Publications de Roberto Castello

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Tepotinib is approved for the treatment of patients with non-small-cell lung cancer harboring MET exon 14 skipping alterations. While edema is the most prevalent adverse event (AE) and a known class effect of MET inhibitors including tepotinib, there is st ...

Currently, more than half of the world’s population lives in cities, which leads to major changes in land use and land surface temperature (LST). The associated urban heat island (UHI) effects have multiple impacts on energy consumption and human health. A ...

The increasing use of ground-source heat pumps (GSHPs) for heating and cooling of buildings raises questions regarding the technical potential of GSHPs and their impact on the temperature in the shallow subsurface. In this paper, we develop a method using ...

The large-scale deployment of photovoltaics (PV) on building rooftops can play a significant role in the transition to a low-carbon energy system. To date, the lack of high-resolution building and environmental data and the large uncertainties related to e ...

Resolving the wind profile in an urban canyon environment means dealing with the turbulent nature of the stream and the presence of non-negligible flux exchanges with the atmosphere inside the canopy, making any deterministic model solution computationally ...

In the context of a rapid and massive deployment or renewable energy and in particular solar photovoltaic, it is necessary to develop methods and tools to guide this deployment. To this end, this work proposes a multicriteria approach for evaluating the su ...

Several contrasting effects are reported in the existing literature concerning the impact assessment of the COVID19 outbreak on the use of energy in buildings. Following an in-depth literature review, we here propose a GISbased approach, based on pre-pande ...

The spatio-temporal patterns of the existing rooftop photovoltaic (PV) production can provide valuable insights for the design of effective strategies for PV integration at large scale. In this work, we quantify the hourly production of existing rooftop PV ...

Mapping the location and size of solar installations in urban areas can be a valuable input for policymakers and for investing in distributed energy infrastructures. Machine Learning techniques, combined with satellite and aerial imagery, allow to overcome ...

All the projected scenarios agree on the immediate necessity of reducing greenhouse gas emissions, especially carbon dioxide (CO2). This research proposes an analysis on the EPFL campus of all the potential reductions of CO2 emissions: energy refurbishment ...

The gas crisis of 2022 put pressure on electricity prices in Europe, prompting the Swiss government to launch a national energy-saving campaign. To effectively quantify potential savings and guide timely decision-making, this campaign called for rigorous n ...

Roberto Castello

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Explainable machine learning prediction of edema adverse events in patients treated with tepotinib

Spatio-Temporal Relationship between Land Cover and Land Surface Temperature in Urban Areas: A Case Study in Geneva and Paris

Using Machine Learning to estimate the technical potential of shallow ground-source heat pumps with thermal interference

Big data mining for the estimation of hourly rooftop photovoltaic potential and its uncertainty

Wind profile prediction in an urban canyon: a machine learning approach

Large-scale evaluation of the suitability of buildings for photovoltaic integration: Case study in Greater Geneva

Impact of the COVID-19 pandemic on the energy performance of residential neighborhoods and their occupancy behavior

Quantification of existing rooftop PV hourly generation capacity and validation against measurement data

Deep learning in the built environment: automatic detection of rooftop solar panels using Convolutional Neural Networks

Geospatial analysis and optimization of the incoming and stored CO2 emissions within the EPFL campus

Real-time estimates of Swiss electricity savings using streamed smart meter data

Spatio-temporal modelling and uncertainty estimation of hourly global solar irradiance using Extreme Learning Machines

From a Vegetation Index to a Sustainable Development Goal Indicator: Forest Trend Monitoring Using Three Decades of Earth Observations across Switzerland

A machine learning-assisted building electricity consumption profiling for anomaly detection