What is INFERLab?

The Intelligent Infrastructure Research Lab (INFERLab) is composed of a dedicated group of researchers at Carnegie Mellon University who are interested in rethinking and redesigning our built environment to improve its operational efficiency, as well as increase its resilience, adaptiveness and autonomy. In an increasingly resource-constrained world, our infrastructure systems will need to be able to interact with their environment and with each other in order to maximize their efficiency and minimize risks. Founded in 2011 by Dr. Mario Berges, INFERLab team is interested in undertaking research to help solve these problems.

Our Interests

Sensing and Instrumentation

How can our infrastructure make use of instrumentation data to provide better feedback, learn from experience and better plan for the future?

Systems Thinking

How can we improve and leverage the interconnectedness of our infrastructure?

Repurpose, Reduce, Reuse

To what extent can we utilize the resources that are already present in our infrastructure to help solve these problems?

Infrastructure Systems

Building technologies, building physics, structural design and analysis, water retention structures, etc.


Machine learning, pattern recognition, signal processing.


Life-cycle assessment, energy management.

Information and Communication Technologies

Sensor systems, Internet of Things, decision support systems.

The Current Team


Francisco Fonseca
PhD Candidate

Engineering and Public Policy, Carnegie Mellon University

Henning Lange

Henning Lange

PhD student interested in the algorithmic aspects of end-to-end high-frequency Non-Intrusive Load Monitoring.


Jingkun Gao
Research Assistant

PhD candidate, CMU

Lucas Pereira

Lucas Pereira
Visiting Scholar

The more instruments you can play, the better chance you have to became part of the band!

Mario Bergés

Mario Bergés
Assocaite Professor

Director of INFERLab
Born and raised in the vibrant and sunny city of Santo Domingo, Dominican Republic.

Yasamin Hashemi

Yasamin Hashemi
Doctoral Candidate

My research aims to utilize novel sensing techniques and advanced statistical modeling to mitigate the environmental impacts of aging natural gas infrastructure and provide optimal strategies for health monitoring of the natural gas networks.

Previous Members