2023 Annual Modeling and
Simulation Conference

May 23 - 26, 2023
Mohawk College, Ontario, Canada
In-Person Conference



Hosted by The Society for Modeling and Simulation International (SCS), the Annual Modeling and Simulation Conference (ANNSIM) is the SCS Conference to cover state-of-the-art developments in Modeling & Simulation (M&S). We invite original contributions to the theory and practice of modeling and simulation in any scientific or engineering discipline. The conference includes keynote speeches presented by technology and industry leaders, technical sessions, professional development tutorials, as well as vendor exhibits. Scientists, engineers, managers, educators, and business professionals who develop or use M&S methodologies and tools are invited to participate and present original contributions. Accepted papers will be submitted for inclusion into ACM and IEEE Xplore subject to meeting ACM and IEEE Xplore’s scope and quality requirements.
Evaluation criteria: Double blind submissions will be assessed with respect to its overall contribution, strengths and weaknesses. Feedback will include qualitative comments on these three dimensions as well as quantitative scores. Both qualitative and quantitative feedback will be used by track changes to suggest a decision, which will then be reviewed by the organizing committee.
Net Zero and Mohawk College
To help build a sustainable future, the Society for Modeling & Simulation International (SCS) has prioritized learning environments for conference sites that minimize the impact on the environment. As buildings are the dominant cause of greenhouse gases, ANNSIM is moving toward the use of Net-Zero Buildings to house the conference to demonstrate what the future will look like for everyone. On site sustainability, tours will leverage the physical conference location to educate attendees and to share lessons learned, including how the use of energy modeling and simulation helps to inform advanced sustainable building design and construction.
For ANNSIM 2023, Mohawk College will share how it is rising in the ranks of the most sustainable academic campuses. Learn more at https://www.mohawkcollege.ca/sustainability.

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Important Dates

Paper Submission: January 29, 2023 (Extended)
Author Notification (papers): March 7, 2023
Tutorials, Work-in-Progress, and PhD Colloquium Submission: March 20, 2023
Camera-Ready Paper Submission: March 20, 2023
Author Notification (Tutorials, Work-in-Progress, and PhD Colloquium Submission): April 10, 2023

Keynote #1: Kathleen M. Carley

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Prof. Kathleen M. Carley, Institute for Software Research, Carnegie Mellon University, Pennsylvania, USA

Presentation Title: Simulating Societal Systems: Issues in linking the micro and the macro

Presentation Abstract: Long, long ago in the land of simulation, the simulationist would make rules that controlled whether little squares on a giant piece of digital graph paper appeared to be dark or light. At issue was, could micro behavior by these “agents” effect large scale macro behavior for their “society.” Rules such as move to an unoccupied square if you are not near three others like you, resulted in behavior that was “human like” to the observers, that is the squares segregated on the basis of color. Success was declared. Now, fast forward to 2023, and the land of simulation looks very different. However, the foundational micro-macro congruence problem still exists and takes many forms. For example, does accurate micro behavior guarantee realistic macro behavior? Do micro-agents need to gain capabilities to generate more accurate social or macro-behavior? Do human observers believe the simulation macro results more as the micro-agents become more realistic? In this talk, questions regarding the micro-macro linkage in simulation models are addressed using a set of models and results associated with diverse applications. These applications include: threat assessment, pandemic interventions, and the growth of civil violence. It is argued that using simulation fruitfully at the micro and macro level is more impacted by human perception and the modeling of social cognition and emotional cognition than the exact level of realism used in creating congruence.

Biography: Kathleen M. Carley is a professor in the School of Computer Science in the department – of the Institute for Software Research – at Carnegie Mellon University. She also has courtesy appointments at Engineering and Public Policy Bio, Heinz School Bio, Electrical and Computer Engineering, and GSIA Bio.

She is the director of the Center for Computational Analysis of Social and Organizational Systems (CASOS), a university-wide interdisciplinary center that brings together network analysis, computer science, and organization science (www.casos.ece.cmu.edu). Kathleen M. Carley’s research combines cognitive science, social networks, and computer science to address complex social and organizational problems. Her specific research areas are dynamic network analysis, computational social and organization theory, adaptation and evolution, text mining, and the impact of telecommunication technologies and policy on communication, information diffusion, disease contagion, and response within and among groups, particularly in disaster or crisis situations. She and her lab have developed infrastructure tools for analyzing large-scale dynamic networks and various multi-agent simulation systems. The infrastructure tools include ORA, a statistical toolkit for analyzing and visualizing multi-dimensional networks. ORA results are organized into reports that meet various needs such as the management report, the mental model report, and the intelligence report. Another tool is AutoMap, a text-mining system for extracting semantic networks from texts and then cross-classifying them using an organizational ontology into the underlying social, knowledge, resource, and task networks.

Her simulation models meld multi-agent technology with network dynamics and empirical data. Three of the large-scale multi-agent network models she and the CASOS group have developed in the counter-terrorism area are: BioWar a city-scale dynamic-network agent-based model for understanding the spread of disease and illness due to natural epidemics, chemical spills, and weaponized biological attacks; DyNet a model of the change in covert networks, naturally and in response to attacks, under varying levels of information uncertainty; and RTE a model for examining state failure and the escalation of conflict at the city, state, nation, and international as changes occur within and among red, blue, and green forces. Dr. Carley is the director of the Center for Computational Analysis of Social and Organizational Systems (CASOS) which has over 25 members, including students, post-doctoral fellows, research staff, and faculty. She is the founding co-editor of the journal Computational and Mathematical Organization Theory which she now co-edits with Dr. Terrill Frantz. She has co-edited several books in the computational organizations and dynamic network area.

Keynote #2: Dawn M. Tilbury

Prof. Dawn M. Tilbury, Mechanical Engineering, University of Michigan, Ann Arbor Michigan, USA

Presentation Title: Digital Twins for Manufacturing Systems: Leveraging real-time information through modeling and simulation

Presentation Abstract: Advances in computing and networking technologies have enabled massive amounts of data to be collected from manufacturing plant floors, and stored either locally or in the cloud. Although data quality remains an important challenge, Digital Twins enable this data to be used, together with models of manufacturing processes, to create useful information and advise human operators on recommended actions. Standards for Digital Twins are emerging, and there are opportunities to create different types of Digital Twins that can best utilize the data that exists. In this talk, we will present a requirements framework for Digital Twins in the manufacturing domain, including the important properties of re-usability, interoperability, interchangeability, extensibility and maintainability. Several examples of digital twins that we have created will be presented, with potential outcomes of reduced costs and improved productivity. Future challenges and opportunities in the area of Digital Twins for manufacturing systems will also be discussed.

Biography: Dawn M. Tilbury is the inaugural Ronald D. and Regina C. McNeil Department Chair of Robotics at the University of Michigan, and the Herrick Professor of Engineering. She received the B.S. degree in Electrical Engineering from the University of Minnesota, and the M.S. and Ph.D. degrees in Electrical Engineering and Computer Sciences from the University of California, Berkeley. Her research interests lie broadly in the area of control systems, including applications to robotics and manufacturing systems. From 2017 to 2021, she was the Assistant Director for Engineering at the National Science Foundation, where she oversaw a federal budget of nearly $1 billion annually, while maintaining her position at the University of Michigan. She has published more than 200 articles in refereed journals and conference proceedings. She is a Fellow of IEEE, a Fellow of ASME, and a Life Member of SWE.


Tutorial I: A Tutorial on Bayesian Sequential Data Assimilation for Dynamic Data-Driven Simulation
Date | Time: Tuesday, May 23, 2023 | 4:00 p.m. –5:30 p.m.
Presenter: Xiaolin Hu
Location: I Wing, i104
Abstract: Data assimilation is an enabling technology for dynamic data driven simulation to support dynamic state estimation and online model calibration. It also plays an important role for enabling effective use of digital twin technology. This paper presents a tutorial on Bayesian sequential data assimilation for dynamic data driven simulation. A special interest is in data assimilation for discrete simulations. This tutorial targets the broader audience in the modeling and simulation community. It describes the sequential Bayesian filtering framework and introduces particle filters as a data assimilation method for general discrete simulation models. Several illustrative examples are provided to help beginners to grasp the concepts.

Tutorial II: Introductory Tutorial on Agent-Based Modeling and Simulation
Date | Time: Wednesday, May 24, 2023| 4:00 p.m.– 5:30 p.m.
Presenter: Charles Macal
Location: I Wing, i224
Abstract: Agent-based modeling (ABM) and simulation is an approach to modeling systems comprised of autonomous, interacting agents. People are often modeled as agents, but any type of entity, natural or artificial, having diverse characteristics and behaviors qualifies as an agent. Computational advances are making it possible to develop agent-based models in a variety of application areas, including areas where simulation has not been extensively applied. Applications range from modeling agent behavior in supply chains, consumer goods and financial markets, to predicting the spread of infectious disease and even understanding the factors responsible for the fall of ancient civilizations. Progress suggests that ABM could have far-reaching effects on the way that businesses and policy makers use computer models to support decision-making and how researchers use models as electronic laboratories to aid in discovery. Some contend that ABM “is a third way of doing science” and could augment traditional discovery methods for knowledge generation. This brief tutorial introduces agent-based modeling by describing key concepts of ABM, discussing some illustrative applications, and addressing toolkits and methods for developing agent-based models.

Tutorial III: Defining DEVS and Real-Time DEVS Models Using DEVS-Graphs Online Environment
Date | Time: Thursday, May 25, 2023| 9:00 a.m.—10:30 a.m.
Presenters: Cristina Ruiz Martin and Gabriel Wainer
Location: I Wing, i104
Abstract: Discrete Event System Specification (DEVS) is a mathematical formalism to model and simulate discrete-event dynamic systems. Using DEVS for modeling and simulation has numerous advantages, including a rigorous formal definition of models, a well-defined mechanism for modular composition, and a separation of concerns between the model definition and the simulation of the model, among others. DEVS-Graphs is a subset of DEVS that allows the modeler to think about the problem more abstractly and facilitates the communication of the model with domain experts. In this tutorial, we will introduce DEVS and DEVS-Graphs. We will also present an online tool to generate executable DEVS models in Cadmium from the DEVS-Graph specification. We will also discuss the Cadmium tool’s Application Programming Interface and explain how to implement those DEVS models that cannot be represented using DEVS-Graph.

Tutorial IV: Tools and Applications using Cosys-AirSim: A Real-Time Simulation Framework Expanded for Complex Industrial Applications
Date | Time: Thursday, May 25, 2023 | 3:30 p.m.– 5:00 p.m.
Presenters: Jean-Edouard Blanquart, Erik Verreycken, Wouter Jansen, Anthony Schenck, Nico Huebel, Connor Verhulst and Jan Steckel
Location: I Wing, i104
Abstract: Demonstration and tutorial of an expanded real time simulation framework for complex industrial applications (related to the paper Cosys-AirSim: A Real-Time Simulation Framework Expanded For Complex Industrial Applications) . Practical introduction, Setting up your own environment in Unreal, Explanation of sensor models and Applications.

Tutorial V: A Tutorial Introduction to Colored Petri Nets (CPNs) Based Modeling and Simulation
Date | Time: Friday, May 26, 2023| 9:00 a.m.—10:30 a.m.
Presenter: Vijay Gehlot
Location: I Wing, i104
Abstract: Colored Petri Nets (CPNs) extend the vocabulary of ordinary Petri Nets and add features that make them suitable for modeling large systems. CPNs combine the strengths of ordinary Petri Nets with the strengths of a high-level programming language. Petri Nets provide the primitives for process interaction, while the programming language provides the primitives for the definition of data types and the manipulations of data values. CPNs and the associated integrated development environment, CPN Tools, have been designed and developed with practical applications and ease of use in mind. This tutorial will introduce the audience to basics of CPNs as well as CPN Tools. We will illustrate the key ideas, underlying concepts, software tools, and modeling techniques by means of numerous real-life examples and live demonstrations that emphasize practical applications of CPNs and CPN Tools. It requires no prior familiarity with Petri nets, system design and analysis, modeling, simulation, or any particular computer language. Our demo includes approach and use of CPN Tools for building and executing hierarchical CPN models, which is useful in the context of model driven systems engineering for large systems. We also cover the details and use of the external process communications library of CPN Tools, which is useful in the context of hardware in the loop, co-simulation, as well as in combining AI/ML models with simulation models.


Annual Simulation Symposium (ANSS)
José Luis Risco Martín and Joachim Denil

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 Modeling and Simulation (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 simulationists in industry, government, and academia.

The purpose of this track is to highlight and advance rigorous experimental, 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 present research of all kinds, including case studies and applications.

Recommended topics in the track include, but are not limited to, the following with application to real-world problems:

● Advances in the field of M&S for implementation purposes
● Application of modeling formalisms into real world applications
● Rigorous comparisons across M&S techniques
● 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

Cyber Physical Systems (CPS)
Cláudio Gomes and Bentley James Oakes

Cyber-Physical Systems (CPS) are well-entrenched in our daily lives, including self-driving cars, Industry 4.0 machines, and smart grid technologies. This wide range of uses comes with many challenges stemming from the complex behaviour of heterogeneous CPS components interacting between themselves and the environment. This track focuses on new developments in Modelling and Simulation (M&S) which manage complexity for all stages of a CPS’ life-cycle, including design, verification, optimization, and monitoring.

Topics of interest include, but are not limited to:

● Applied Modelling and (Co-)Simulation of CPS
● Machine Learning for CPS
● Model-Based Digital Twins for CPS
● Model Creation/Recommendation Systems for CPS
● Collaborative Modelling and Simulation for CPS
● Techniques for Handling Uncertainty, Reliability, and/or Explainability in CPS
● (Co-)Simulation-Based Verification/Optimisation of CPS
● Low-Code Development of CPS
● (Co-)Simulation in Advanced Manufacturing and Industry 4.0
● Modeling and (Co-)Simulation as a Service for CPS
● Advanced and Visual Analytics for (Co-)Simulation of CPS

Emerging Topic – Digital Twins (ET-DT)
Guodong (Gordon) Shao and Istvan David

Digital twinning is a transformational trend in many domains, such as smart manufacturing, precision healthcare, and smart energy management. By enabling real-time synchronization with its physical counterpart, a digital twin can provide descriptive (what has happened?), diagnostic (why did it happen?), predictive (what will happen), and prescriptive (how can we make it happen?) functionalities. Many of these functionalities are enabled by simulation. Because of the multidisciplinary nature and complexity of digital twins, their correct and efficient development is especially challenging.

This track aims to provide a forum for researchers and practitioners alike to exchange their latest results and experiences in developing simulators for or by digital twins.

Topics of interest include, but are not limited to:

● Simulation and co-simulation for digital twins, simulation-based digital twins (simulators as the core of digital twins)
● Fidelity, scalability, reliability, trust, security of simulators in digital twins
● Real-time simulation
● Data analytics and data-driven techniques for digital twin development
● Architectural patterns of simulators in digital twinning
● Development lifecycle of digital twins
● Frameworks, methodologies, and formalisms for digital twin development
● Digital twins in support of the Digital Thread
● Digital twins in support of the metaverse
● Verification, Validation and Uncertainty Quantification (VVUQ) of digital twins
● Standards, standardization, and certification of simulators for digital twinning
● Case studies, industry applications, and experience reports
● Human factors in digital twins, such as simulation for or by the human-in-the-loop
● Digital twins for dynamic system (re)configuration and optimization
● Digital twins as a training environment

Humans, Societies and Artificial Agents (HSAA)
Taylor Anderson and Alison Heppenstall

Artificial societies have typically relied on agent-based models or cellular automata approaches that can capture the decision-making processes of individuals as they interact and respond to other individuals and their environment. This has supported a wide range of applications (e.g., in archaeology, economics, geography, psychology, political science, health and epidemiology) and research tasks (e.g., what-if scenarios or predictive models, models to guide data collection). Of particular interest are artificial societies where the individual agents’ behavior is guided by insights from computational social sciences and calibrated using real world data. These heterogeneous agents participate in social networks, which can be physical – such as those established in workplaces, schools, sporting events, etc. – or virtual, like chat groups of common interest. Agents are often mobile within an environment that exposes them to social determinants and physical constraints. Despite the many applications and resulting publications, there remain basic methodological challenges for modeling realistic human behavior i.e., agent representation, construction of behavioral rules, the degree to which behavioral theories and their assumptions are incorporated, validation and calibration of models representing complex social phenomena, as well as the detection and avoidance of unwanted or harvesting of welcomed emergent behavior on the societal level.

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 development and evaluation through simulations
● 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)

Machine Learning and Simulation (MLS)
Joon-Seok Kim and Andreas Züfle

Modeling and simulation (M&S) have advanced our understanding of complex systems, have improved our ability to predict future states, and have been leveraged to prescribe (near-)optimal interventions and policies in many different application areas. In the enterprise of exploring such complex systems, artificial intelligence and machine learning (AI/ML) have the potential to improve our ability to optimize simulation parameters, to train agent/actor behavior throughout simulations, and to evolve the simulation environment based on observations. The vision of this track is to push the boundaries of human understanding by marrying M&S with AI/ML.

This Machine Learning and Simulation (MLS) track is a dedicated forum to exchange our views, ideas, research methods, and applications to resolve the scientific questions of what and how cutting-edge AI/ML methods can synergize M&S and vice versa. This track explores M&S practices to which AI/ML methods are applied such as knowledge reasoning, computer vision, natural language processing, deep learning, and reinforcement learning.

In this track, we are seeking papers on original contributions across all modes of M&S leveraging AI/ML and interdisciplinary contributions that advance the state of the arts in AI/ML. This track will use the traditional format of having oral paper presentations. Topics of interest include, but not limited to:

● Advancing validation and verification (V&V) using AI and ML
● AI and ML methods for training and evolving agents
● Best practices of convergence of AI and Simulation
● Empirical comparisons of state-of-the-art AI and ML methods in M&S
● Facilitating experimentation using AI and ML
● M&S to improve AI and ML solutions
● Simulation modeling tools and methods based on AI and ML
● Simulation optimization using AI and ML
● Visionary methodology of AI and ML in simulation

M&S in Cybersecurity (MSCS)
Sachin Shetty and Danda Rawat

Modeling and Simulation has the ability to improve our understanding and gain better insights into the exploitability and impact of threat landscape in cyber systems underpinning several critical infrastructures. The emergence of Internet of Everything has resulted in the growth in interactions between humans, physical and cyber systems and there is an increased need to understand how these interactions could be exploited by adversaries. Modeling and simulation provide a cost-effective means to support research, development, refinement, deployment, and evaluation of the next generation of security solutions for preventing, detecting, 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 modeling and simulation of cybersecurity. The symposium will address all aspects of modeling, analyzing, design, simulation, implementation, deployment and management of security algorithms, protocols, architectures and systems. We encourage submissions related to all aspects of cybersecurity in a modeling and simulation context in a broad spectrum of application areas.

Topics of interest include, but are not limited to:

● Formal models for cybersecurity simulation
● Cybersecurity evaluation and assessment approaches
● Test beds and experimental infrastructure for cybersecurity simulation
● 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
● Risk assessment and management
● Systems engineering for security

M&S in Medicine (MSM)
Michel Audette and Jerzy W. Rozenblit

Medical and healthcare simulation span a variety of areas where medicine converges with Modeling and Simulation (M&S). Computer-based medical simulation emphasizes the application of computers to synthesizing the response of tissues to therapy, which represents a trade-off between fidelity to real tissue response and computational efficiency. High-fidelity medical/surgical simulation is typically used to provide experienced clinicians, including surgeons, with insight on how to optimize treatment of the patient, while high-efficiency simulation emphasizes real-time interactivity for haptics, typically used in conjunction with Virtual Reality (VR) visualization for skill acquisition and training. In both cases, a computer visualization of the anatomy is needed, however in the interactive case based on VR, this visualization must be also responsive in real-time, which presupposes highly efficient therapy models (e.g., cutting models) as well as relatively sparse anatomical models and collision models, where the latter determines where the therapy takes place, in conjunction with the pose of the haptic device. A related research area is the segmentation of medical images that map intensities to tissues and discretization (meshing) that converts tissues to elements. Another intensively researched area is the application of digital deep learning (deep neural networks- DNNs) to the synthesis of a neural computation within a medical context, such as to approximate a diagnosis or a tissue response to therapy, while exploiting the ability of the solution to learn.

Healthcare simulation is used to denote two areas that complement the above-described medical simulation. One the one hand, it is used to designate mannequin-based training systems and part-trainers, whose physical implementation is intended to develop proprioceptive understanding of therapies. On the other, this term also represents medical processes at a large scale, such as emergency rooms, and hospitals, to formulate an understanding of bottlenecks in patient treatment and improve efficiencies.

This track is particularly open to contributions in the following areas, though not exclusively:

● Simulation for healthcare systems
● Simulation of medical processes
● Simulation for care learning
● Simulation for elderly
● Sensing-based patient simulation
● Haptics-driven interactive simulation
● Predictive simulation
● Simulation training methods
● Age-based healthcare simulation
● Patient surgery simulation
● Therapy simulation
● Simulation patient safety
● Simulation of emergency situations
● Calibration of healthcare simulation tools
● Integrating simulation tools
● Interactive simulation tools
● Deep neural networks for computer-assisted medicine

Theory and Foundations for Modeling and Simulation (TMS)
Hessam Sarjoughian and Eugene Syriani

The TMS Track provides a forum to present the most recent advances in the Theory and Foundations of Modeling and Simulation. The focus is on the Modeling and Simulation concepts, methods, methodology, practice, and toolkits. The TMS Track welcomes unpublished papers on the topics below as well as others that can help deepen and expand the M&S Theory and Foundations for better understanding and development of computing, physical, and human systems.


● Modeling & Simulation Formalisms (Actors, DEVS, Petri nets, Statecharts, etc.)
● Multi-formalism Modeling, Hybrid Modeling Languages, Multi-Modal Modeling
● Multi-Resolution/Multi-Scale Modeling, Multi-Paradigm/Multi-Domain Modeling,
● Model Checking, Formalism-Based Model Debugging, Model Transformation
● Parallel, Distributed, Real-Time, Cloud-Based, and Interactive Simulation
● Modular Hybrid, Spatially Distributed, and Ultra Large-Scale Systems
● Co-simulation, Interoperability, Simulation Languages, Numerical Solvers
● Embedded, IoT, and Fog Computing Systems
● Model Development and Simulation Visualization Tools
● Model Libraries, Repositories, and Data Formats

Simulation of Architectural and Urban Design (SimAUD)
Gabriel Wurzer and Mohamed Aly Etman
Scientific Chair: Nina M. Sharifi

We invite you to submit your original research to SimAUD 2023, held as part of ANNSIM 2023. 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 Green House 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

Simulation Education and Simulation-Based Learning (SimEd)
Ashkan Negahban and Omar Ashour

The SimEd track is seeking submissions for papers, panels, and workshops related to the following two areas:

Simulation Education: This area focuses on teaching and learning simulation in engineering, sciences, social sciences, or any other discipline where simulation techniques are used. We welcome submissions that discuss and share pedagogical models, best practices, lessons learned, course projects, tools, case studies, and other resources for training the next generation of simulation experts.

Simulation-Based Learning (SBL): SBL refers to the use of simulation models and tools to enrich teaching and learning. SBL offers a wide range of opportunities for experiential learning and to practice critical thinking, problem-solving, and decision-making. Research shows that SBL is among the most effective ways to learn complex skills across different domains as it enables knowledge application in a virtual yet realistic environment. Moreover, SBL educational experiences can be made available to geographically dispersed students in support of remote and online learning. All learning situations are of interest (formal/informal, in-person/distance learning, K-12, Higher Education, Professional Training, Continuing Education, etc.)

Topics of interest include but are not limited to:

• Implementation and assessment of SBL in courses from any domain (engineering, sciences, social sciences, etc.)
• Problem-/project-based, experiential, and collaborative learning via SBL
• Skill development and workforce training via SBL
• SBL in online, in-person, and blended learning models
• Immersive simulated learning environments (augmented, virtual, and mixed reality, immersive game-based learning)
• Comparative studies on the effectiveness of SBL vs other teaching and learning methods
• Learning analytics in SBL

Sustainability and Energy Systems (S&ES)
Kishwar Ahmed and Marco Pruckner

Standing at the center of climate change, sustainability is one of the greatest challenges and opportunities of this century. The sustainability and energy systems (SES) track provides a forum to present the latest developments in modeling and simulation of sustainability and energy systems. Modeling and simulation can be an effective tool to design sustainable systems, that includes software applications in the field of energy systems. We welcome collaborative works with different and disjoint disciplines such as computer and data sciences, energy, applied math or environmental sciences. In particular, this call for papers asks modeling and simulation contributions in the following fields:

● Decision making in sustainability and energy systems
● Environmental and emerging simulation challenges of sustainable systems
● Building energy systems, e.g., data centers
● Smart Grids
● Energy-efficient cloud computing
● Internet-of-things energy consumption
● ML applications sustainability concerns
● HVAC energy systems
● Twin city sustainability
● Carbon mitigation strategies

Symposium on Performance Evaluation of Computer and Telecommunication Systems / Communications and Network Simulation (SPECTS/CNS)
Malamati Louta, George Karetsos, Abdolreza Abhari and Ala’a Al-Habashna

Over the years, topics related to communication, computer and network research have expanded from traditional computer networking systems to emerging systems and technologies such as Internet of Things and to intelligent network-based systems in broader contexts.

SPECTS/CNS provides a forum for professionals and researchers to discuss and disseminate the most promising contributions on performance evaluation of current and emerging computer and communication systems, technologies and networks. Papers describing results of theoretic and/or practical significance are solicited. Experimental, modeling, analysis, optimization and simulation studies as well as testbed deployment, field trials and experiences gained are all in the scope of this track. Work presenting novel performance evaluation methods or providing insights on design and runtime tradeoffs are particularly encouraged. All papers describing design principles, simulation methodologies and practices, as well as applications performance modeling and evaluation pertinent (but not limited) to the following topics are welcome:

● AI and ML in communications and networking and computer systems
● Data Science, Big Data Analysis in communications, networking and computer systems
● Next Generation Internet of Things, enabling technologies and intelligent applications (Architecture, networking technologies, smart-cities, health-care systems, smart environment, smart mobility, precision agriculture, livestock, smart sustainability)
● 5G/6G and Beyond and enabling technologies (mmWave communications, Terahertz communications, massive MIMO, Intelligent Reflective Surfaces, etc.), Device to Device communications
● Software Defined Networking and Network Function Virtualization
● Edge/Fog/Cloud Computing, Distributed Systems
● Green and energy efficient communications and networking
● Cooperative communications and networking
● Cognitive radio and networking, Future Radio Access Networks
● Optical-Wireless communication and systems, Wireless ad-hoc Networks/ Wireless Sensor Networks/ Delay Tolerant Networks/ Opportunistic Networks/ Peer-to-Peer networking and computations
● Social networks 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 simulation and applications

Other Submissions

Work-in-Progress (WiP)
Ali Kucukozyigit

The Work in Progress (WIP) section of the conference seeks submissions reporting on highly innovative research that is not yet quite ready for a full-length publication. The goal is to foster a discussion of early scholarly works that are at intermediary stages of their development. This will enable participants to focus the discussion on foundational, conceptual and implementation aspects of their work even though the ultimate results have not been reached or validated. WIP will help participants assess the potential impact of a developing research idea and obtain constructive feedback and suggestions on ongoing research. Student papers are welcome as long as the paper is not about their drafted PhDs. For dissertation work, please submit to the PhD Colloquium.
All papers will undergo an evaluation by the WIP Committee and the papers accepted in this track will also be published in the USB proceedings and is planned to be uploaded to the SCS website.
The topics of interest for WiP papers are like those of the main conference tracks. Authors can submit any modeling and simulation related topics that are not fully ready for full paper submission. WiP paper submissions are submitted through an extended abstract (max 2 pages) and, if accepted, presented in the form of a short presentation and a poster. Submissions to the WiP track will be reviewed by the WiP program committee. As for any accepted submissions at ANNSIM’23, authors are expected to register for the conference and present their work. Please refer to the “IMPORTANT DATES” tab above for more details.”

Simon Gorecki and Scott Rosen

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 2022 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.
Proposals should be one to two pages and must include the following information:
● Title of the workshop/tutorial and description (max 2 pages)
● Organizers and their affiliations (including short bios)
● Expected duration of the workshop/tutorial: 90 minutes, 120 minutes, a half-day, or full day.
● If the proposal type is:
○ Workshop: provide sample call for papers, including workshop main topics.
○ Tutorial: provide an abstract of the tutorial (up to 2 pages). A tutorial may submit a full paper to one of the related technical tracks and if accepted after peer-review, it will appear in the conference proceedings.
Tutorial/workshop proposals should be submitted to the tutorial section in the conference system.

PhD Colloquium
Hoda Khalil

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.

Who should participate?
Students at all stages of their Ph.D. program who are working on a thesis topic relevant to ANNSIM tracks are encouraged to participate in this track.

Submissions Requirements
● Students interested in participating in the colloquium should submit a 2-page description of their dissertation. The abstract should have a single author (the student) and must be formatted using the Submission Guidelines on the conference page (https://scs.org/annsim). The advisor should be included in the acknowledgments.
● The advisor of the participating student must e-mail a letter of recommendation in support of the student’s application to the Ph.D. Colloquium chair (hoda.khalil@cmail.carleton.ca) with the subject “ANNSIM 2023 Ph.D. Colloquium Recommendation”. This letter should include the student’s name, a candid assessment of the current status of their dissertation research, a list of publications on the topic so far (if any), and an expected date for dissertation submission.

Submissions will be reviewed by at least two members of the Ph.D. Colloquium committee. Authors of selected submissions must attend the conference and present their work during the conference to get feedback from the Colloquium panel. The 2-page submissions will be available on the conference website but they will not be archived in the proceedings.

Important Dates
The Ph.D. colloquium will follow the deadlines of the conference Tutorials and Work in progress papers. Please refer to the conference main page for more details. Please refer to the “IMPORTANT DATES” tab above for more details.”

Featured Speaker: Baher Abdulhai, Ph.D., P.Eng.
Talk: Mindset Transformation from a Ph.D. Grad to Professorship – Dream Big

PhD Keynote

Professor and Director, Toronto Intelligent Transportation Systems Centre
Co Director, iCity Centre for Automated and Transformative Transportation Systems – iCity CATTS.
Department of Civil and Mineral Engineering, University of Toronto
35 St. George St., #105, Toronto, Ontario, Canada M5S 1A4
YouTube: The traffic game – can traffic lights learn to be smart? Baher Abdulhai at TEDxUTSC

Baher Abdulhai has been a professor at the University of Toronto since 1998. Born in Cairo, Egypt in 1966, and earned his Ph.D. in engineering from the University of California Irvine, Irvine, California, USA, in 1996.

Prof. Baher Abdulhai has 35 years of experience in transportation systems engineering and Intelligent Transportation Systems (ITS). He is the founder and Director of the Toronto ITS Centre and the founder and co-Director of i-City Centre for Automated and Transformative Transportation Systems (iCity-CATTS). Abdulhai received several awards including IEEE Outstanding Service Award, Teaching Excellence award, and research awards from Canada Foundation for Innovation, Ontario Research Fund, and Ontario Innovation Trust. He served on the Board of Directors of the Government of Ontario (GO) Transit Authority from 2004 to 2006. He served as a Canada Research Chair (CRC) in ITS from 2005 to 2010. The ITS Centre won the Ontario Showcase Merit Award of Excellence and the National GTEC Bronze Medal Award in 2005. His research team won international awards including the International Transportation Forum innovation award in 2010 (Hossam Abdelgawad), IEEE ITS 2013 (Samah El-Tantawy) and INFORMS 2013 (Samah El-Tantawy). In 2014, he won the University of Toronto Inventor of the Year Award. In 2015 he has been inducted as a Fellow of the Engineering Institute of Canada (EIC). In 2018, he won the prestigious CSCE Sandford Fleming (Career Achievement) Award for his contribution to transportation in Canada. He has been elected Fellow of the Canadian Academy of Engineering in 2020. In 2021, he won the Ontario Professional Engineers Awards (OPEA) Engineering Medal for career Engineering Excellence.

Areas of Expertise: Intelligent Transportation Systems (ITS), modelling and simulation of large-scale dynamic transportation networks, Artificial Intelligence (AI) based street and freeway traffic control, emergency evacuation optimization, dynamic congestion pricing, smart cities under automated and transformative transportation systems.

Submission Guidelines

Where to submit: For all submissions, unless noted otherwise in their guidelines, go to https://www.softconf.com/sim/ANNSIM23/

Authors of accepted papers are expected to attend the conference, present their work to their peers, transfer copyright, and pay a conference registration fee at the time their camera-ready paper is submitted. Conference proceedings may be submitted to the ACM and IEEE Digital Libraries, for archiving and indexed in DBLP Computer Science Bibliography and SCOPUS. Some exceptions apply.

The ANNSIM’23 organization committee will invite a list of highly rated accepted papers to an extended paper submission for a special issue at SIMULATION: Transactions of The Society for Modeling and Simulation International.

General Technical Papers

Original, high-quality technical papers are solicited for review, possible presentation and subsequent publication in the conference proceedings. Papers are max 12 pages long with single column format (see author’s kit at https://scs.org/authorskit). Papers must not have appeared before (or be pending) in a journal or conference with published proceedings, nor may they be under review or submitted to another forum during ANNSIM’23 review process. All submissions will be peer reviewed by a minimum of 3 reviewers and feedback will be provided.

Please ensure that author names and institutions are replaced with placeholder text to follow the double-blind review process and to maintain the overall paper page length limit. Also, please note that the 12-page limit includes authors bios and the references.

The copyright form can be found in the authors kit at this link: https://scs.org/authorskit/.

It can also be downloaded at this link here.


We are seeking proposals for workshops and tutorials, which can be scheduled for 90 minutes, 120 minutes, a half-day, or full day. The conference and the workshop/tutorials are scheduled to take place in person at Mohawk College in Ontario, Canada.

Work-in-Progress (WiP)

The topics of interest for WiP papers are like those of the main conference tracks. Authors can submit any modeling and simulation related topics that are not fully ready for full paper submission. WiP paper submissions are submitted through an extended abstract (max 2 pages) and, if accepted, presented in the form of a short presentation and a poster.

PhD Colloquium

• Students interested in participating in the colloquium should submit a 2-page description of their dissertation. The abstract should have a single author (the student) and must be formatted using the authors’ kit. Your advisor should be included in the acknowledgments.
• The advisor of the participating student must e-mail a letter of recommendation in support of the student’s application to the PhD Colloquium chair (hoda.khalil@cmail.carleton.ca) with the subject “ANNSIM 2023 PhD Colloquim Recommendation”. This letter should include the student name, a candid assessment of the current status of their dissertation research, list of publications on the topic so far (if any), and an expected date for dissertation submission.

All presented work will be available to conference attendees electronically.

Registration & Pricing



*IEEE and IEEE Computer Society Members are eligible to receive the member registration fee.

*Manual Registration and Verification Forms:

Student Verification Form
Retiree Verification Form
Manual Registration Form

Electronic Travel Authorization

Visa Invitation Request Form
If you are from a foreign country, an author of an accepted conference paper & need a Conference Invitation letter for your visa, you must complete & submit the Visa Invitation form. Note: Visa Invitation Letters are provided ONLY to authors with accepted conference papers and who have paid their registration to the conference.

Cancellation Policy

Student Scholarship (US-Only) ----- NEW!

There will be NSF funding SUPPORT for US-based graduate students who seek to attend ANNSIM’23. To apply for this funding, students may submit regular papers (due Jan 29th) as well as work-in-progress or PhD Colloquium manuscripts, due March 20th. Student authors of accepted papers will receive a link (at acceptance) to complete a form requesting NSF funding. You can reach out to Philippe Giabbanelli at giabbapj@miamioh.edu if you have any questions regarding this support.

Venue & Hotels

Venue Address
Mohawk College
135 Fennell Avenue West
Hamilton, ON, Canada L9C 0E5
Ph: 905-575-1212

Located at the edge of the Hamilton escarpment, Fennell Campus has undergone the largest renovation in Mohawk history. Re-designed as a welcoming place to live and learn, the renewal has created a modernized space while enhancing energy efficiency, barrier-free access and more. Whether you choose to live in residence or in an off-campus neighborhood, at Fennell Campus you’ll feel at home.

Electronic Travel Authorization

The conference attire is business casual.

Hotel Accommodation Options

Residence & Conference Centre- Hamilton ( Mohawk Residence)
Located right next to Mohawk College, Fennell Campus

245 Fennell Avenue West
Hamilton, ON L9C 7V7

Group Rate (CAD) $89.95+HST single-double occupancy. Two-bedroom suite, group rate includes parking & WIFI.

To book online: Visit BOOKHAMILTONDIRECT 

1) Enter Arrival & Departure Dates.
2) Click on the word ‘PROMO CODE’.
3) Promo Code: SCI23 into the box below the Check In & Check Out Dates (group rate available from May 21-26, 2023).
4) Click on the blue Apply Button.
5) Cut-off date of book the group rate is MAY 1, 2023 (or based on availability)

You can call the property direct at (905) 641-4435 and provide them with the promo code SCI23.

Other Options

Staybridge Suites Hamilton – Downtown
20 Caroline St S, Hamilton, ON L8P 0B1, Canada
0.7 miles from Mohawk College

Days Inn by Wyndham Hamilton
210 Main St E, Hamilton, ON L8N 1H3, Canada
1.5 miles from Mohawk College

Homewood Suites By Hilton Hamilton, Ontario, Canada
40 Bay St S, Hamilton, ON L8P 0B3, Canada
0.8 miles from Mohawk College

Sheraton Hamilton Hotel
116 King St W, Hamilton, ON L8P 4V3, Canada
0.9 miles from Mohawk College

Towneplace Suites Hamilton
1195 Upper James St, Hamilton, ON L9C 3B2, Canada
3.1 miles from Mohawk College

Courtyard by Marriott Hamilton
1224 Upper James St, Hamilton, ON L9C 3B1, Canada
3.2 miles from Mohawk College

Hotel C by Carmen’s, BW Premier Collection
1530 Stone Church Rd E, Hamilton, ON L8W 3P9, Canada
5.6 miles from Mohawk College

Comfort Inn Hamilton
183 Centennial Pkwy N, Hamilton, ON L8E 1H8, Canada
6.6 miles from Mohawk College

Sandman Hotel Hamilton
560 Centennial Pkwy N, Hamilton, ON L8E 0G2, Canada
6.7 miles from Mohawk College

Four Points by Sheraton Hamilton – Stoney Creek
49 Goderich Rd, Hamilton, ON L8E 4W8, Canada
6.6 miles from Mohawk College


There are many alternatives to get to campus without driving alone. In fact, 70% of our students get to campus by transit, carpool, bike, or walking, because they know it saves money and is less stressful. Explore your transportation options.

Bus Pass and Transit Information
There are many options to consider when planning your route to campus and Mohawk Sustainability is here to help.
Use the resources listed below to make your transportation plan!
Don’t forget to check out and access the transportation discounts that are available to you!

Map your route to Campus

Use Google Maps to plan your route.

Student Transit Discounts

The Mohawk Students’ Association and some local transit providers offer discounted rates for students. This makes transit a more affordable option. Learn more about the various discounts available below.

Transit Provider Information

The City of Hamilton’s local transit provider is HSR – Hamilton Street Railway. Regional transit in the GTHA is provided by GO Transit. Local accessible transit in Hamilton is provided by DARTS. Learn more about the transit providers and their services below.

Organizing Committee

General Chair: Hamdi Kavak, George Mason University, USA
Vice-General Chair: Philippe Giabbanelli, Miami University, USA
Program Chair: Cristina Ruiz Martin, Carleton University, Canada
Proceedings Chair: Maria Julia Blas, Instituto de Desarrollo y Diseño INGAR (CONICET-UTN), Argentina
Awards Chair: Mamadou Kaba Traore, University of Bordeaux, France​

Program Committee

• Abdurrahman Alshareef, Arizona State University, United States
• Patricia Arroba, Universidad Politecnica de Madrid, Spain
• Souvik Barat, Tata Consultancy Services Research, India
• Eva Besada Portas, Universidad Complutense de Madrid, Spain
• Paul-Antoine Bisgambiglia, CNRS – University of Corsica, France
• Dominique Blouin, Telecom ParisTech, France
• Frédéric Boulanger, Université Paris-Saclay, LMF, CentraleSupélec, France
• Samira Briongos Herrero, NEC Laboratories Europe, Germany
• Roman Cardenas, Universidad Politecnica de Madrid, Spain
• Maximiliano Cristia, Universidad Nacional de Rosario, Argentina
• Ranjita Dash, National Institute of Technology, Rourkela, India
• Robson De Grande, Brock University, Canada
• Joachim Denil, University of Antwerp, Belgium
• Lorenzo Donatiello, University of Bologna, Italy
• Ta Duong, Singapore Management University, Singapore
• Gabriele D’Angelo, University of Bologna, Italy
• Alberto Falcone, University of Calabria, Italy
• Mohammed Farhan, The University of Texas at Arlington, United States
• Erika Frydenlund, Old Dominion University, United States
• Simon Gorecki, University of Bordeaux, France
• Xiaolin Hu, Georgia State University, United States
• Hai Le, Georgia State University, United States
• Pedro Malagon, Universidad Politécnica de Madrid, Spain
• Peter Maurer, Dept. of Computer Sci., Baylor University, United States
• Saurabh Mittal, The MITRE Corporation, United States
• Josué Pagán, Technical University of Madrid, Spain
• Randy Paredis, University Of Antwerp, Belgium
• Shengrui Peng, Research Centre L3S, Germany
• Francesco Quaglia, DIAG – Sapienza Universita’ di Roma, Italy
• Daniel Rippel, BIBA – Bremer Institut für Produktion und Logistik GmbH at the University of Bremen, Germany
• Jose L. Risco-Martin, Universidad Complutense de Madrid, Spain
• Óscar Rodríguez Polo, Universidad de Alcala, Spain
• Lynne Serre, Defence Research and Development Canada, Canada
• Mirko Stoffers, RWTH Aachen University, Germany
• Mamadou TRAORE, University of Bordeaux, France
• Alfonso Urquia, UNED, Spain
• Gabriel Wainer, Carleton University, Canada
• Pia Wilsdorf, University of Rostock, Germany
• Levent Yilmaz, Auburn University, United States
• Greg Zacharewicz, IMT – Mines Ales, France
• Bahram Zarrin, Microsoft, Denmark
• Fernando Barros, Universidade de Coimbra, Portugal
• Johan Bergelin, Mälardalen University, Sweden
• Paolo Bocciarelli, University of Rome, Italy
• Walter Commerell, Technische Hochschule Ulm, Germany
• Virginie Galtier, CentraleSupélec, France
• Rhys Goldstein, Autodesk Research, Canada
• Eduard Kamburjan, University of Oslo, Norway
• Joost Mertens, University of Antwerp, Belgium
• Marina Rantanen Modeer, Technische Universität Dortmund, Germany
• Yon Vanommeslaeghe, University of Antwerp, Belgium
• Maria Julia Blas, Universidad Tecnologica Nacional, Argentina
• Stefan Boschert, Siemens, Germany
• Lena Buffoni, Linköping University, Sweden
• Loek Cleophas, TU Eindhoven, The Netherlands
• Mirgita Frasheri, Aarhus University, Denmark
• Sumin Jeon, Henkel, Singapore
• Al Jones, NIST, USA
• Deo Kibira, NIST, USA
• Inki Kim, University of Illinois Urbana-Champaign, USA
• Istvan Komlosi, KUKA Robotics, Hungary
• Daniel Lehner, Johannes Kepler University, Austria
• Carla Martin Villalba, National Distance Education University, Spain
• Laetitia Monnier, NIST, USA
• Paula Muñoz, University of Malaga, Spain
• Elisa Negri, Politecnico Milano, Italy
• Roland Rosen, Siemens, Germany
• Feng Shaw, NIST, USA
• Rishabh Venkatesh, NIST, USA
• Petra Ahrweiler, Johannes Gutenberg University Mainz, Germany
• Kuldip Singh Atwal, George Mason University, USA
• Jen Boyd, University of Glasgow, UK
• Thomas Clemen, Hochschule für Angewandte Wissenschaften Hamburg, Germany
• Andrew Crooks, University at Buffalo, USA
• Suzana Dragicevic, Simon Fraser University, Canada
• Dawn Parker, University of Waterloo, Canada
• Liliana Perez, University of Montreal, Canada
• Nathalie Pinede, Université Bordeaux Montaigne, France
• Gary Polhill, James Hutton Institute, UK
• Dhananjai Rao, Miami University, USA
• Nanda Wijermans, Stockholm University, Sweden
• Sarah Wise, University College London, UK
• Taylor Anderson, George Mason University, USA
• Richard Flournoy, MITRE, USA
• Ross Gore, Old Dominion University, USA
• Yasanka Horawalavithana, Pacific Northwest National Laboratory, USA
• Hyunjee Jin, Siemens, USA
• Jeon-Young Kang, Kyung Hee University, Korea
• William Kennedy, George Mason University, USA
• Joon-Seok Kim, Oak Ridge National Laboratory, USA
• Kyoung-Sook Kim, National Institute of Advanced Industrial Science and Technology, Japan
• Dieter Pfoser, George Mason University, USA
• Ignacio Segovia-Dominguez, University of Texas at Dallas, USA
• Ashwin Shashidharan, Environmental Systems Research Institute, Inc., USA
• Paul Torrens, New York University, USA
• Srikanth Yoginath, Oak Ridge National Laboratory, USA
• Andreas Züfle, Emory University, USA
• Md ali reza Al amin, Old Dominion University, USA
• BISWAJIT BISWAL, South Carolina State University, USA
• Uttam Ghosh, Meharry Medical College, USA
• Sarada Prasad Gochhayat, Villanova University, USA
• Kamrul Hasan, Old Dominion University, USA
• Charles Kamhoua, US Army Research Laboratory, USA
• Xueping Liang, UNCG, USA
• Juan Zhao, Vanderbilt University Medical Center, USA
• Sachin Shetty, Old Dominion University, USA
• Deepak Tosh, El Paso, United States
• Danda Rawat, Howard University, USA
• Ismail Abbas, Hospital Clinic of Barcelona, Spain
• Andreas Attenberger, FH Kufstein University of Applied Sciences, Austria
• Michel Audette, Old Dominion University, USA
• Deniz Cetinkaya, Bournemouth University, UK
• Rachel Clipp, Kitware, Inc., USA
• Hadrien Courtecuisse, CNRS, France
• Francesca De Crescenzio, University of Bologna, Italy
• Makarand Deo, Norfolk State University, USA,
• Gregory Ditzler, University of Arizona, USA
• Dominique Duncan, University of Southern California
• Wolfgang Fenz, RISC Software GmbH, Austria
• Michael Giretzlehner, RISC Software GmbH, Austria
• Feng Gu, College of Staten Island, USA
• Minsik Hong, University of Arizona, USA
• Christopher Paolini, San Diego State University, USA
• Marco Parente, FEUP, Portugal
• Michael Polanco, Old Dominion University, USA
• Jerzy Rozenblit, University of Arizona, USA
• Johannes Sametinger, JKU, USA
• Carmen Paz Suarez-Araujo, Universidad de Las Palmas de Gran Canaria, Spain
• Austin Tapp, Children’s National Hospital, USA
• Przemysław Śliwiński, Wrocław University of Science and Technology, Poland
• Burkhard Stiller, UZH, Switzerland
• Omar Abbaas, The University of Texas at San Antonio, USA
• Daniel Knight, University of Colorado Boulder, USA
• Christian Lopez, Lafayette College, USA
• Konstantinos Mykoniatis, Auburn University, USA
• Ajla Aksamija, School of Architecture, University of Utah, United States
• Haşim Altan, Prince Mohammad bin Fahd University, Saudi Arabia
• Mohamed Aly Etman, Yale University Center for Ecosystems + Architecture, United States
• Spyridon Ampanavos, Harvard Graduate School of Design, United States
• Ding Wen ‘Nic’ Bao, RMIT University School of Architecture and Urban Design, Australia
• Ardavan Bidgoli, Carnegie Mellon University, United States
• Johannes Braumann, Robots in Architecture | UfG Linz, Austria
• Gustavo Carneiro, Regulatory Agency for Water, Energy and Sanitation (ADASA), Brazil
• Giorgia Chinazzo, Northwestern University, United States
• Ugo Maria Coraglia, Alma Mater Studiorum – University of Bologna, Italy
• Francesco De Luca, Tallinn University of Technology, Estonia
• Pieter de Wilde, University of Strathclyde, United Kingdom
• Elif Erdine, Architectural Association (AA) School of Architecture, United Kingdom
• Pau Fonseca, Universitat Politènica de Catalunya, Spain
• Marjan Ghobad, Independent Researcher, Germany
• Paula Gomez, Georgia Tech Research Institute, United States
• Sol Haroon, Georgia Institute of Technology, United States
• Navid Hatefnia, BuroHappold Engineering/ Technical University of Munich, Germany
• Brandon Haworth, University of Victoria, Canada
• Mohammad Heidarinejad, Assistant Professor, Illinois Institute of Technology, United States
• Nathaniel Jones, Arup, United States
• Odysseas Kontovourkis, University of Cyprus, Cyprus
• Christiane M Herr, Southern University of Science and Technology, China
• Eleanna Panagoulia, Georgia Institute of Technology, United States
• Cheol-Soo Park, Seoul National University, Republic of Korea
• Terri Peters, Toronto Metropolitan University, Canada
• Vinu Subashini Rajus, CMHC, Canada
• Davide Schaumann, Technion – Israel Institute of Technology, Israel
• Mathew Schwartz, New Jersey Institute of Technology, United States
• Rudai Shan, Northeastern University (China),
• Nina Sharifi, Syracuse Unversity, United States
• Yasaman Tahouni, Institute for Computational Design and Construction (ICD), University of Stuttgart, Germany
• Martin Tamke, CITA / KADK, Denmark
• Walid Tizani, The University of Nottingham, United Kingdom
• Thanos Tzempelikos, Prof, United States
• Margarita Vinnikov, NJIT, United States
• Peter von Buelow, University of Michigan, United States
• Rufei Wang, Atelier Ten, United States
• Ramon Weber, Massachusetts Institute of Technology, United States
• Gabriel Wurzer, TU Wien, Austria
• Ayesha Afzal, Friedrich-Alexander-University Erlangen-Nuremberg, Germany
• Kazi Asifuzzaman, Oak Ridge National Laboratory, United States
• Peter Bazan, Friedrich-Alexander-University Erlangen-Nuremberg, Germany
• Konstantin Hopf, University of Bamberg, Germany
• Leo Strobel, University of Wurzburg, Germany
• Samia Tasnim, The University of Toledo, United States
• Kazutomo Yoshii, Argonne National Laboratory, United States
• George T. Karetsos, University of Thessaly, Greece
• Abdolreza Abhari, Toronto Metropolitan University(formerly Ryerson University), Canada
• Peristera Baziana,University of Thessaly, Greece
• Minas Dasygenis, University of Western Macedonia
• Benjamin Earle,Carleton University, Canada
• Joaquin Entrialgo, University of Oviedo, Spain
• Helen Karatza, University of Thessaloniki, Greece
• Zbigniew Kotulski, Warsaw University of Technology,Poland
• Susan Lincke, University of Wisconsin-Parkside, USA
• Luisa Massari,University of Pavia, Italy
• Hassan Rajaei, Bowling Green State University, USA
• Georgios L. Stavrinides, University of cyprus, Cyprus
• Iraklis Varlamis, University of Athens, Greece
• Bernd Wolfinger, University of Hamburg, Germany
• Philipp Andelfinger, University of Rostock, Germany
• Fernando Barros, University of Coimbra, Portugal
• Maria Julia Blas, Instituto de Desarrollo y Diseño INGAR (CONICET), Argentina
• Paolo Bocciarelli, University of Rome Tor Vergata, Italy
• Frédéric Boulanger, Centrale Supélec, France
• Rodrigo Castro, Universidad de Buenos Aires, Argentina
• Franco Cicirelli, ICAR-CNR, Italy
• Cristia, Maximiliano, CIFASIS and UNR, Argentina
• Andrea D’Ambrogio, University of Rome Tor Vergata, Italy
• Robson de Grande, Brock University, Canada
• Juan de Lara, Universidad Autonoma de Madrid, Spain
• Alberto Falcone, University of Calabria, Italy
• Pau Fonseca, Universitat Politècnica de Catalunya, Spain
• Claudia Frydman, Aix-Marseille University, France
• Olaf Hagendorf, Hochschule Wismar, Germany
• Moath Jarrah, Jordan University of Science and Technology, Jordan
• Laetitia Li, FAST Labs, BAE Systems, United States of America
• Imran Mahmood, National University of Sciences and Technology, Pakistan
• Steve McKeever, Uppsala University, Sweden
• Saurabh Mittal, The MITRE Corporation, United States of America
• Il-Chul Moon, KAIST, Republic of Korea
• Alexandre Muzy, Côte d’Azur University, France
• Andreas Naderlinger, University of Salzburg, Austria
• Eva Navarro-López, University of Wolverhampton, United Kingdom
• James Nutaro, Oak Ridge National Laboratory, United States of America
• Bentley Oakes, Université de Montréal, Montreal, Canada
• Thorsten Pawletta, Wismar University of Applied Sciences, Germany
• Herbert Praehofer, Johannes Kepler University Linz, Germany
• Moon Gi Seok, Nanyang Technological University, Singapore
• Ange Lionel Toba, Idaho National Laboratory, United States of America
• Enrico Tronci, Università di Roma, La Sapienza, Italy
• Alfonso Urquia, UNED, Spain
• Andrea Vandin, Sant’Anna School of Advanced Studies, Italy
• Philip Wilsey, University of Cincinnati, United States of America
• Cecilia Zanni-Merk, INSA Rouen Normandie, France
• Ala’a Al Habashna, Carleton University, Canada
• Joseph Boi-Ukeme, Carleton University, Canada
• Khaldoon Al-Zoubi, Jordan University of Science and Technology, Jordan
• Scott Rosen, The MITRE Corporation, USA
ACM-In-Cooperation_medium (1)






Questions? Call Phone: 858-277-3888 or Email scs@scs.org