ARCC-EAAE 2026 International Conference
LOCAL SOLUTIONS FOR GLOBAL ISSUES
April 8-11, 2026 | Atlanta, Georgia, USA
Hosted by Kennesaw State University
Conference Agenda
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
Please note that all times are shown in the time zone of the conference. The current conference time is: 30th Apr 2026, 08:59:25pm PDT
|
Daily Overview | |
|
Location: Classroom 4 - N176 College of Architecture and Construction Management. Kennesaw State University (Marietta Campus) 1100 South Marietta Parkway SE, Marietta, GA 30060 |
| 11:00am - 12:30pm |
T3: Technologies of Place 3 Location: Classroom 4 - N176 Session Chair: Ute Poerschke, Pennsylvania State University Morpho: A Multi-Objective Design Exploration Tool for Designer-in-the-Loop, Performance-Informed Design University at Buffalo, United States of America Post-Disaster Housing: Analyzing Environmental Sustainability of Modular Construction through Simulation-Based Life Cycle Assessment and Multi-Objective Design Optimization Georgia Institute of Technology, United States of America Multi-Objective Beam Optimization: A Metric-Based Design Framework for Sustainable and Efficient Construction 1: Kennesaw State University, United States of America; 2: University of Campania Luigi Vanvitelli; 3: Woodbury University |
| 2:00pm - 3:30pm |
WK 3: Developing Your Research Agenda Location: Classroom 4 - N176 Session Chair: Mahyar Hadighi, Texas Tech University |
| 4:30pm - 6:00pm |
T4: Technologies of Place 4 Location: Classroom 4 - N176 Session Chair: James Doerfler, Kennesaw State University Soft Solar Shading: Localized Adaptive Shading with Knitted Textiles and Micro-Controlled Mechanisms Iowa State University, United States of America Integrating Urban Heat Island Effect And Solar Energy Potential At NC State Campus North Carolina State University, United States of America Smarter Solar Energy: Evaluation of Machine Learning Models to Predict Economic Performance of Distributed Solar PV systems University of North Carolina Charlotte, United States of America |