Daniel Garcelán
Senior Data Scientist
Madrid, Community of Madrid, Spain
Summary
👤
Senior🎓
Top SchoolDaniel Garcelán is a Senior Data Scientist and researcher with a PhD in Computer Science and six years’ experience applying ML to climate, health insurance, and industrial problems from Madrid. He leads IE’s Climate Change Effects on Life & Health Insurance initiative, combining DLNMs, relative risk modeling and novel Kolmogorov–Arnold Networks to translate climate-driven hazards into pricing and risk strategies while building interactive Flask dashboards for decision-makers. As an adjunct professor he teaches applied mathematics, time series and responsible use of AI assistants, and as COO of Canonical Green he operationalizes data-driven AI and optimization for Industry 4.0 clients. His background spans academic-industry collaborations with Airbus and Komorebi AI, practical deployments (Streamlit/Flask) and publications, reflecting a rare mix of theoretical rigor and production-facing delivery. Notably, his Github focus on “Data Science for the Blue Economy” underscores a recurring interest in marine and environmental applications beyond conventional enterprise use cases.
6 years of coding experience
4 years of employment as a software developer
PhD, Computer Science, Cum Laude, International, PhD, Computer Science, Cum Laude, International at Cádiz UniversityDegree, Physics, Degree, Physics at Complutense University of MadridMaster of science, Statistical and Computational Information Processing, Master of science, Statistical and Computational Information Processing at Universidad Politécnica de Madrid
Spanish, English
Github Skills (36)
monitoring10
pytorch10
gru10
convolutional-neural-networks10
load-data10
classification10
energy10
recurrent-neural-networks10
algorithms9
python9
tensorflow9
neural-network9
deep-learning9
forecasting9
forecast9
Programming languages (3)
Github contributions (5)
UCA-Datalab/covid-npi
Feb 2021 - May 2022
Non-pharmaceutical interventions during COVID
Contributions:6 releases, 15 PRs, 299 pushes in 1 year 3 months
interventionsespanolcovid-npi
UCA-Datalab/covid_occupancy_simulation
Apr 2020 - Apr 2020
Predict future hospital admissions and simulate the number of beds occupied.
Contributions:5 PRs, 121 pushes, 16 branches in 11 days
pythonhospitalmachine-learningoccupiedpredict
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