Prof. Dr. Jonathan Costa
Jonathan leads the MSc in Sustainability, Innovation, and Technology and oversees research strategy. His work spans AI for Sustainability, applied machine learning, and digital education.

Biography
Prof. Dr. Jonathan Costa is the Vice President of Research and Program Director for the MSc in Sustainability, Innovation, and Technology at Tomorrow University of Applied Sciences. With a background in high-energy physics and a PhD from Imperial College London, he combines academic rigor with a passion for learner-centered, interdisciplinary education. He previously led the BSc in AI & Sustainable Technologies and has designed programs that integrate sustainability, innovation, and emerging technologies. As a professor of Data Science & AI, he empowers learners to apply cutting-edge tools to real-world challenges and prepares them to drive meaningful change in business, policy, and society.
Previously Worked For
Research Profile
Prof. Dr. Jonathan Costa’s research spans multiple scientific domains, including solar physics, soil physics, and high-energy particle physics. His early work at Imperial College London and CERN advanced the analysis of collider data and the search for dark matter, contributing to our understanding of fundamental particles and the structure of the universe. In parallel, he has explored solar phenomena and space weather, as well as conducted applied research in soil physics—studying mass attenuation coefficients and bulk density to inform sustainable agriculture and environmental science. Now leading Tomorrow University’s research agenda, Dr. Costa focuses on the intersection of AI, sustainability, and innovation, fostering interdisciplinary collaboration through projects with partners like Fraunhofer AHEAD. His work continues to bridge theory and application, guiding scalable, impact-driven research that addresses global challenges.

List of Papers
- Global analysis of dark matter simplified models with leptophobic spin-one mediators using MasterCode - The European Physical Journal C · Nov 1, 2019
- Likelihood analysis of the pMSSM11 in light of LHC 13-TeV data - The European Physical Journal C · Mar 1, 2018
- Likelihood analysis of the sub-GUT MSSM in light of LHC 13-TeV data - The European Physical Journal C · Feb 1, 2018
- Likelihood analysis of the minimal AMSB model - The European Physical Journal C · Apr 1, 2017
- Likelihood analysis of supersymmetric SU(5) GUTs - The European Physical Journal C · Feb 1, 2017
- Soil mass attenuation coefficient: Analysis and evaluation - Annals of Nuclear Energy, Feb, 2014
- Representative Elementary Length to Measure Soil Mass Attenuation Coefficient - The Scientific World Journal, Jan 2014
- Soil bulk density evaluated by gamma-ray attenuation: Analysis of system geometry - Soil and Tillage Research, May 2013
- Effect of collimator size and absorber thickness on soil bulk density evaluation by gamma-ray attenuation Radiation - Physics and Chemistry, Nov 2012
Professional Community Services
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Talks
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Thesis Supervised
Teaching at Tomorrow University
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Programs
Skills You Can Learn
Problem Solving with Data
Data Visualization
Storytelling with Data
Data Products
Introduction to Cognitive Systems and Neuroscience
Data Solutions
Ethics and Economics of AI
Human-AI Collaboration
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