Personlig profil
Forskningsområder
Data science, Explainable AI, Industrial digitalization, Energy informatics
Research Interests
His research mainly focuses on data intelligence in complex systems, such as clustering, causal inference, data understanding, and pattern discovery. He develops machine learning and deep learning approaches to support analysis and decision-making in industrial and sensor-based environments, with a particular focus on reducing energy consumption in industry sectors through data-driven methodologies.
Emneord
- Produktionssystemer i industri
- Industrial Digitalization
- Energy Informatics
- Industry 4.0
- Maskinlæring
- Data Science
- Explainable AI
- Decision Support Systems
Fingeraftryk
- 1 Lignende profiler
Samarbejde og topforskningsområder i de sidste fem år
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Artificial Intelligence-Driven Decision Support Framework for Improving Energy Efficiency in Industry and Transportation
Ma, Z. M., 14. jan. 2026, Syddansk Universitet. Det Tekniske Fakultet. 271 s.Publikation: Afhandling › Ph.d.-afhandling
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An Automated Domain-Agnostic and Explainable Data Quality Assurance Framework for Energy Analytics and Beyond
Tolnai, B. A., Ma, Z. M., Jørgensen, B. N. & Ma, Z. G., 26. sep. 2025, I: Information. 16, 10, 34 s., 836.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
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Data-Driven Causal Reasoning for Eco-Driving Behavior Analysis in Public Transportation Systems
Ma, Z., Jørgensen, B. N. & Ma, Z. G., 5. maj 2025, (Afsendt) I: Complex & Intelligent Systems.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
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Data-Driven Digital Twin Based Energy Flexibility Investigation for Commercial Greenhouse Production Process
Howard, D. A., Værbak, M., Ma, Z. M., Jørgensen, B. N. & Ma, Z. G., 2025, Progress in Artificial Intelligence: 23rd EPIA Conference on Artificial Intelligence, EPIA 2024, Viana do Castelo, Portugal, September 3–6, 2024, Proceedings, Part I. Santos, M. F., Machado, J., Novais, P., Cortez, P. & Moreira, P. M. (red.). Springer Nature, s. 193-205 (Lecture Notes in Computer Science, Bind 14967).Publikation: Kapitel i bog/rapport/konference-proceeding › Konferencebidrag i proceedings › Forskning › peer review
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Data-Driven Digital Twin for Foundry Production Process: Facilitating Best Practice Operations Investigation and Impact Analysis
Howard, D. A., Værbak, M., Ma, Z., Jørgensen, B. N. & Ma, Z., 2025, Energy Informatics: 4th Energy Informatics Academy Conference, EI.A 2024, Kuta, Bali, Indonesia, October 23–25, 2024, Proceedings, Part I. Jørgensen, B. N., Ma, Z. G., Wijaya, F. D., Irnawan, R. & Sarjiya, S. (red.). Springer Science+Business Media, s. 259-273 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bind 15271 LNCS).Publikation: Kapitel i bog/rapport/konference-proceeding › Konferencebidrag i proceedings › Forskning › peer review
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Driver Coach
Jørgensen, B. N. (PI), Ma, Z. G. (Co-PI) & Ma, Z. M. (Projektdeltager)
01/02/2022 → 30/09/2026
Projekter: Projekt › Forskning
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DECODE: Data-driven best-practice for energy-efficient operation of industrial processes
Ma, Z. G. (PI), Jørgensen, B. N. (Co-PI) & Ma, Z. M. (Projektdeltager)
01/09/2022 → 31/08/2026
Projekter: Projekt › Forskning
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IEA IETS Annex Task XVIII: Danish participation in IEA IETS Annex Task XVIII - Digitization, artificial intelligence and related technologies for energy efficiency and reduction of greenhouse gas emissions in industry
Ma, Z. G. (Projektleder), Ma, Z. M. (Projektdeltager), Clausen, C. S. B. (Projektdeltager), Værbak, M. (Projektdeltager) & Schwarz, H. (Projektdeltager)
01/07/2021 → 31/12/2024
Projekter: Projekt › Forskning