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Researcher
Philipp Geyer
- Disciplines:Architectural engineering, Architecture, Interior architecture, Architectural design, Art studies and sciences
Affiliations
- Design and Engineering of Construction and Architecture (Division)
Member
From1 Aug 2020 → 30 Sep 2021 - Department of Architecture (Department)
Member
From1 Oct 2019 → 31 Jul 2020 - Architectural Engineering (Division)
Member
From1 Oct 2014 → 31 Jul 2020
Projects
1 - 8 of 8
- Early Stage Design Support using Machine Learning and Building Information ModellingFrom29 Mar 2018 → 29 Mar 2022Funding: BOF - doctoral mandates
- Model and simulate a novel thermo-chemical district networks based on lab dataFrom14 Dec 2017 → 11 Oct 2021Funding: Own budget, for example: patrimony, inscription fees, gifts
- System-based simulation of energy flowsFrom1 May 2017 → 30 Apr 2020Funding: Foreign private sponsor - undefined
- Intelligent Hybrid Thermo-Chemical District NetworksFrom1 Jun 2016 → 31 May 2019Funding: H2020-EU.3.3. - SOCIETAL CHALLENGES - Secure, clean and efficient energy
- Machine Learning for Energy Performance Prediction in Early Design Stage of BuildingsFrom2 Dec 2015 → 21 Feb 2020Funding: Own budget, for example: patrimony, inscription fees, gifts
- H-DisNet : Hybrid Thermal and Thermochemical District Networks.From1 Mar 2015 → 31 Dec 2018Funding: BOF - Bilateral scientific cooperation
- Metamodels for Systems Engineering to Support Sustainable Building Design.From1 Oct 2014 → 30 Sep 2019Funding: BOF - tenure track
- Metamodels for Systems Engineering to Support Sustainable Building Design.From1 Oct 2014 → 30 Sep 2016Funding: BOF - Other initiatives
Publications
1 - 10 of 32
- Machine Learning for Energy Performance Prediction in Early Design Stage of Buildings(2020)
- Uncertainty Analysis of Life Cycle Energy Assessment in Early Stages of Design(2020)Published in: Energy and BuildingsISSN: 0378-7788Issue: 1 February 2020Volume: 208
- Information requirements for multi-level-of-development BIM using sensitivity analysis for energy performance(2019)Published in: Advanced Engineering InformaticsISSN: 1474-0346Volume: 43Pages: 1 - 8
- Deep convolutional learning for general early design stage prediction models(2019)Published in: Advanced Engineering InformaticsISSN: 1474-0346Volume: 42
- Economic Evaluation and Simulation for the Hasselt Case Study: Thermochemical District Network Technology vs. Alternative Technologies for Heating(2019)Published in: EnergiesISSN: 1996-1073Issue: 7Volume: 12Pages: 1 - 26
- Component-based machine learning for performance prediction in building design(2018)Published in: Applied EnergyISSN: 0306-2619Volume: 228Pages: 1439 - 1453
- Information Exchange Scenarios between Machine Learning Energy Prediction Model and BIM at Early Stage of Design(2018)Pages: 487 - 494
- Deep Learning Neural Networks Architectures and Methods: Building Design Energy Prediction by Component-Based Models(2018)Published in: Advanced Engineering InformaticsISSN: 1474-0346Volume: 38Pages: 81 - 90
- Use cases with economics and simulation for thermo-2 chemical district networks(2018)Published in: SustainabilityISSN: 2071-1050Issue: 1Volume: 1Pages: 1
- Use cases with economics and simulation for thermo-2 chemical district networks(2018)Published in: SustainabilityISSN: 2071-1050Issue: 1Volume: 1Pages: 1