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ECSA 2021
Mon 13 - Fri 17 September 2021 Location to be announced
Patricia Lago

Registered user since Fri 6 May 2016

Name:Patricia Lago
Bio:

Patricia Lago is a professor at the Vrije Universiteit Amsterdam, the Netherlands, where she leads the Software and Sustainability (S2) research group in the Computer Science Department. She has a PhD in Control and Computer Engineering from Politecnico di Torino and a Master in Computer Science from the University of Pisa, both in Italy. She is a member of the IEEE ICSA and ECSA Steering Committees, and the Steering Committee Chair of the ICT4S conference series. She has published in all major conferences and journals in her field.

Her passion in research is to create software engineering knowledge that makes software better, smarter, and more sustainable. Her philosophy is that research should be industrial-relevant and serve the final purpose of being applied in practice. To this end, her research specifically focuses on the “real’’ needs of practice by establishing collaboration with partners from both the private and public sectors.

Her research and teaching are about software architecture, sustainability, software design and modeling, software quality assessment. She is the initiator of the Computer Science Master Track in Software Engineering and Green IT, and the director of the Master Information Sciences. She co-founded the Green Lab, a place where researchers, students, and companies collaborate to measure the energy footprint of software solutions.

Country:Netherlands
Affiliation:Vrije Universiteit Amsterdam
Personal website:http://patricialago.nl
Research interests:Software Engineering, Software Architecture, Software Sustainability

Contributions

ECSA 2021 Committee Member in Steering Committee
Session Chair of Session 2: Architectural knowledge, decisions, and rationale (part of Research Papers)
Architectural Tactics for Energy-aware Robotics Software: A Preliminary Study
Ordinary PC member in Program Committee within the Research Papers-track
ATDx: A tool for Providing a Data-driven Overview of Architectural Technical Debt in Software-intensive Systems
Building and Evaluating a Theory of Architectural Technical Debt in Software-intensive Systems
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