Bradley Schmerl

Registered user since Mon 16 Oct 2017

Name: Bradley Schmerl

Country: United States

Affiliation: Carnegie Mellon University, USA

Personal website: http://www.cs.cmu.edu/~schmerl

Research interests: Self-Adaptive Systems, Software Architecture, Software Engineering

Contributions

SEAMS 2021Committee Member in Program Committee within the SEAMS 2021-track
ACSOS 2020Author of Case Study of an Automated Approach to Managing Collections of Autonomic Systems within the Research Papers-track
Author of Hybrid Planning Using Learning and Model Checking for Autonomous Systems within the Research Papers-track
PC Member in Program Committee within the Research Papers-track
Author of Reasoning about When to Provide Explanation for Human-in-the-loop Self-Adaptive Systems within the Research Papers-track
Author of REACT: A Model-Based Runtime Environment for Adapting Communication Systems within the Research Papers-track
ECSA 2020Committee Member in Program Committee within the Research Papers-track
SEAMS 2020Committee Member in Artifact Program Committee within the SEAMS 2020-track
Author of Software Architecture and Task Plan Co-Adaptation for Mobile Service Robots within the SEAMS 2020-track
Committee Member in Program Committee within the SEAMS 2020-track
Author of SEAMS 2006 MIP: Architecture-based self-adaptation in the presence of multiple objectives within the SEAMS 2020-track
SEAMS 2019Author of Machine Learning Meets Quantitative Planning: Enabling Self-Adaptation in Autonomous Robots within the SEAMS 2019-track
Program Committee in Program Committee within the SEAMS 2019-track
ICSE 2020Author of How do you Architect your Robots? State of the Practice and Guidelines for ROS-based Systems within the Software Engineering in Practice-track
SEAMS 2018Committee Member in Steering Committee within the SEAMS 2018-track
Author of SWIM: An Exemplar for Evaluation and Comparison of Self-Adaptation Approaches for Web Applications within the SEAMS 2018-track
Committee Member in Program Committee within the SEAMS 2018-track