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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 - 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 31
- Machine Learning for Energy Performance Prediction in Early Design Stage of Buildings(2020)
Authors: Sundar Singaravel, Philipp Geyer, Hans Janssen, Johan Suykens
- Uncertainty Analysis of Life Cycle Energy Assessment in Early Stages of Design(2020)
Authors: Manav Mahan Singh, Philipp Geyer
- Information requirements for multi-level-of-development BIM using sensitivity analysis for energy performance(2019)
Authors: Manav Mahan Singh, Philipp Geyer
Pages: 1 - 8 - Deep convolutional learning for general early design stage prediction models(2019)
Authors: Sundar Singaravel, Johan Suykens, Philipp Geyer
- Economic Evaluation and Simulation for the Hasselt Case Study: Thermochemical District Network Technology vs. Alternative Technologies for Heating(2019)
Authors: Muhannad Delwati, Ahmed Ammar, Philipp Geyer
Pages: 1 - 26 - Component-based machine learning for performance prediction in building design(2018)
Authors: Philipp Geyer, Sundar Singaravel
Pages: 1439 - 1453 - Information Exchange Scenarios between Machine Learning Energy Prediction Model and BIM at Early Stage of Design(2018)
Authors: Manav Mahan Singh, Sundar Singaravel, Philipp Geyer
Pages: 487 - 494 - Deep Learning Neural Networks Architectures and Methods: Building Design Energy Prediction by Component-Based Models(2018)
Authors: Sundar Singaravel, Johan Suykens, Philipp Geyer
Pages: 81 - 90 - Use cases with economics and simulation for thermo-2 chemical district networks(2018)
Authors: Philipp Geyer, Muhannad Delwati, Martin Buchholz, Alessandro Giampieri, Andrew Smallbone, Antony Roskilly, Reiner Buchholz, Provost Mathieu
Pages: 1 - Use cases with economics and simulation for thermo-2 chemical district networks(2018)
Authors: Philipp Geyer, Muhannad Delwati
Pages: 1