weighted persistent entropy loss: A green geometric and topological framework for function approximation
V. Toscano-Duran, R. Gonzalez-Diaz & M. Á. Gutierrez-Naranjo.
2025
JOURNAL · OPEN RESEARCH EUROPE
↗Topology-based analysis and optimization for agent fleet behavior
J. Perera-Lago, V. Toscano-Duran et al. · Open Research Europe, 5:200.
2024
JOURNAL · OPEN RESEARCH EUROPE
↗An in-depth analysis of data reduction methods for sustainable deep learning
J. Perera-Lago, V. Toscano-Duran et al. · Open Research Europe, 4:101.
WHERE I'VE BEEN04
Experience & education
Research, industry and academic training — building a multidisciplinary perspective on data and AI.
NOV 2025 — NOW
RESEARCH
Researcher · Neurovascular Research Group
Working at the intersection of data analysis and machine learning applied to stroke. Statistical analysis, reports and visualisations for medical teams, application and dashboard development, and training, validation and deployment of ML and deep learning models.
DEC 2023 — OCT 2025
RESEARCH · UNIVERSITY OF SEVILLE
Researcher · Department of Applied Mathematics I
Worked on machine learning, energy optimisation and applied topology within the European REXASI-PRO project. Reduced training data volume by 75% while maintaining accuracy; developed topological metrics for dataset representativeness and persistent-entropy-based analysis of robot fleets and explainable safety regions.
APR — JUN 2025
RESEARCH STAY · AIDOS LAB
University of Freiburg
Collaboration with Prof. Dr. Bastian Rieck on topological tools in medical computing. Developed an Euler Characteristic Transform-based molecular descriptor for molecular learning tasks.
OCT 2024
RESEARCH STAY · CNR-IEIIT
Consiglio Nazionale delle Ricerche · Genoa
Collaboration with Dr. Maurizio Mongelli and his team on topology and explainable AI, developing approaches to define efficient safety regions for safe and unsafe simulations.
DEC 2022 — DEC 2023
INDUSTRY · GLUCUBE
Data Scientist
Developed and validated deep learning models (RNN, CNN and Transformers) for blood glucose prediction, alongside data preprocessing, visualisation and SQL-based ETL.
SEP — DEC 2022
INDUSTRY · SOLERA
Software Developer
Implemented Python software modules and automated test suites to improve product reliability.
JAN — MAR 2022
HEALTH RESEARCH · FISEVI
Data Science Intern
Supported clinical data analysis through statistical techniques, reports and visualisations for medical teams.
RESEARCH GROUPS & PROJECTS
2025 — NOW
AIDOS Lab
Research team member
2023 — NOW
Combinatorial IMage Analysis Group (CIMAgroup)
Research team member
2023 — 2025
REXASI-PRO · European project
Reliable & Explainable Swarm Intelligence for People with Reduced Mobility · Grant Agreement 101070028
2023 — 2024
Green AI and computational topology
TED2021-129438B-I00 · Energy saving and optimisation of deep learning methods
EDUCATION & TRAINING
2022 — 2023
MSc · Logic, Computation and Artificial Intelligence
University of Seville
2018 — 2022
BSc · Statistics
University of Seville
JUN 2025
Statistical Optimal Transport Workshop
SLMath · Berkeley, California
JUN 2024
GATMAID EMS Summer School
Centre de Recerca Matemàtica · Barcelona
TOOLS OF THE TRADE05
Technical toolkit
A practical stack shaped by research, modelling and application development.
PROGRAMMING
PythonRSQL
ML & DATA
PyTorchTensorFlowKerasScikit-learnNumPyPandas
APPLICATIONS & VISUALISATION
DashShinyPower BIMatplotlib
DATABASES & WORKFLOW
PostgreSQLMySQLGitJupyterAmazon SageMakerGoogle Colab
DEPLOYMENT LAYER
DockerDocker ComposeLinuxReverse proxyHTTPS
Containerisation and self-hosted deployment are part of the engineering direction of this portfolio. Add links to concrete deployments as you publish them.
BEYOND THE PAPERS06
Talks, awards & mentoring
Sharing research through conferences, seminars and academic supervision.
2025
ECML-PKDD · Mining and Learning with Graphs
Poster presentation on topological molecular representations based on the Euler Characteristic Transform.
2025
CIBB & TDA2025
Conference poster on molecular machine learning and a talk on interpolation and function approximation using neural networks and barycentric coordinates.
2025
Scuola di Robotica · Genoa
Seminar: Topological Data Analysis for data analysis and AI in robotics.
2024
World Conference on Explainable AI
Oral presentation and doctoral consortium poster on reliable decision trees and unseen vehicle collision data.
2024—26
Academic supervision
Co-directed final degree projects in medical imaging, radiomics, oncology and machine learning, with marks between 9.0 and 9.5.
CERTIFICATES
NVIDIA Deep Learning Institute
Fundamentals of Accelerated Data Science · Fundamentals of Deep Learning.
HAVE AN IDEA OR A PROJECT?
Let's make
Let's make
something meaningful.
I'm always happy to connect with researchers, practitioners and people working on interesting problems in data science and AI.
Get in touch ↗