My research is focused on understanding the importance of spatial and temporal environmental variability on communities and populations. The key question I aim to address is how the anthropogenic impacts, such as disturbances of individual animals or changed landscape heterogeneity associated with climate changes, influence the persistence of species. The harbour porpoise is an example of a species that is influenced by anthropogenic disturbances, and much of my research has focused on how the Danish porpoise populations are influenced by noise from offshore constructions. I use a wide range of modelling tools to assess the relative importance of different sources of environmental variation, including individual-based/agent based models, spatial statistics, and classical population models. This involves development of computer programs in R and NetLogo. In addition to my own research I currently supervise three PhD students and participate in the management of Department of Bioscience at Aarhus University.

Leonardo Grando is a Ph.D. 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.

I am an Associate Professor of Industrial Engineering with over two decades of experience in teaching, research, and supervision in data-driven decision making, operations research, and computational modeling. My research integrates Multi-Criteria Decision Analysis (MCDA), Agent-Based Modeling (ABM), and Reinforcement Learning (RL) to support strategic decision systems in sustainability, investment, and industrial operations. My recent work explores human-centric and multi-actor systems, leveraging simulation-based optimization and AI-driven analytics to enhance resilience, efficiency, and sustainability in complex socio-technical environments. I have published extensively in international journals, reviewed over 75 manuscripts, and am an active member of INFORMS and the System Dynamics Society. My long-term goal is to bridge industrial systems modeling with intelligent decision support, aligning academic research with real-world sustainability and innovation challenges.

🔹 Experience
Associate Professor — Industrial Engineering, University of Engineering and Technology, Taxila (2018 – Present)• Teach graduate and undergraduate courses in Operations Research, Data Mining, Advanced Statistics, System Simulation, and Soft Computing.• Conduct funded research in agent-based and reinforcement learning models for sustainable and data-driven decision systems.• Supervise doctoral students in decision analytics, multi-agent modeling, and MCDM applications.• Reviewer for international journals including Neural Computing and Applications, the Journal of Cleaner Production, Annals of Operations Research, Environment, Development and Sustainability, Energy for Sustainable Development, Scientific Reports, IEEE Access, Cleaner Energy Systems, Utilities Policy, and Sustainable Futures

🔹 Research Interests•
Data-Driven Decision Making• Agent-Based Modeling (ABM)• Reinforcement Learning (RL)• Multi-Criteria Decision Analysis (MCDA / MAMCA)• Sustainable Supply Chains• System Dynamics; Simulation• E-Health and Humanitarian Systems

🔹 Selected Achievements•
30+ peer-reviewed publications; ~360+ citations• Reviewer for 75+ international journal papers• Completed Coursera Specializations in Machine Learning, Deep Learning, and Reinforcement Learning• 20+ years of experience integrating data science with sustainability modeling

**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

Electrical and Computer Engineer (NTU, Athens), M.Sc. and Ph.D. on Artificial Intelligence (Univ. Paris VI, France). Formerly senior researcher in the Institute of Communication and Computer Systems (NTU, Athens). I have taught a variety of courses on intelligent, complex and biological systems and cognitive science. I have participated in numerous national and european R&D projects and I have authored about a hundred articles in journals, books and conference proceedings, at least half of them as a single author. I am frequent reviewer for journals, conferences and research grants. My research interests lie on the intersection of biological, complex and cognitive systems and applications.