Annual Modeling and Simulation Conference (ANNSIM)
May 26-29, 2025
Complutense University of Madrid, Spain
About ANNSIM
Hosted by The Society for Modeling and Simulation International (SCS), the 2025 Annual Modeling and Simulation Conference (ANNSIM’25) is the annual conference that covers state-of-the-art developments in Modeling & Simulation (M&S). The conference includes keynote speeches presented by technology and industry leaders, technical sessions, and tutorials for professional development. Scientists, engineers, managers, educators, and business professionals who develop or use M&S methodologies and tools are invited to participate and present original contributions. ANNSIM’25 invites original contributions to the theory, methodology, and practice of modeling and simulation in any discipline.
Organizing Committee & Publicity Chairs
Organizing Committee:
General Chair: Jose L. Risco-Martin, Complutense University of Madrid
Vice-General Chair:
Ghaith Rabadi, School of Modeling, University of Central Florida, Orlando, FL, USA
Program co-Chairs:
Deniz Cetinkaya, Bournemouth University, Bournemouth, United Kingdom
Román Cárdenas, Polytechnic University of Madrid, Madrid, Spain
Sponsorship and Exhibitor Opportunities
The 2025 ANNSIM Conference Sponsor and Exhibitor Guide will provide opportunities to network with the modeling and simulation community and display your agency, business, or organization.
You can find options on our guide on which companies or groups can sponsor items for an SCS Event. ANNSIM offers standard packages such as Platinum, Gold, and Silver, Bronze, and an Exhibitor
Only option. We also offer customized Packages. For specialized sponsor options, please contact the SCS Office at scs@scs.org.
Awards
Each year, ANNSIM recognizes exceptional papers, attendees, and student affiliates with awards given during our Annual Conference. These include the best paper award and the best runner-up paper.
Potential Tracks
Click on each track to expand.
Annual Simulation Symposium
Modeling and Simulation (M&S) is currently the core of many industrial processes. It is a vital ingredient, since it can support early evaluation and optimization of designs, as well as ongoing verification while changes occur to make sure that the right product is developed with the required quality. However, there are still businesses that must understand that embracing M&S in project development and management is good practice, and this can be done by showing real-world examples of success.
Real-world applications have always been the driving force for the development of M&S theories. For over 50 years, the Annual Simulation Symposium has been a forum to exchange ideas, results, and methods related to real-world theories and applications of M&S for simulation experts in industry, government, and academia.
The purpose of this track is to highlight and advance rigorous experimental and computational practices of M&S devoted to the study of real-world problems. Research on all topics concerning the practice of M&S theories are welcome. Authors are invited to submit original research papers, including case studies and applications.Recommended topics in the track include, but are not limited to, the following:
- Advances in the field of M&S for implementation purposes
- Application of modeling formalisms into real world applications
- Rigorous comparisons across M&S techniques
- Model checking, formalism-based model debugging, model transformation
- Model-driven and model-based approaches in M&S
- New applications of M&S
- Novel uses of M&S in real world applications
- Application of M&S to co-design, hardware-in-the-loop, co-simulation
- M&S tools: performance analysis, scalability
- M&S of quantum information and quantum algorithms
- Quantum simulators and quantum simulation of physical systems
Humans, Societies, and Artificial Agents
Agent-based models (ABMs), cellular automata, and microsimulations model systems through the lens of complex systems theory. More specifically, such approaches simulate populations of possibly heterogeneous individuals as they utilize either simple behavioral rules or learning models to govern their interactions with each other and their environment, and from which system-level properties emerge. Such modeling and simulation approaches have supported a wide range of applications related to human societies (e.g., traffic and urban planning, economics, natural hazards, national security, epidemiology) and research tasks (e.g., exploring what-if scenarios, predictive models, data generation, hypothesis testing, policy formation and generation).
Despite the multitude of advancements in the last few decades, there remain longstanding challenges that limit the usefulness of such models in the policy cycle. Such challenges include but are not limited to: capturing realistic individual and collective social behaviors; basic issues in model development (calibration, scalability, model reusability, difficulties in generalizing findings); and making transparent the strengths and limitations of models. This track focuses generally on advancements in modeling and simulation approaches in application to human societies that seek to overcome these challenges, with a special interest in policy modeling and the inclusion of models in the policy cycle.Thus, authors are encouraged to submit papers that include, but are not limited to, the following areas:
- Applications of artificial societies (e.g., modeling group decisions and collective behaviors, emergence of
social structures and norms, dynamics of social networks) - Data collection for artificial societies (e.g., using simulations to identify data gaps, population simulations
with multiple data sources, use of the Internet-of-Things) - Design and implementation of artificial agents and societies (e.g., case studies, analyses of moral and
ethical considerations) - Participatory modeling and simulation
- Policy modeling
- Fostering dialog between modelers and policy makers
- Improved models of social behavior
- Simulations of societies as public educational tools
- Mixed-methods (e.g., analyzing or generating text data with artificial societies, combining machine
learning and artificial societies) - Models of individual decision-making, mobility patterns, or socio-environmental interactions
- Testbeds and environments to facilitate artificial society development
- Tools and methods (e.g., agent-based models, case-based modeling, soft systems)
- Addressing longstanding challenges (model validation, re-use, communication)
- Applications of artificial societies (e.g., modeling group decisions and collective behaviors, emergence of
Health and Medicine
Modeling and simulation techniques have been widely adopted across various domains such as healthcare, clinical medicine, and population health. In healthcare settings, simulations have been useful to represent medical processes at a large scale (e.g., emergency rooms, hospitals) to identify bottlenecks in patient treatment and improve efficiencies. Computer-based medical simulations are useful for synthesizing the response of tissues to therapy while trading off between response fidelity and computational efficiency. High-fidelity clinical simulation and disease progression modeling can be used to provide insights for experienced clinicians to optimize across treatment options. Finally population health modeling and simulation tools have been useful for guiding real-time epidemic response while also understanding the impact of various policies on different aspects of community health. These may range from individual level agent-based models to aggregate simulations including system dynamics models. Such methods could also be used to address healthcare-associated infections (HAIs) which impact both public health and healthcare operations.
Multiple recent advances in computational modeling are yet to be fully exploited in health and medicine. High-performance computing (HPC) intensive simulation tools are needed for studying multiscale dynamics such as co-evolving epidemics and health impacts of extreme weather events on the population. Application of deep learning techniques for complementing such simulations through surrogate modeling is an active research area. For clinical simulations, the use of Virtual Reality (VR) and haptics to enhance real-time interactivity is promising for skill acquisition and training. Interactive platforms for exploring simulated outcomes in the healthcare and medical simulations could improve uptake among clinicians and health system administrators. Efficient integration of domain knowledge and complex data calibration in the case of biomedical simulations is needed to improve fidelity of tissue response to therapy. Finally, coupling such simulations with medical imaging techniques to improve diagnosis capabilities would be greatly beneficial.This track encourages submissions on simulation aspects of health and medicine that include, but are not limited to, the following:
- Simulation for healthcare systems and medical processes
- Predictive models and simulations for disease progression
- Surgery and therapy simulation
- Biomedical simulations for tissue response
- Epidemic modeling and simulations across scales
- Health impact simulations for extreme weather events
- Deep learning models and surrogate simulations
- Interactive simulation and summarization tools
- Virtual reality enabled simulations for healthcare training
- Calibration of complex simulations with real world data
Cyber
Modeling and simulation (M&S) has the ability to improve our understanding of cyber operations and illuminate insights into the exploitability and impact of the threat landscape in cyber systems underpinning critical infrastructures. The emergence of the Internet of Everything (IoE) has accelerated growth in interactions between humans, physical, and cyber systems with an attendant increase in the need to understand how these interactions could be exploited by adversaries. M&S provides a safe, secure, and cost-effective means to enhance cyber training, conduct cyber mission rehearsals, and support research, experimentation, development, refinement, deployment, and test and evaluation of the next generation of security solutions for detecting, preventing, and recovering from cyber-attacks and failures. The goal of this track is to provide a forum to present and discuss advancements in research, tools, techniques, solutions, best practices, and heuristics related to the M&S of cyber. We encourage submissions related to all aspects of cyber M&S in a broad spectrum of application areas.
Topics of interest include, but are not limited to:
- Formal models for cybersecurity simulation
- Simulation-supported cybersecurity evaluation and assessment approaches
- Test beds and experimental infrastructure for cyber simulation
- Artificial adversarial threat actor, defender, and user representations
- Integration of cyber simulations, kinetic / physical simulations, and cyber ranges
- Multi-resolution representations of cyber objects, attacks, and effects
- Simulation platforms for cybersecurity assessment
- Hybrid simulations for cyber-physical system security
- Modeling and analysis of networked security systems
- Modeling security and privacy in mobile and cellular networks
- Modeling security for future Internet architectures
Digital Twins and Cyber-Physical Systems
Cyber-physical Systems (CPSs) are becoming more and more ingrained in our everyday life, enabled by digital technologies that bring together the physical and cyber realities, including communication, computation, and control capabilities. These technologies are impacting industry and cities in many respects. Industries at large are moving to become networks of CPS that are not only acting and sensing in the real world, but also model, simulate, control, optimize, predict, reason and share information on the virtual world. To this end, a key technology is the Digital Twin (DT), a real-time synchronized simulation of a physical component or system that can monitor and provide additional functionality like prediction and predictive maintenance, reconfiguration, learning, in the virtual part of CPS.
The synergy of CPS and DT is also enhanced by the use of other digital technologies and approaches, such as Internet-of-Things (IoT), Artificial Intelligence (AI) and machine learning (ML), advanced and autonomous robotics, cloud-edge computing, advanced sensors, augmented reality.
This has an impact on how tasks are carried out and how decisions are made at any level of companies and industrial systems. The Track welcomes any contribution to Modelling and Simulation (M&S) to support the decision making during any lifecycle phase of industrial systems including, but not limited to, manufacturing, assembly, logistics and robotics systems.The topics of interest are including, but not limited to:
- Digital Twin modeling and simulation of CPS
- Tools and techniques supporting the management of the DT lifecycle
- DT and CPS parallel development, DevOps perspective
- Verification, validation (V&V) of digital twins
- Handling uncertainty in digital twins
- Fidelity, scalability, reliability, trust, security of simulators in digital twins
- Case studies, industry applications, and experience reports
- Digital Twins and Digital Threads
- Digital Twins and Industrial Metaverse
- Digital Twins for sustainable CPS
- Digital Twins for circular CPS
- AI as a support to DT-based decision making in CPS systems
- The role of IoT in CPS systems
- DT and mobile robots
- DT for human-centric production and logistics
- DT for collaborative robotics
- Standards and certifications developments for DT of CPS
Communications and Networking Simulation
The CNS track emphasizes the vital role of communications and networking in modern systems. While it originally centered on traditional computer networks, its scope now includes the Intelligent Internet of Things (IIoT), 5G/6G technology, and smart telecommunication systems. The track also explores the transformative impact of Edge and Cloud computing, understanding their potential in shaping intelligent network-based systems for building the foundation and infrastructure of smart cities.
CNS forum serves as a premier platform for professionals to exchange insights on the performance evaluation of both current and emerging new generations of communication, energy, and healthcare network systems. Embracing a diverse spectrum, we are keen on contributions that range from theoretical research to hands-on practical investigations. Work that presents innovative evaluation methods or offers insights into design and performance optimization in communications and network systems is especially valued. Whether it’s experimental analysis, system optimization, artificial neural networks, Using AI and Machine Learning in networking, or real-world case studies, all pertinent contributions that align with these themes (but not limited to the following topics) are warmly welcomed.- AI and ML in communications and networking and computer systems
- Data Science, Big Data Analysis in communications, networking and computer systems
- 5G/6G and Beyond and enabling technologies, Device to Device communications, and network routing
- Software Defined Networking and Network Function Virtualization
- Edge/Fog/Cloud Computing, Distributed Systems, Scalable Machine Learning Networks
- Green and energy efficient communications and networking
- Cooperative communications and networking
- Cognitive radio and networking, Future Radio Access Networks
- Web social network modeling and simulation, socially aware networking and applications
- Vehicular ad-hoc networks / connected vehicles
- Traffic modeling and simulation of Telecommunication systems and networks, Large scale networks simulation
- Trust and security in communications, networking and computer systems and enabling technologies
- Web-based systems and simulation of video analytics applications
- Optical-Wireless communication and systems, Wireless ad-hoc Networks/ Wireless Sensor Networks/ Delay
Tolerant Networks/ Opportunistic Networks/ Peer-to-Peer networking and computations - Next Generation Internet of Things, enabling technologies and intelligent applications (Architecture, networking
technologies, smart-cities, health-care systems, smart environment, smart mobility, precision agriculture, smart sustainability)
Sustainability and Resource Management
Sustainability emerges as both a profound challenge and a tremendous opportunity in this century. The imperative of achieving sustainable development, where present needs are met without compromising the well-being of future generations, has never been more apparent. This involves a harmonious integration of social equity, economic growth, and environmental preservation, recognizing their interconnectedness across various dimensions.
Sustainability-aware systems must explicitly balance trade-offs between factors like cost reduction, emission reduction, positive social behaviors and system evolution ease.
The call stresses the growing importance of supporting sustainability through modeling and analysis, particularly in complex systems like cyber-physical systems, and it also highlights the significance of addressing sustainability in urban contexts, as cities increasingly determine global resource use. The call addresses software and systems, which adhere to sustainability principles or which support sustainability goals. Sustainability modeling might include energy efficiency, environmental friendliness, societal and economic impact, inclusivity, and adaptability for prolonged viability. The urgent need for urban transformation strategies is emphasized, covering aspects such as sustainable mobility, efficient buildings, industry and urban infrastructure, renewables, and circular economy concepts. The challenges of congestion, affordable housing, and overspending on biocapacity are acknowledged, with a call to address climate change-related problems through decarbonizing urban infrastructure and innovative concepts for load management, flexibility, storage, and local renewables.
The sustainability and resource management track provides a forum to present the latest developments in modeling and simulation of sustainability and sustainable systems. Modeling and simulation can be an effective tool to evaluate sustainability, to design sustainable systems, and to provide optimum scenarios for the transformation of the built environment and the urban transportation infrastructure. We welcome collaborative works with different and disjoint disciplines such as computer sciences, energy engineering, geoinformation and data sciences or environmental and social sciences.In particular, this call for papers asks modeling and simulation contributions in the following fields:
- Modeling for sustainability regarding ethical concerns, modeling for the good, quality and cost trade-offs, cost assessment methods
- Modeling and simulation tools, languages and frameworks for sustainability
- Techniques promoting prolonged system lifecycle or environmental sustainability
- Zero emission building clusters and positive energy neighborhoods
- Sustainable mobility solutions, services and electrification impacts on smart grids
- Urban microclimate modeling with green and blue infrastructure
- Circular economy, resource management and urban mining
- Communication, Control and Internet-of-things in smart cities
- Renewable energy systems and storage
- Urban digital twins and city scale data analytics and modeling
- Empirical inquiries, surveys, case studies, tool evaluations in modeling of sustainability
- Modeling and simulating human behavior which contributes to sustainability
- Energy efficient computing
- Smart Grids
- Urban carbon emission accounting and modeling
- Flexibility and demand response
- Decision support for urban transformation strategies
- ML applications for sustainability
Business
We are pleased to announce the “Business Informatics and Process Management Track” at the 2024 Annual Modeling and Simulation Conference (ANNSIM’24). We cordially invite you to participate in this prestigious event, dedicated to exploring the latest advancements in the realms of business informatics and process management. Simulation is a critical component of process management, with the ultimate goal of performing what-if analysis and various scenarios for process improvement. Furthermore, the data available in the information system has enabled the generation of accurate and close-to-reality simulation models. Various simulation techniques in different settings, such as discrete event simulation, system dynamics, agent-based modeling, Markov chains, and other innovative techniques for using information systems, can address business needs.
The Business Informatics and Process Management Track aims to bring academics, researchers, and industry professionals together to discuss and exchange cutting-edge ideas, research findings, and innovative solutions related to the effective application of modeling and simulation techniques in business settings. We welcome original papers highlighting emerging trends, methodologies, and case studies in business informatics and process management.Authors are encouraged to submit papers that include, but are not limited to, the following areas:
- Business process modeling and simulation
- Process optimization and automation
- Process simulation
- Process simulation using process mining
- Big data analytics in business decision-making
- Artificial Intelligence and Machine Learning for business processes
- Business intelligence and data-driven decision support systems
- Digital transformation and technology adoption in organizations
- Blockchain applications in supply chain management and finance
- Simulation-based risk assessment and management
- Cognitive and collaborative decision-making in business
- Innovative business models and strategies
- Industry 4.0 and smart manufacturing
- Agile and adaptive business processes
- Simulation-based gaming and training for business professionals
- Human factors and usability in business systems
- Enterprise Architecture Management
- Modeling and Simulation of processes, capabilities, and data
- Modeling and Simulation of Enterprise Information Systems
- Circular Process Management
Machine Learning and AI
Artificial Intelligence has fundamentally changed how we conduct our business, research, teaching, and even shopping, among other activities, often through the automation of routine tasks and the mediation of human/machine interactions. In the age of Large Language Models, there is a focus on generative models of AI and their impact on human labour. However, both generative and non-generative AI are increasingly and consistently being incorporated into the many facets of research practice and outcomes. As the M&S community moves forward, we need to consider not only the technical but also the methodological and ethical challenges when integrating AI into our research. This includes how ML/AI methods can expand M&S theory and practice and how M&S can be a key component in the advancement of ML/AI.
The Machine Learning and Artificial Intelligence (ML/AI) track seeks to engage scholars, across domains, on discussing the ML/AI and M&S synergy: from the philosophical to the technical, from the theoretical to the empirical.
The topics of interest include, but are not limited to, the following:- AI-mediated M&S and M&S-mediated AI
- Generative AI and the design and development of models
- Generative AI and the interpretation of models
- M&S generated data and ML training
- M&S and ML/AI towards improving interdisciplinary research
We are looking for new thoughts and experiences that can set the pace for ML/AI and M&S research for the next five years.
Symposium on Simulation for Architecture and Urban Design (SimAUD)
We invite you to submit your original research to SimAUD 2024, held as part of ANNSIM 2024. The Symposium on Simulation for Architecture and Urban Design provides an opportunity for architecture researchers and simulation researchers to come together to focus on this important area.
Buildings are the largest consumers of energy, responsible for the majority of all greenhouse gas emissions due to the complexity and
multidisciplinary aspects of architectural design and construction. However, there are now hundreds of exemplar net-zero buildings around the world demonstrating that research should focus on how to generalize and deploy this knowledge at scale. To this end, we seek submissions, for example, that can apply net-zero systems to novel designs for retrofit recommendations or optimizations to new build designs. Examinations of aspects of the built environment, and how they impact emissions and occupancy health, are welcome.Additional topics of interest include:
- Simulation, Data-Driven, and Generative Design for Sustainability
- Whole Building Energy Simulation
- Modeling of Net-zero Building Systems
- Multidisciplinary Design Optimization
- Modeling of Occupant Behavior
- Thermal Comfort & Occupant Satisfaction
- Lighting and Daylighting
- Airflow In & Around Buildings
- Acoustics Modeling, Simulation & Design
- Urban-Scale Modeling & Simulation
- Augmented and Virtual Reality
- Intelligent Buildings & Building Lifecycle Management
- Interactive Environments & Responsive Facades
- Digital and Robotic Fabrication
- Material and Structural Performance Modeling
Tutorials
The Annual Modeling and Simulation Conference (ANNSIM) offers conference attendees a stimulating and informative selection of tutorials reflecting current topics in the Modeling and Simulation (M&S) domain. Therefore, we invite experts in the M&S domain to present engaging tutorials at the ANNSIM 2024 conference. Tutorials provide researchers and practitioners with the opportunity to introduce their applications, tools, methodologies, or theories in 90-120 minutes long sessions.
Tutorials can be introductory, oriented toward the participants who are interested in broadening their knowledge or, advanced tutorials for the participants who seek the latest advances in M&S. We would like to invite and encourage modeling and simulation researchers and practitioners in academia, government agencies, or industry to submit proposals for tutorials. Topics of interest include M&S theories, methodologies, and tools applied to any domains.Ph.D. Colloquium
The Ph.D. colloquium is a great opportunity for Ph.D. students to present their progress and get constructive feedback from the Modeling and Simulation experts before completing their thesis. Accepted applicants will showcase their work via a short presentation followed by a discussion with the attendees. In addition to receiving valuable feedback, the students get the chance to network for future collaborations and a swift introduction to the research community.
Technical Program Committee
Click here to expand the Technical Program Committee
- Mania Aghaei Meibodi, University of Michigan, USA
- Sara Alsaadani, Arab Academy for Science, Technology and Maritime Transport, Egypt
- Abdurrahman Alshareef, Arizona State University, USA
- Armin Amirazar, University of North Carolina at Charlotte, USA
- Alpha Yacob Arsano, Northeastern University, USA
- Andreas Attenberger, FH Kufstein University of Applied Sciences, Austria
- Kuldip Singh Atwal, George Mason University, USA
- S.R. Aurora, Arizona State University, USA
- Mona Azarbayjani, University of North Carolina at Charlotte, USA
- Rahman Azari, Pennsylvania State University, USA
- Ehsan Baharlou, University of Virginia, USA
- Ding Wen Bao, RMIT University School of Architecture and Urban Design, Australia
- Souvik Barat, Tata Consultancy Services Research, India
- Giacomo Barbieri, Universidad de los Andes, Colombia
- José Barbosa, Polytechnic Institute of Bragança, Portugal
- Simon Barner, Fortiss, Canada
- Joana Barros, University of London, UK
- Chad Bates, United States Army War College, USA
- Peristera Baziana, University of Thessaly, Greece
- Michal Ben-Nun, Predictive Science Inc., USA
- Frederick Benaben, IMT Mines Albi, France
- Aysu Berk, Bilkent University, Turkey
- Nicola Berti, University of Padua, Italy
- Eva Besada Portas, Universidad Complutense de Madrid, Spain
- Ardavan Bidgoli, Carnegie Mellon University, USA
- Paul-Antoine Bisgambiglia, University of Corsica, France
- Biswajit Biswal, South Carolina State University, USA
- Maria Blas , Instituto de Desarrollo y Diseño INGAR (UTN-CONICET), Argentina
- Dominique Blouin, Institut Polytechnique de Paris, France
- Paolo Bocciarelli, University of Rome Tor Vergata, Italy
- Biayna Bogosian, University of Southern California, USA
- Mohammad Bolhassani, City College of New York, USA
- Frédéric Boulanger, Université Paris-Saclay, France
- Alexandros-Apostolos Boulogeorgos, University of Western Macedonia, Macedonia
- Johannes Braumann, University of Art and Design Linz, Austria
- Samira Briongos Herrero, NEC Laboratories Europe, Germany
- Alessio Bucaioni, Mälardalen University, Sweden
- Michael Budig, Singapore University of Technology and Design, Singapore
- Roman Cardenas, Universidad Politecnica de Madrid, Spain
- Gustavo Carneiro, Regulatory Agency for Water, Energy and Sanitation of the Federal District (ADASA), Brazil
- Ana Cavalcanti, University of York, UK
- David Chapela-Campa, University of Tartu, Estonia
- Cheney Chen, Perkins&Will, USA
- Jiangzhuo Chen, University of Virginia, USA
- Angelos Chronis, Austrian Institute of Technology, Austria
- Thomas Clemen, Hamburg University of Applied Sciences, Germany
- Rachel Clipp, Kitware, Inc., USA
- Andrew Collins, Old Dominion University, USA
- Ugo Maria Coraglia, University of Bologna, Italy
- Hadrien Courtecuisse, French National Centre for Scientific Research, France
- Maximiliano Cristia, Universidad Nacional de Rosario, Argentina
- Andrew Crooks, University at Buffalo, USA
- Jacome Cunha, University of Porto, Portugal
- Dana Cupkova, Carnegie Mellon, USA
- Andrea D’Ambrogio, University of Rome Tor Vergata, Italy
- Suresh Damodaran, The MITRE Corporation, USA
- Ranjita Dash, National Institute of Technology, Rourkela, USA
- Daniel Davis, WeWork, USA
- Francesca De Crescenzio, University of Bologna, Italy
- Robson De Grande, Brock University, Canada
- Juan de Lara, Universidad Autonoma de Madrid, Spain
- Francesco De Luca, Tallinn University of Technology, Estonia
- Pieter de Wilde, University of Strathclyde, UK
- Eren Demir, University of Hertfordshire, UK
- Makarand Deo, Norfolk State University, USA
- Gregory Ditzler, University of Arizona, USA
- Lorenzo Donatiello, University of Bologna, Italy
- Dominique Duncan, University of Southern California, USA
- Ta Duong, Singapore Management University, Singapore
- Gabriele D’Angelo, University of Bologna, Italy
- Bruce Edmonds, Manchester Metropolitan University, UK
- Joaquin Entrialgo, Universidad de Oviedo, Spain
- Elif Erdine, Architectural Association (AA) School of Architecture, UK
- Zeynep Ertem, State University of New York, USA
- Yasamin Eslami, Ecole centrale de Nantes, France
- Lukas Esterle, Aarhus University, Denamark
- Alberto Falcone, University of Calabria, Italy
- Marie Farell, University of Manchester, UK
- Mohammed Farhan, University of Texas at Arlington, USA
- Maryam Farsi, Cranfield University, UK
- Wolfgang Fenz, RISC Software GmbH, Austria
- Nicolas Ferry, Universite Cote d’Azur, France
- John Fitzgerald, Newcastle University, UK
- Neal Fitzgerald Wagner, The MITRE Corporation, USA
- Marco Franceschetti, University of St.Gallen, Switzerland
- Erika Frydenlund, Old Dominion University, USA
- Mohsen Garshasby, Mississippi State University, USA
- Mona Ghandi, Washington State University, USA
- Marjan Ghobad, PJ Carew, South Africa
- Nigel Gilbert, University of Surrey, UK
- Michael Giretzlehner, RISC Software GmbH, Austria
- Rhys Goldstein, Autodesk Research, Canada
- Claudio Gomes, Aarhus University, Denamark
- Paula Gomez, Georgia Tech Research Institute, USA
- Ross Gore, Old Dominion University, USA
- Simon Gorecki, University of Bordeaux, France
- Feng Gu, College of Staten Island, USA
- Olaf Hagendorf, University of Applied Science Wismar, Germany
- Sol Haroon, Georgia Institute of Technology, USA
- Jonathan Harris, US Navy, USA
- Navid Hatefnia, Technical University of Munich, Germany
- John Haymaker, Perkins & Will, USA
- Mohammad Heidarinejad, Illinois Institute of Technology, USA
- Alison Heppenstall, University of Glasgow, UK
- Konstantin Hopf, University of Bamberg, Germany
- Xiaolin Hu, Georgia State University, USA
- Jianxiang Huang, The University of Hong Kong, China
- Amel Jaoua, University of Tunis El Manar, Tunisia
- Soo Jeong Jo, Virginia Tech, USA
- Nathaniel Jones, Arup, USA
- Hamdi Kavak, George Mason University, USA
- William Kennedy, George Mason University, USA
- Mohammad Keshavarzi, University of California, Berkeley, USA
- Arman Khalilbeigi Khameneh, University of Calgary, Canada
- Azam Khan, Trax, Canada
- Joon-Seok Kim, Oak Ridge National Laboratory, USA
- Inki Kim, University of Illinois at Urbana-Champaign, USA
- Istvan Komlosi, University of Debrecen, Hungary
- Youssouf Kone, Université Clermont Auvergne, France
- Odysseas Kontovourkis, University of Cyprus, Cyprus
- Mathias Kraus, FAU Erlangen-Nuremberg, Germany
- Caroline Krejci, The University of Texas at Arlington, USA
- Hai Le, Georgia State University, USA
- Paulo Leitao, Polytechnic Institute of Bragança, Portugal
- Letitia Li, BAE Systems, USA
- Dr.Anas lila, Cardiff University, UK
- Christian Lopez, Lafayette College, USA
- Giovanni Lugaresi, KU Leuven, Belgium
- Christiane M Herr, Southern University of Science and Technology, USA
- Atefeh Makhmalbaf, University of Texas at Arlington, USA
- Pedro Malagon, Universidad Politécnica de Madrid, Spain
- Monika Malinova Mandelburger, TU Wien, Austria
- Nick Malleson, University of Leeds, UK
- Niels Martin, Hasselt University, Belgium
- Carla Martin Villalba, National University of Distance Education, Spain
- Sandro Martinelli Reia, George Mason University, USA
- Andrea Martinez, University of Concepción, Chile
- Peter Maurer, Baylor University, USA
- Steve McKeever, Uppsala University, Sweden
- Giovanni Meroni, Technical University of Denmark, Denmark
- Judith Michael, RWTH Aachen University, Germany
- Sermet Mir, Bournemouth University, UK
- Saurabh Mittal, The MITRE Corporation, USA
- Sifat Moon, University of Virginia, USA
- Andreas Naderlinger, University of Salzburg, Austria
- Taro Narahara, New Jersey Institute of Technology, USA
- Fuzhan Nasiri, Concordia University, Canada
- Eva Navarro, University of Wolverhampton, UK
- Martin Neumann, University of Southern Denmark, Denmark
- Liam O’Brien, Carleton University, Canada
- Bentley Oakes, Polytechnique Montreal, Canada
- Omid Oliyan Torghabehi, University of Michigan, USA
- Bertug Ozarisoy, London South Bank University, UK
- Krista Palen, Transsolar KlimaEngineering, Canada
- Christopher Paolini, San Diego State University, USA
- Dimitris Papanikolaou, University of North Carolina at Charlotte, USA
- Randy Paredis, University Of Antwerp, Belgium
- Marco Parente, University of Porto, Portugal
- Mojtaba Parsaee, Indiana State University, USA
- Paolo Pedrazzoli, University of Applied Sciences and Arts of Southern Switzerland, Switzerland
- Sen Pei, Columbia University, USA
- Shengrui Peng, Leibniz University Hannover, Germany
- Liliana Perez, Université de Montréal, Canada
- Terri Peters, Toronto Metropolitan University, Canada
- Tyler Pilet, Pacific Northwest National Laboratory, USA
- Nathalie Pinede, University of Bordeaux Montaigne, France
- Bianica Pires, The MITRE Corporation, USA
- Geert Poels, Ghent University, Belgium
- Gary Polhill, The James Hutton Institute, UK
- Faryaneh Poursardar, Old Dominion University, USA
- Ebrahim Poustinchi, Kent State University, USA
- Sarada Prasad Gochhayat, Villanova University, USA
- Luise Pufahl, Technical University of Munich, Germany
- Francesco Quaglia, Sapienza University of Rome, Italy
- Majid Rafiei, RWTH Aachen University, Germany
- Mina Rahimian, The Pennsylvania State University, USA
- Vinu Subashini Rajus, Canada Mortgage and Housing Corporation, Canada
- Dhananjai Rao, Miami University, USA
- Luciana Rebelo, Gran Sasso Science Institute, Italy
- Roya Rezaee, Georgia Institute of Technology, USA
- Daniel Rippel, University of Bremen, Germany
- Jose L. Risco-Martin, Universidad Complutense de Madrid, Spain
- Siobhan Rockcastle, University of Oregon, USA
- Óscar Rodríguez Polo, University of Alcalá, Spain
- Lorenzo Rossi, University of Camerino, Italy
- Jerzy Rozenblit, University of Arizona, USA
- Ivan Ruchkin, University of Pennsylvania, USA
- Heath Rush, CAPE Technology Solutions, USA
- Mehrdad Saadatmand, RISE Research Institutes of Sweden, Sweden
- Johannes Sametinger, Johannes Kepler University Linz, Austria
- Davide Schaumann, Technion – Israel Institute of Technology, Israel
- Greg Schleusner, HOK Group, USA
- Mathew Schwartz, New Jersey Institute of Technology, USA
- Moon Gi Seok, Nanyang Technological University, Singapore
- Lynne Serre, Defence Research and Development Canada
- Fatemeh Shahsavari, Perkins and Will, USA
- Shani Sharif, Autodesk, Canada
- Ashwin Shashidharan, Esri, USA
- Ahmed Sherif, The American University in Cairo, Egypt
- Mirko Stoffers, RWTH Aachen University, Germany
- Rudi Stouffs, National University of Singapore, Singapore
- Carmen Paz Suarez-Araujo, University of Las Palmas de Gran Canaria, Spain
- Samarth Swarup, University of Virginia, USA
- Paul T, New York University, USA
- Yasaman Tahouni, University of Stuttgart, Germany
- Martin Tamke, Royal Danish Academy, Denmark
- Austin Tapp, Children’s National Hospital, USA
- Khaled Tarabieh, The American University in Cairo, Egypt
- Moosa Tatar, University of Houston, USA
- Matthias Thürer, Chemnitz University of Technology, Germany
- Daniel Tish, Harvard University, USA
- Walid Tizani, The University of Nottingham, UK
- Ange Lionel Toba, Idaho National Laboratory, USA
- Andreas Tolk, The MITRE Corporation, USA
- Paul Torrens, New York University, USA
- Mamadou Traore, University of Bordeaux, France
- Enrico Tronci, Sapienza University of Rome, Italy
- Irmak Turan, Illinois Institute of Technology, USA
- Alfonso Urquia, National University of Distance Education, Spain
- Koen H. van Dam, Imperial College London, UK
- Harko Verhagen, Stockholm University, Sweden
- Peter von Buelow, University of Michigan, USA
- Christoph Waibel, ETH Zurich, Switzerland
- Gabriel Wainer, Carleton University, Canada
- Fei Wang, Cornell University, USA
- Ramon Weber, Massachusetts Institute of Technology, USA
- Nanda Wijermans, Stockholm University, Sweden
- Sarah Wise, University College London, UK
- Bernd Wolfinger, University of Hamburg, Germany
- Deok-Oh Woo, Lawrence Technological University, USA
- Jim Woodcock, University of York, UK
- Gabriel Wurzer, TU Wien, Austria
- Levent Yilmaz, Auburn University, USA
- Srikanth Yoginath, Oak Ridge National Laboratory, USA
- Nari Yoon, University of Ulsan, Korea
- Kazutomo Yoshii, Argonne National Laboratory, USA
- Greg Zacharewicz, IMT – Mines Ales, France
- Tea Zakula, University of Zagreb, Croatia
- Bahram Zarrin, Technical University of Denmark, Denmark
- Andrzej Zarzycki, New Jersey Institute of Technology, USA
- Xin Zhao, Seattle University, USA
- Kashif Zia, University of Glasgow, UK
- ZahraSadat Zomorodian, Shahid Beheshti Universtiy, Iran
- Przemysław Śliwiński, Wrocław University of Science and Technology, Poland