Dr. Rob Roggema was a landscape-driven design and sustainable urban environments professor at three universities in the Netherlands and the University of Technology Sydney in Australia. He is a visiting professor in Landscape Urbanism at Queen’s University Belfast in Northern Ireland and was a Distinguished Visiting Professor at Western Sydney University in Australia, and a Distinguished Global Professor at KEIO University in Japan.

He is the founder of Cittaideale, an office for adaptive design, spatial planning, and design research for regenerative urban environments and landscapes. Some of the design concepts he has developed are FoodRoofRio, a rooftop garden with an aquaponic system that provided food for families in the Cantagalo favela in Rio de Janeiro, Brazil; Moeder Zernike, a regional long-term regenerative plan for the northern part of the Netherlands; and Nature Rich Netherlands,
a national plan to convert Dutch land use to 50% nature while solving problems related to climate change impacts, nitrogen deposition, and housing.

For his Ph.D., he developed the Swarm Planning concept, a new method for planning and responding to climate adaptation and spatial design. Rob Roggema’s research interests are in creating innovative spatial solutions for regenerative urban landscapes. He has facilitated over 40 design charrettes in the Netherlands, Japan, Mongolia, China, Jordan, India, Australia, and New Zealand, engaging communities, academics, governments, and industries in complex design processes to address wicked problems.

Rob Roggema joined Tecnológico de Monterrey as a Distinguished Professor in Regenerative Cultures for the School of Architecture, Art and Design.

• Ph.D., Swarm Planning: The development of a methodology to deal with climate adaptation, Delft University of Technology and Wageningen University & Research
• M.Sc., Landscape Architecture, Wageningen University & Research
   

• Roggema, R.; Chamski, R. The New Urban Profession: Entering the Age of Uncertainty. Urban Sci. 2022, 6, 10. https://doi.org/10.3390/urbansci6010010

• Roggema, R. (2022). Design for Regenerative Cities and Landscapes: Rebalancing Human Impact and Natural Environment (Contemporary Urban Design Thinking) (English Edition). Springer.

• Roggema, Rob. (2021). TransFEWmation: Towards Design-led Food-Energy-Water Systems for Future Urbanization. 10.1007/978-3-030-61977-0. 

• Roggema, Rob. (2020). Nature Driven Urbanism. 10.1007/978-3-030-26717-9. 

• Roggema, Rob. (2020). Designing Sustainable Cities. 10.1007/978-3-030-54686-1. 

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Dr. Carlos Coello is a professor with distinction (Investigador CINVESTAV 3F) at the Center for Research and Advanced Studies of the Instituto Politécnico Nacional (CINVESTAV-IPN) in Mexico City and visiting professor at the Basque Center for Applied Mathematics in Spain. Has taught master’s and Ph.D. level courses on evolutionary computation, evolutionary multiobjective optimization, programming languages, and engineering optimization at CINVESTAV-IPN. In addition, he has taught short courses in Spain, England, India, U.S., among others.

His research interests are evolutionary computation (genetic algorithms and evolution strategies), as well as engineering optimization. His main contributions have been the design of biologically inspired stochastic algorithms to solve highly complex multi-objective optimization problems (mainly non-linear). He has made pioneering contributions to this area, which is now known as evolutionary multi-objective optimization. For example, he proposed, along with his research group, the first genetic micro-algorithm for multi-objective optimization, which has been used in real-world applications in several countries, like the United States, for the design of supersonic business jets. He is member of the Foundation Advisory Board of the International AIQT Foundation, which strives to establish a highly competitive (international-level) research center in artificial intelligence and quantum technology.

Among his multiple special recognitions and awards, Dr. Carlos Coello was awarded by the International Society on Multi-Criteria Decision Making (MCDM) the 2024 MCDM Edgeworth-Pareto Award. In 2023, he won the Premio Crónica in Science and Technology and was selected by Líderes magazine as part of their "300 most influential leaders in Mexico" list, taking the 69th position. He also won the SIGEVO Outstanding Contribution Award (2023) given by the Association for Computing Machinery (ACM), the IEEE Computational Intelligence Society Evolutionary Computation Pioneer Award (2021), among many others.

Dr. Coello is level 3 in the National System of Researchers (SNII) in Mexico and was also ranked #289 in the world and #1 in Mexico in the 8th Edition of the Guide2Research 2022 Ranking of Top 1000 Scientists in the field of Computer Science and Electronics.

Professor Carlos Coello joined Tecnológico de Monterrey as Distinguished Visiting Professor in Computer Science and Computational Intelligence for the School of Engineering and Sciences.

• Ph.D., Computer Science, Tulane University, New Orleans
• M.Sc., Computer Science, Tulane University, New Orleans
• B.Sc., Civil Engineering, Universidad Autónoma de Chiapas (Summa cum laude)
   

• Sofien Boutaib, Maha Elarbi, Slim Bechikh, Carlos A. Coello Coello, Lamjed Ben Said, Uncertainty-wise Software Anti-patterns Detection: A Possibilistic Evolutionary Machine Learning Approach, Applied Soft Computing, Vol. 129, Article Number: 109620, November 2022.

• Forhad Zaman, Saber Elsayed, Ruhul Sarker, Daryl Essam and Carlos A. Coello Coello, Pro-Reactive Approach for Project Scheduling Under Unpredictable Disruptions, IEEE Transactions on Cybernetics, Vol. 52, No. 11, pp. 11299--11312, November 2022.

• Lingjie Li, Yongfeng Li, Qiuzhen Lin, Zhong Ming, Carlos A. Coello Coello, A Convergence and Diversity Guided Leader Selection Strategy for Many-objective Particle Swarm Optimization<, Engineering Applications of Artificial Intelligence, Vol. 155, Article Number: 105249, October 2022.

• Qiuzhen Lin, Xunfeng Wu, Jianqiang Li, Maoguo Gong and Carlos A. Coello Coello, An Ensemble Surrogate-based Framework for Expensive Multiobjective Evolutionary Optimization, IEEE Transactions on Evolutionary Computation, Vol. 26, No. 4, pp. 631--645, August 2022.

• Qiyuan Yu, Qiuzhen Lin, Zexuan Zhu, Ka-Chun Wong, Carlos A. Coello Coello, A dynamic multi-objective evolutionary algorithm based on polynomial regression and adaptive clustering, Swarm and Evolutionary Computation, Vol. 71, Article No. 101075, June 2022.

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Dr. Carlos Coello is a professor with distinction (Investigador CINVESTAV 3F) at the Center for Research and Advanced Studies of the Instituto Politécnico Nacional (CINVESTAV-IPN) in Mexico City and visiting professor at the Basque Center for Applied Mathematics in Spain. Has taught master’s and Ph.D. level courses on evolutionary computation, evolutionary multiobjective optimization, programming languages, and engineering optimization at CINVESTAV-IPN. In addition, he has taught short courses in Spain, England, India, U.S., among others.

His research interests are evolutionary computation (genetic algorithms and evolution strategies), as well as engineering optimization. His main contributions have been the design of biologically inspired stochastic algorithms to solve highly complex multi-objective optimization problems (mainly non-linear). He has made pioneering contributions to this area, which is now known as evolutionary multi-objective optimization. For example, he proposed, along with his research group, the first genetic micro-algorithm for multi-objective optimization, which has been used in real-world applications in several countries, like the United States, for the design of supersonic business jets. He is member of the Foundation Advisory Board of the International AIQT Foundation, which strives to establish a highly competitive (international-level) research center in artificial intelligence and quantum technology.

Among his multiple special recognitions and awards, Dr. Carlos Coello was awarded by the International Society on Multi-Criteria Decision Making (MCDM) the 2024 MCDM Edgeworth-Pareto Award. In 2023, he won the Premio Crónica in Science and Technology and was selected by Líderes magazine as part of their "300 most influential leaders in Mexico" list, taking the 69th position. He also won the SIGEVO Outstanding Contribution Award (2023) given by the Association for Computing Machinery (ACM), the IEEE Computational Intelligence Society Evolutionary Computation Pioneer Award (2021), among many others.

Dr. Coello is level 3 in the National System of Researchers (SNII) in Mexico and was also ranked #289 in the world and #1 in Mexico in the 8th Edition of the Guide2Research 2022 Ranking of Top 1000 Scientists in the field of Computer Science and Electronics.

Professor Carlos Coello joined Tecnológico de Monterrey as Distinguished Visiting Professor in Computer Science and Computational Intelligence for the School of Engineering and Sciences.

• Ph.D., Computer Science, Tulane University, New Orleans
• M.Sc., Computer Science, Tulane University, New Orleans
• B.Sc., Civil Engineering, Universidad Autónoma de Chiapas (Summa cum laude)
   

• Sofien Boutaib, Maha Elarbi, Slim Bechikh, Carlos A. Coello Coello, Lamjed Ben Said, Uncertainty-wise Software Anti-patterns Detection: A Possibilistic Evolutionary Machine Learning Approach, Applied Soft Computing, Vol. 129, Article Number: 109620, November 2022.

• Forhad Zaman, Saber Elsayed, Ruhul Sarker, Daryl Essam and Carlos A. Coello Coello, Pro-Reactive Approach for Project Scheduling Under Unpredictable Disruptions, IEEE Transactions on Cybernetics, Vol. 52, No. 11, pp. 11299--11312, November 2022.

• Lingjie Li, Yongfeng Li, Qiuzhen Lin, Zhong Ming, Carlos A. Coello Coello, A Convergence and Diversity Guided Leader Selection Strategy for Many-objective Particle Swarm Optimization<, Engineering Applications of Artificial Intelligence, Vol. 155, Article Number: 105249, October 2022.

• Qiuzhen Lin, Xunfeng Wu, Jianqiang Li, Maoguo Gong and Carlos A. Coello Coello, An Ensemble Surrogate-based Framework for Expensive Multiobjective Evolutionary Optimization, IEEE Transactions on Evolutionary Computation, Vol. 26, No. 4, pp. 631--645, August 2022.

• Qiyuan Yu, Qiuzhen Lin, Zexuan Zhu, Ka-Chun Wong, Carlos A. Coello Coello, A dynamic multi-objective evolutionary algorithm based on polynomial regression and adaptive clustering, Swarm and Evolutionary Computation, Vol. 71, Article No. 101075, June 2022.

More publications