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Mario Bergés - Carnegie Mellon University. Pittsburgh, PA, US

Mario Bergés

Professor | Carnegie Mellon University


Mario Bergés is interested in making our built environment more operationally efficient through the use of communication technologies.


Mario Bergés is a professor in the Department of Civil and Environmental Engineering at Carnegie Mellon University (CMU). He is interested in making our built environment more operationally efficient and robust through the use of information and communication technologies, so that it can better deal with future resource constraints and a changing environment. Currently his work largely focuses on developing approximate inference techniques to extract useful information from sensor data coming from civil infrastructure systems, with a particular focus on buildings and energy efficiency.

Bergés is the faculty co-director of the Smart Infrastructure Institute at CMU, as well as the director of the Intelligent Infrastructure Research Lab (INFERLab). Among recent awards, he received the Professor of the Year Award by the ASCE Pittsburgh Chapter in 2018, Outstanding Early Career Researcher award from FIATECH in 2010, and the Dean's Early Career Fellowship from CMU in 2015.

Bergés received his B.Sc. in 2004 from the Instituto Tecnológico de Santo Domingo, in the Dominican Republic; and his M.Sc. and Ph.D. in Civil and Environmental Engineering in 2007 and 2010, respectively, both from Carnegie Mellon University.

Areas of Expertise (5)

Sensor Networks

Smart Grid

Infrastructure Monitoring

Building Energy Management

Machine Learning for Signal Processing

Media Appearances (5)

Carnegie Mellon University: Where graduates land high-demand careers in AI

Study International  online


“I’m excited to see what transformations that will happen to our profession once these students have graduated and taken on the workforce,” says Mario Bergés, a professor in the Department of Civil and Environmental Engineering. “This new generation of engineers will not only be able to master AI tools but to recognise how they can leverage engineering domain knowledge to extend them to be more practical and powerful.”

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Brick Consortium Announces Inaugural Commercial Members

ACHR News  online


“The Consortium will provide the community assurances that Brick has a long-term future and can be a contributing technology for improving the efficiency and comfort of buildings,” added Carnegie Mellon University Professor Mario Bergés.

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Brick Consortium Announces Inaugural Commercial Members

AutomatedBuildings.com  online


“We are excited to have these industry leaders joining the Brick Consortium and contributing to the development of the Brick schema” said Carnegie Mellon University professor Yuvraj Agarwal. “The Consortium will provide the community assurances that Brick has a long-term future and can be a contributing technology for improving the efficiency and comfort of buildings” said Carnegie Mellon University professor Mario Bergés. Both Agarwal and Bergés are Brick Consortium Steering Committee members.

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Smart space habitat looks to put AI to work in deep space

New Atlas  online


"How do you conduct automated fault detection and diagnosis without a lot of system data? This is where AI comes in," says Associate Professor Mario Bergés, who heads up the research team. "We have machines that learn by themselves if you give them enough data, but we don't have a lot of machines that can reason by using existing engineering knowledge, which can reduce the amount of data they need."

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Dominican Republic Greens see ‘hope reborn’

Dominican Today  online


"Today, in this esplanade of the Attorney General’s Office, we can express satisfaction because as a result of the organization and persistence of this people, actions are beginning to be seen to apply justice to those who have illegally enriched themselves from State coffers,” said Mario Bergés, reading a document on behalf of the civic movement Marcha Verde.

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Mario Berges: Unlocking the Power of Sensing Technology Today and Tomorrow Behind the Researcher - Mario Bergés Mario Bergés: Using Analytics to Understand Energy Consumption in Buildings MS in AI Engineering in CEE @ CMU



Industry Expertise (3)



Civil Engineering

Accomplishments (2)

Dean's Early Career Fellowship Award (professional)

2015 CMU College of Engineering

ASCE Pittsburgh Section 2017 Professor of the Year Award (professional)


Education (3)

Carnegie Mellon University: Ph.D., Civil and Environmental Engineering 2010

Carnegie Mellon University: M.S., Civil and Environmental Engineering 2007

Instituto Tecnológico de Santo Domingo: B.S., Civil Engineering 2005

Patents (1)

Electrical meter system for energy desegregation



An energy meter is configured to determine component waveforms that form a measured waveform. The meter inputs the waveform into one or more entries of a data structure, each entry of the one or more entries of the data structure storing a weight value that is determined based at least in part on values of the data signatures representing the plurality of remote devices, each entry being connected to one or more other entries of the data structure.

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Articles (5)

AlphaShed: A scalable load flexibility model for shedding potential in commercial HVAC systems

Energy and Buildings

2023 Technologies that enable the demand flexibility (DF) in building loads have been identified as a key advancements to support the reliable operation of the electric grid. The concept of grid-interactive efficiency buildings (GEBs) envisions building loads actively controlling power consumption in alignment with grid services. Commercial HVAC systems, through load shedding, hold a significant portion of this resource.

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Characterizing Data Sharing in Civil Infrastructure Engineering: Current Practice, Future Vision, Barriers, and Promotion Strategies

Journal of Computing in Civil Engineering

2023 Data sharing between different organizations is critical in supporting decision making in civil infrastructure engineering projects (e.g., transportation projects). Understanding the characteristics of data-sharing-related factors in civil infrastructure engineering is crucial for the civil engineering community to identify the priorities in promoting data sharing. The ASCE Data Sensing and Analysis (DSA) Committee initiated an investigation on data-sharing barriers in civil infrastructure engineering.

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The field of human building interaction for convergent research and innovation for intelligent built environments

Scientific Reports

2022 Human-Building Interaction (HBI) is a convergent field that represents the growing complexities of the dynamic interplay between human experience and intelligence within built environments. This paper provides core definitions, research dimensions, and an overall vision for the future of HBI as developed through consensus among 25 interdisciplinary experts in a series of facilitated workshops.

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Ten questions concerning human-building interaction research for improving the quality of life

Building and Environment

2022 This paper seeks to address ten questions that explore the burgeoning field of Human-Building Interaction (HBI), an interdisciplinary field that represents the next frontier in convergent research and innovation to enable the dynamic interplay of human and building interactional intelligence.

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The Digital Twin Landscape at the Crossroads of Predictive Maintenance, Machine Learning and Physics Based Modeling


2022 The concept of a digital twin has exploded in popularity over the past decade, yet confusion around its plurality of definitions, its novelty as a new technology, and its practical applicability still exists, all despite numerous reviews, surveys, and press releases. The history of the term digital twin is explored, as well as its initial context in the fields of product life cycle management, asset maintenance, and equipment fleet management, operations, and planning. A definition for a minimally viable framework to utilize a digital twin is also provided based on seven essential elements.

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