In my research I focus on understanding human behaviour in group(s) as a part of a complex (social) system. My research can be characterised by the overall question: ‘How does group or collective behaviour arise or change given its social and physical context?‘ More specifically, I have engaged with: ‘How is (individual) human behaviour affected by being in a crowd?’, ‘Why do some groups (cooperatively) use their resources sustainably, whereas others do not?‘, ‘What is the role of (often implicit simplistic) assumptions regarding human behaviour for science and/or management?’

To address these questions, I use computational simulations to integrate and reflect synthesised knowledge from literature, empirics and experts. Models, simulation and data analysis are my tools for gaining a deeper understanding of the mechanisms underlying such systems. More specifically, I work with agent-based modelling (ABM), simulation experiments and data analysis of large datasets. Apart from crowd modelling and social-ecological modelling, I also develop methodological tools to analyse social simulation data and combining ABM with other methods, such as behavioural experiments.

GIS enthusiast and ABM practitioner

Leonardo Grando is a Ph.D. Student at the University of Campinas (UNICAMP) in Brazil. I am interested in complex systems, agent-based simulation, artificial intelligence, the Internet of Things, programming, and machine learning tools. I have expertise in Netlogo, Python, R, Latex, SQL, and Linux tools.

My Ph.D. work project is an IoT devices (UAVs) swarm agent-based modeling simulation (ABMS) aiming the perpetual flight. The workflow is Netlogo to ABMS simulate, Python and R to data analysis, and I use Latex for my thesis writing.

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.

Furkan Gürsoy received the BS in Management Information Systems from Boğaziçi University, Turkey, and the MS in Data Science from İstanbul Şehir University, Turkey. He is currently a PhD Candidate at Boğaziçi University. He previously worked as an IS/IT Consultant and a Machine Learning Engineer with the industry for several years. He held a Visiting Researcher Position with IMT Atlantique, France, in 2020. His research interests include complex networks, machine learning, simulation, and broad data science.