We are thrilled to welcome the following list of outstanding scientific leaders as our GECCO 2026 keynote speakers.
Speaker Bio
Antonio Lazcano Araujo is Professor at the National Autonomous University of Mexico (UNAM), where is engaged in research and teaching on the origin and early evolution of life. He has worked on prebiotic chemistry, analysis of carbon-rich meteorite, and the early evolution of microorganisms. He is the author or co-author of nearly 200 research articles and book chapters on the origin and evolution of cells, and of several popular science books, including El origen de la vida, La chispa de la vida, La bacteria prodigiosa, Tres ensayos darwinistas and, and El retablo de las maravillas. He has been a visiting professor at the universities of Havana, the Autonomous University of Madrid, Houston, Valencia, Orsay Paris-Sud, and California, San Diego, as well as the University of Rome and the Sorbonne. He has also been a visiting researcher at the Pasteur Institute in Paris, the ETH Zurich, and the A. N. Bakh Institute of Biochemistry in Moscow, among others. From 2002 to 2004, he chaired the Evaluation Committee of the NASA Astrobiology Institute and coordinated the Gordon Conference on the Origins of Life. For eight years, he was a member of the NASA Advisory Committee for the Study of the Origin and Evolution of Life (NASA-COEL) and twice served as President of the International Society for the Study of the Origins of Life, a position to date being the only Latin American scientist to hold this office. He holds three honorary doctorates: one from the University of Milan (Italy) in 2008, another from the University of Valencia (Spain) in 2014, and a third from the Michoacán University of San Nicolás de Hidalgo in 2015. In 2013, the Third Summit on Evolution awarded him the Charles Darwin Distinguished Scientist Award, and in 2018, the Collège de France awarded him the Guillaume Bude Medal. In October 2014 he joined El Colegio Nacional, the most important cultural institution in Mexico, and in 2023 he was elected as an honorary member of the National Academy of Medicine.
Tecumseh Fitch
Department of Behavioral and Cognitive Biology at the Faculty of Life Sciences, University of Vienna. Webpage
Dendrophilia and the Evolution of Human Cognition
Abstract
Understanding of the neural mechanisms involved in human cognition, and their evolutionary history, requires comparisons between humans and nonhuman animals. Ideally, such comparisons are grounded in an explicit, computational framework encompassing both formal and neural components. I review work comparing cognitive computation in humans with nonhuman primates, other mammals, and birds carried out in the last decades to explore the neural basis and evolutionary origins of human cognition. This comparative research suggests the dendrophilia hypothesis, which proposes that humans are unusual in our ability to process complex hierarchical structures across multiple cognitive domains (language, music, etc.). These hierarchical abilities require computational power at the supra-regular level (above finite state), which support processing of the abstract tree structures needed for language, music and other complex cognition. However, dendrophilia makes heavy use of the finite-state serial processing abilities shared with many other species. I propose that human general hierarchical abilities are supported anatomically by the great enlargement of Broca’s area in our species, along with the broadening of its connections to large portions of the parietal and temporal lobes. Computationally, Broca’s region in humans may act as a domain-general “stack”, or auxiliary memory, supporting supra-regular computation in both language and music.
Speaker Bio
Tecumseh Fitch is a cognitive biologist, and a professor and founder of the Department of Behavioral and Cognitive Biology at the Faculty of Life Sciences, University of Vienna. Fitch studies the biology and evolution of cognition and communication in vertebrates. He has a particular interest in the evolution of language, music and speech in humans, studied from a broad comparative perspective. Current research foci include bioacoustics, vocal learning, the biology and evolution of rhythm, empirical aesthetics and comparisons of syntactic abilities in different bird and mammal species. He holds a Bachelors in Biology and a PhD in Cognitive Science, both from Brown University. After a post-doc at MIT and Harvard, he lectured at Harvard and the University of St. Andrews before moving to Vienna in 2009. He is a recipient of an ERC Advanced Grant and is an elected Fellow of the Association for Psychological Science and the US National Academy of Science.
Wolfgang Banzhaf
Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA. Webpage
Neutrality, Simplicity and Search: Lessons from Genetic Programming
Abstract
The role of neutrality, a phenomenon where many genotypes map to one phenotype, has long been considered in evolutionary computation a (sometimes annoying) side effect rather than a principle. In this keynote we want to argue that it is, in fact, a central force in search over redundant genotype-phenotype maps. Its main consequence is a bias toward simple solutions. Using linear genetic programming on Boolean functions, where complexity can be measured directly, we show that simpler phenotypes occupy exponentially larger neutral sets, and that search is therefore drawn toward them. It turns out that this bias is a property of the map itself, not of evolution as such. Notably, it appears in other evolutionary systems with redundant genotype-phenotype maps, such as RNA, and even in non-evolutionary settings like deep neural networks and other redundant, complexity-bounded representations. It is absent, however, in the one-to-one representations often used in optimization. We then suggest that hierarchical systems built from modules may be understood as realizing neutrality at a higher level, because composing phenotypes from reusable modules enlarges their neutral sets combinatorially. This connects the classical 1960s argument of Herbert Simon about the architecture of complexity with more recent observations about depth in modern machine learning. From this follow lessons for the design of fitness functions and representations, as well as a broader question, namely whether genetic programming can serve as a model system for understanding simplicity bias in machine learning at large.
Speaker Bio
Wolfgang Banzhaf is the John R. Koza Chair for Genetic Programming, the first endowed chair dedicated to Evolutionary Computation in the United States, and a professor in the Department of Computer Science and Engineering at Michigan State University, East Lansing, USA. His research interests are in the field of bio-inspired computing, notably evolutionary computation and complex adaptive system, and in particular genetic programming and artificial life. Formerly a professor at the Technical University of Dortmund, Germany (1993-2003), Memorial University of Newfoundland in Canada (2003-2016) and now Michigan State University, he is the (co-)author of more than 300 scientific contributions and 7 patents. His books and edited volumes include “Genetic Programming – An Introduction” (1998), “Linear Genetic Programming” (2007), “Artificial Chemistries” (2015) and most recently “Advances in Linear Genetic Programming” (to appear mid 2026). He served as treasurer and later chair of ACM SIGEVO, founding editor-in-chief of the SpringerNature journal ‘Genetic Programming and Evolvable Machines’ and was the first editor-in-chief of the annual GECCO conference proceedings. He won the Intl. Society for Genetic and Evolutionary Computation (now ACM SIGEVO) Senior Fellow Award in 2003, the EvoStar Award for major contributions to Evolutionary Computation in Europe in 2007 and the Intl. Society for Artificial Life (ISAL) Lifetime Achievement Award in 2022.