Leigh Tesfatsion received the Ph.D. degree in economics from the University of Minnesota, Mpls., in 1975, with a minor in mathematics. She is Research Professor of Economics, Professor Emerita of Economics, and Courtesy Research Professor of Electrical & Computer Engineering, all at Iowa State University. Her principal current research areas are electric power market design and the development of Agent-based Computational Economics (ACE) platforms for the performance testing of these designs. She is the recipient of the 2020 David A. Kendrick Distinguished Service Award from the Society for Computational Economics (SCE) and an IEEE Senior Member. She has served as guest editor and associate editor for a number of journals, including the IEEE Transactions on Power Systems, the IEEE Transactions on Evolutionary Computation, the Journal of Energy Markets, the Journal of Economic Dynamics and Control, the Journal of Public Economic Theory, and Computational Economics. Online Short Bio

Alma Mater: FT Ranked No. 10 Business Economics school.
Ranked No 1 in an engineering mathematics national level test.
Ranked No 1 in an analytics program at IIT Bombay.
B.E. Mechanical Engineering.
MTech 1st year Modelling and Simulation.
PhD 1st year Strategy Simulation at The University of Texas at Dallas.
Tuition scholarships at the Santa Fe Institute.
GMAT 730
5 years of operations research work experience.
Published and presented a poster at the The Operational Research Society, UK Annual Conference 2021 integrating strategy and applied math. Took on and resolved a longstanding problem.
Solo authored leadership article in the Analytics magazine Nov/Dec 2021 issue from INFORMS.
Solo authored theoretical optimization abstract at the ICORES 2022 Conference.
Authoring the black-tie, board room manual - The Change Management Series Volume 1 Kindle edition on Amazon March, 2022.
I am a participant at the Financial Modeling World Cup 2022.
Build spiders for scraping web data.

S.R. Aurora, also known as Mai P. Trinh, is an Assistant Professor of Management at The University of Texas Rio Grande Valley. Her interdisciplinary work intersects leadership, complex systems science, education, technology, and inclusion. Her research harnesses technology to cultivate future leaders and helps people thrive in our volatile, uncertain, complex, and ambiguous (VUCA) high-tech world, aligning with four United Nations’ sustainable development goals: Quality education (#4), Gender equality (#5), Decent work and economic growth (#8), and Reduced inequalities (#10). She has published in top-tiered peer-reviewed journals such as The Leadership Quarterly and The Academy of Management Learning and Education and received multiple national and international awards for her research, teaching, and mentoring. Dr. Aurora earned her doctoral degree in Organizational Behavior from the Weatherhead School of Management at Case Western Reserve University in 2016.

Ronja Hotz is a PhD student in the Land Use Change & Climate Research Group at the Karlsruhe Institute of Technology, where she has been working since August 2023. Her research focuses on understanding and modelling the social processes underlying land use change using agent-based modelling, with a particular emphasis on the CRAFTY framework. She holds a Bachelor’s degree in Physics from Freie Universität Berlin and a Master’s degree in Theoretical Physics from Technische Universität Berlin.

Prior to her PhD, she worked at the Potsdam Institute for Climate Impact Research, where she implemented a generic decision-making layer for land managers in agent-based socio-ecological models. The framework was analysed in a stylised model to investigate emergent dynamics and critical transitions and was subsequently integrated into the InSEEDS model, which simulates the adoption of conservation agriculture at regional to global scales.

I have a strong background in building and incorporating agent-based simulations for learning. Throughout my graduate career, I have worked at the Center for Connected Learning and Computer Based Modeling (CCL), developing modeling and simulation tools for learning. In particular, we develop NetLogo, the gold standard agent-based modeling environment for learners around the world. In my dissertation work, I marry biology and computer science to teach the emergent principles of ant colonies foraging for food and expanding. The work builds on more than a decade of experience in ABM. I now work at the Center for the Science and the Schools as an Assistant Professor. We delivered a curriculum to teach about COVID-19, where I incorporated ABMs into the curriculum.

You can keep up with my work at my webpage: https://kitcmartin.com

Archaeologist from Brazil, working with shellmound population dynamics in agent-based modelling.

**PROFESSIONS **

Associate Professor
School of Management Science and Engineering, Shandong Technology and Business University (Yantai 264005, P. R. China)

**EDUCATION BACKGROUDS **

Ph. D. Degree, 09/2009 – 07/2015
School of Economics and Management, Beihang University (P. R. China)

M. A. Degree, 09/2003 – 02/2006
The Institute of Systems Engineering, Dalian University of Technology (P. R. China)

B. A. Degree, 09/1999 – 07/2003
Department of Information and Control Engineering, Zhengzhou University of Light Industry (P. R. China)

**VISITING & SUMMER SCHOOLS **

Visiting Scholar at GECS – Research Group of Experimental and Computational Sociology (March, 2017 – February, 2018)
 Università degli Studi di Brescia (Italy)
 Co-supervisor: Professor Flaminio Squazzoni

Summer school in ‘Agent-based modeling for social scientists’ (September 4-8, 2017)
 University of Brescia, Italy
 Instructors: Flaminio Squazzoni, Simone Gabbriellini, Nicolas Payette, Federico Bianchi

The Santa Fe Institute’s Massive Open Online Course: Introduction to Agent-Based Modeling (Jun 5 – September 8, 2017)
 The Santa Fe Institute, Complexity Explore Web: abm.complexityexploer.org
 Instructors: Bill Rand

Summer school in ‘Complex systems and management’ (July 2-12, 2012)
 National Defense University, P. R. China
 Instructors: Xinjun Mao, Yongfang Liu, Dinghua Shi, Qiyue Cheng