Matias Quintana

Matias Quintana
National University of Singapore | NUS · College of Design and Engineering

Master in Information Systems Management

About

31
Publications
16,730
Reads
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213
Citations
Introduction
I am a Ph.D. Candidate in the School of Design and Environment at the National University of Singapore (NUS) advised by Prof. Clayton Miller. My research interests are broadly in the field of robotics, applied machine learning, and their applications to smart buildings and occupant thermal comfort. My recent work focuses on generative modeling, recommender systems, and reinforcement learning. You can read more about my work in: https://matiasquintana.com/
Additional affiliations
April 2017 - June 2018
Carnegie Mellon University
Position
  • Research Assistant
Description
  • Research Assistant at the Intelligent Infrastructure Research Laboratory (INFERLab) under the direction of Mario Bergés.
Education
August 2018 - June 2022
National University of Singapore
Field of study
  • Building and Systems Engineering
August 2015 - December 2016
Carnegie Mellon University
Field of study
  • Information Systems
March 2009 - July 2014
Pontifical Catholic University of Peru
Field of study
  • Electronic Engineering

Publications

Publications (31)
Preprint
Full-text available
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) infectious disease (COVID-19) risk perception, ii) privacy and distraction in an office context, and iii) triggers of various movement-related behaviors in buildings. Thi...
Article
Full-text available
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 Great Energy Predictor III (GEPIII) machine learning competition used an extensive meter data set to crowdsource the most accurate machine learning workflow for whole buildin...
Preprint
Full-text available
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 Great Energy Predictor III (GEPIII) machine learning competition used an extensive meter data set to crowdsource the most accurate machine learning workflow for whole buildin...
Conference Paper
Full-text available
Thermal comfort affects the well-being, productivity, and overall satisfaction of building occupants. However, due to economical and practical limitations, the number of longitudinal studies that have been conducted is limited, and only a few of these studies have shared their data publicly. Longitudinal datasets collected indoors are a valuable re...
Article
Full-text available
Internet-of-Things (IoT) devices in buildings and wearable technologies for occupants are quickly becoming widespread. These technologies provide copious amounts of high-quality temporal data pertaining to indoor and outdoor environmental quality, comfort, and energy consumption. However, a barrier to their use in many applications is the lack of s...
Preprint
Full-text available
Internet-of-Things (IoT) devices in buildings and wearable technologies for occupants are quickly becoming widespread. These technologies provide copious amounts of high-quality temporal data pertaining to indoor and outdoor environmental quality, comfort, and energy consumption. However, a barrier to their use in many applications is the lack of s...
Article
Full-text available
Global climate is changing as a result of anthropogenic warming, leading to higher daily excursions of temperature in cities. Such elevated temperatures have great implications on human thermal comfort and heat stress, which should be closely monitored. Current methods for heat exposure assessments (surveys, microclimate measurements, and laborator...
Article
Full-text available
Many energy performance analysis methodologies assign buildings a descriptive label that represents their main activity, often known as the primary space usage (PSU). This attribute comes from the intent of the design team based on assumptions of how the majority of the spaces in the building will be used. In reality, the way a building’s occupants...
Conference Paper
Full-text available
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. These data can be used for modeling comfort behavior to support design and operations towards energy efficiency and well-being. By nature, occupant subjective feedback is imb...
Conference Paper
Full-text available
As the individual difference in thermal comfort transition time is yet to be thoroughly explored, this paper studies time adaptability amongst individuals by collecting high frequency subjective comfort feedback using micro ecological momentary assessments on a smart-watch. The individuals were grouped based on their thermal preference responses an...
Article
Full-text available
Evaluating and optimising human comfort within the built environment is challenging due to the large number of physiological, psychological and environmental variables that affect occupant comfort preference. Human perception could be helpful to capture these disparate phenomena and interpreting their impact; the challenge is collecting spatially a...
Preprint
Full-text available
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. These data can be used for modeling comfort behavior to support design and operations towards energy efficiency and well-being. By nature, occupant subjective feedback is imb...
Preprint
Full-text available
Evaluating and optimising human comfort within the built environment is challenging due to the large number of physiological, psychological and environmental variables that affect occupant comfort preference. Human perception could be helpful to capture these disparate phenomena and interpreting their impact; the challenge is collecting spatially a...
Conference Paper
Full-text available
Thermal comfort is a decisive factor for the well-being, productivity, and overall satisfaction of commercial building occupants. Many commercial building automation systems either use a fixed zone-wide temperature set-point for all occupants or they rely on extensive sensor deployments with frequent online interaction with occupants. This results...
Poster
Full-text available
Human comfort datasets are widely used in smart buildings. From thermal comfort prediction to personalized indoor environments, labelled subjective responses from participants in an experiment are required to feed different machine learning models. However, many of these datasets are small in samples per participants, number of participants, or suf...
Conference Paper
Full-text available
Thermal comfort is very important for well-being and productivity of building occupants. It has been shown that body shape is a useful feature to determine thermal comfort of individuals [2]. It is because, the heat dissipation rate of individuals depends on the body surface area. As a result, a tall and skinny person can tolerate higher room tempe...
Conference Paper
Occupancy detection, tracking, and estimation has a wide range of applications including improving building energy efficiency, safety, and security of the occupants. As depth sensors are getting cheaper, they offer a viable solution to estimate occupancy accurately in a non-privacy invasive manner. Even though there are publicly available depth dat...
Article
Full-text available
This study describes a human-building interaction framework called the SDE Learning Trail , a mobile app that is currently deployed at the SDE4 building - the new Net Zero Energy Building (NZEB) at the National University of Singapore (NUS). This framework enables building occupants and visitors to learn about the well and green features of the new...
Article
Full-text available
Labelled human comfort data can be a valuable resource in optimising the built environment, and improving the wellbeing of individual occupants. The acquisition of labelled data however remains a challenge. This paper presents a methodology for the collection of in-situ occupant feedback data using a Fitbit smartwatch. The clock-face application co...
Preprint
Full-text available
Human comfort datasets are widely used in smart buildings. From thermal comfort prediction to personalized indoor environments, labelled subjective responses from participants in an experiment are required to feed different machine learning models. However, many of these datasets are small in samples per participants, number of participants, or suf...
Preprint
Full-text available
Many energy performance analysis methodologies assign buildings a descriptive label that represents their main activity, often known as the primary space usage (PSU). This attribute comes from the intent of the design team based on assumptions of how the majority of the spaces in the building will be used. In reality, the way a building's occupants...
Preprint
Full-text available
This study describes a human-building interaction framework called the SDE Learning Trail, a mobile app that is currently deployed at the SDE4 building-the new Net Zero Energy Building (NZEB) at the National University of Singapore (NUS). This framework enables building occupants and visitors to learn about the well and green features of the new NZ...
Conference Paper
Full-text available
The recent growth of the building performance research community has been in parallel with the oneb-uilding.org Bldg-sim email list. This list was formed in 1999 and steadily grew into a major venue for building simulation community announcements, discussions , and questions and answers (Q&A). This paper presents an analysis of the Bldg-sim email a...
Preprint
Full-text available
Labelled human comfort data can be a valuable resource in optimising the built environment, and improving the wellbeing of individual occupants. The acquisition of labelled data however remains a challenge. This paper presents a methodology for the collection of in-situ occupant feedback data using a Fitbit smartwatch. The clock-face application co...
Preprint
Full-text available
The recent growth of the building performance research community has been in parallel with the oneb-uilding.org Bldg-sim email list. This list was formed in 1999 and steadily grew into a major venue for building simulation community announcements, discussions , and questions and answers (Q&A). This paper presents an analysis of the Bldg-sim email a...
Conference Paper
Full-text available
This paper introduces a low-cost AC meter designed to continuously measure voltage and current waveforms at up to 14 kHz. The AC power meter, provided as open hardware, is designed using the same micro controller as the Arduino UNO¹ with an In-system Programming (ISP) interface, thus allowing the user to change the firmware to match their particula...
Conference Paper
Full-text available
Occupancy estimation is very useful for a wide range of smart building applications including energy efficiency, safety, and security. In this demonstration, we present a novel solution called FORK, which uses a Kinect depth sensor for estimating occupancy in real-time. Unlike other camera-based solutions, FORK is much less privacy invasive (even i...
Conference Paper
Full-text available
Total Station has been one of the most common acquisition devices for achieving maps through topographic survey. Nowadays, Terrestrial Laser Scanner (TLS) and Photogrammetry are commonly used to generate accurate meshes. In addition, commercial products such as Kinect offer low cost technology to acquire point-cloud information. The present paper a...
Chapter
Full-text available
3D acquisition and reconstruction is extensively used in documenting and preserving archaeological sites. Despite its benefits, price and portability of the devices used are still an issue in many cases. This work presents a characterization of the Microsoft Kinect sensor and a complete methodology of data acquisition, registration and 3D reconstru...

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Projects

Projects (3)
Project
Model and understand buildings occupants' preferences and behavior inside indoor environments to better control and design such spaces.
Project
Develop an open-source clock face for Fitbit and Apple Watch, to allow researchers, facility managers, engineers and architects to easily collect subjective feedback from building occupants.
Project
Deep reinforcement learning algorithms have seen an increased interest and have demonstrated human expert level performance in other domains, e.g., computer games. Research in the building and cities domain has been fragmented and with focus on different problems and using a variety of frameworks. The purpose of this Workshop is to build a growing community around this exciting topic, provide a platform for discussion for future research direction, and share common frameworks.