140 citations · 284 across the 10 of their papers we have counts for
10 papers
Recommender systems and reinforcement learning for human-building interaction and context-aware support: A text mining-driven review of scientific literature
Wenhao Zhang, Matias Quintana, Clayton Miller
The indoor environment significantly impacts human health and well-being; enhancing health and reducing energy consumption in these settings is a central research focus. With the a…
Creating synthetic energy meter data using conditional diffusion and building metadata
Chun Fu, Hussain Kazmi, Matias Quintana +1
Advances in machine learning and increased computational power have driven progress in energy-related research. However, limited access to private energy data from buildings hinder…
Opening the Black Box: Towards inherently interpretable energy data imputation models using building physics insight
Antonio Liguori, Matias Quintana, Chun Fu +3
Missing data are frequently observed by practitioners and researchers in the building energy modeling community. In this regard, advanced data-driven solutions, such as Deep Learni…
The Building Data Genome Directory -- An open, comprehensive data sharing platform for building performance research
Xiaoyu Jin, Chun Fu, Hussain Kazmi +6
The building sector plays a crucial role in the worldwide decarbonization effort, accounting for significant portions of energy consumption and environmental effects. However, the…
Utilizing wearable technology to characterize and facilitate occupant collaborations in flexible workspaces
Kristi Maisha, Mario Frei, Matias Quintana +3
Hybrid working strategies have become, and will continue to be, the norm for many offices. This raises two considerations: newly unoccupied spaces needlessly consume energy, and th…
Smartwatch-based ecological momentary assessments for occupant wellness and privacy in buildings
Clayton Miller, Renee Christensen, Jin Kai Leong +5
This paper describes the adaptation of an open-source ecological momentary assessment smart-watch platform with three sets of micro-survey wellness-related questions focused on i)…
Cohort comfort models -- Using occupants' similarity to predict personal thermal preference with less data
Matias Quintana, Stefano Schiavon, Federico Tartarini +2
We introduce Cohort Comfort Models, a new framework for predicting how new occupants would perceive their thermal environment. Cohort Comfort Models leverage historical data collec…
ALDI++: Automatic and parameter-less discord and outlier detection for building energy load profiles
Matias Quintana, Till Stoeckmann, June Young Park +3
Data-driven building energy prediction is an integral part of the process for measurement and verification, building benchmarking, and building-to-grid interaction. The ASHRAE Grea…
Balancing thermal comfort datasets: We GAN, but should we?
Matias Quintana, Stefano Schiavon, Kwok Wai Tham +1
Thermal comfort assessment for the built environment has become more available to analysts and researchers due to the proliferation of sensors and subjective feedback methods. Thes…
Humans-as-a-sensor for buildings: Intensive longitudinal indoor comfort models
Prageeth Jayathissa, Matias Quintana, Mahmoud Abdelrahman +1
Evaluating and optimising human comfort within the built environment is challenging due to the large number of physiological, psychological and environmental variables that affect…