Luis M. Rocha

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Luis M. Rocha
Luis M. Rocha, 2014.jpg
Born (1966-10-05) October 5, 1966 (age 57)
Luanda, Angola
Alma mater Instituto Superior Técnico, Portugal Lic. (B.A. plus M.S.), 1990
Binghamton University Ph.D., 1997
Awards
Scientific career
Fields
Institutions
Thesis Evidence Sets and Contextual Genetic Algorithms: Exploring Uncertainty, Context, and Embodiment in Cognitive and Biological Systems. SUNY Binghamton.  (1997)
Academic advisors
Website casci.binghamton.edu

Luis M. Rocha is the George J. Klir Professor of Systems Science at the Thomas J. Watson College of Engineering and Applied Science, Binghamton University (State University of New York). He has been director of the NSF-NRT Complex Networks and Systems graduate Program in Informatics at Indiana University, Bloomington, USA. He is also director of the Center for Social and Biomedical Complexity, between Binghamton University and Indiana University, Bloomington, a Fulbright Scholar, and Principal Investigator at the Instituto Gulbenkian de Ciencia, Portugal. His research is on complex systems and networks, [1] [2] [3] [4] computational and systems biology, [1] [5] [6] [7] [8] biomedical complexity and digital health, [9] [10] [11] [12] and computational intelligence (including Artificial Life and Embodied Cognition). [13] [14] [15] [16] [17] [18] [19] [20] [21]

Contents

Biography

He was born in Luanda, Angola, moving to Lisbon, Portugal in his teens and completing an Licentiate (B.A. plus M.S.) in Mechanical and Systems Engineering at the Instituto Superior Técnico. He received his Ph.D in Systems Science in 1997 from the Binghamton University. From 1998 to 2004 he was a staff scientist at the Los Alamos National Laboratory, where he founded and led a Complex Systems Modeling Team during 1998-2002, and was part of the Santa Fe Institute research community. He has been the director of the NSF-NRT Interdisciplinary Training Program in Complex Networks and Systems, and Professor of Informatics in the Luddy School of Informatics, Computing, and Engineering at Indiana University, where he was a member of the advisory council of the Indiana University Network Science Institute, and core faculty of the Cognitive Science Program. From 2005 to 2015 he was the director of the Computational Biology Collaboratorium and in the Direction of the PhD program in Computational Biology at the Instituto Gulbenkian de Ciencia, where he remains a Principal Investigator. He has organized the Tenth International Conference on the Simulation and Synthesis of Living Systems (Alife X) [22] and the Ninth European Conference on Artificial Life (ECAL 2007). [23]

Research

Dr. Rocha studies the systems properties of natural and artificial systems which enable them to adapt and evolve. He has approached this general topic by investigating how information and redundancy are fundamental for controlling the behavior and evolutionary capabilities of complex systems, [1] [15] [16] [17] as well as abstracting principles from natural systems to produce adaptive information technology. [18] [19] [21]

Accepting Von Neumann's principle of self-replication and Turing's universal computation as a general principle for generating open-ended complexity that encompasses Natural Selection, Dr. Rocha has developed the work of Howard Pattee, [24] Sydney Brenner, [25] and others who regard computation and information as fundamental to understanding life, cognition and other complex systems (a good overview is Gleick's Book). From this viewpoint, he has approached several questions: how do cells and collectives of cells compute? [1] Is language an evolutionary system operating under the same principle? [13] [16] [17] Can artificial systems implement the same principle? [13] [15] Namely, can collective intelligence on the web become a super-organism implementing this principle? [14] [18] [26] [27] From these questions, he has worked on various specific research projects ranging from Biomedical Literature Mining and Social Media Mining [9] [10] [6] [7] [8] to understanding redundancy, robustness, modularity and control in Complex Networks, [1] [2] [3] [4] Collective Intelligence on the Web and in Social Systems, [13] [14] [2] [18] [20] [26] [27] and Agent-based models of Evolutionary Systems such as RNA Editing [19] and Artificial Immune Systems. [21]

Philosophical views

Rocha is a proponent of embodied and situated cognition and has defended the grounded epistemological stance of evolutionary constructivism. He is a proponent of the view that the threshold of complexity required for open-ended evolution requires an interplay between symbolic memory and dynamical machinery, i.e. a strict genotype-phenotype separation. This idea has been labeled semiotic closure [28] and is generally understood to fit in the area of biosemiotics. He has defended that this principle of organization is at play in cognition and human collective behavior, having developed web technology to implement the principle. [13] [14] [2] [15] [18] In addition to scientific work often mentioned in the media, he regularly publishes opinion articles in the popular media to disseminate scientific thinking. [29]

Related Research Articles

Complexity characterises the behaviour of a system or model whose components interact in multiple ways and follow local rules, leading to non-linearity, randomness, collective dynamics, hierarchy, and emergence.

Artificial consciousness (AC), also known as machine consciousness (MC), synthetic consciousness or digital consciousness, is the consciousness hypothesized to be possible in artificial intelligence. It is also the corresponding field of study, which draws insights from philosophy of mind, philosophy of artificial intelligence, cognitive science and neuroscience. The same terminology can be used with the term "sentience" instead of "consciousness" when specifically designating phenomenal consciousness.

<span class="mw-page-title-main">Autopoiesis</span> Systems concept which entails automatic reproduction and maintenance

The term autopoiesis refers to a system capable of producing and maintaining itself by creating its own parts. The term was introduced in the 1972 publication Autopoiesis and Cognition: The Realization of the Living by Chilean biologists Humberto Maturana and Francisco Varela to define the self-maintaining chemistry of living cells.

Bio-inspired computing, short for biologically inspired computing, is a field of study which seeks to solve computer science problems using models of biology. It relates to connectionism, social behavior, and emergence. Within computer science, bio-inspired computing relates to artificial intelligence and machine learning. Bio-inspired computing is a major subset of natural computation.

Social simulation is a research field that applies computational methods to study issues in the social sciences. The issues explored include problems in computational law, psychology, organizational behavior, sociology, political science, economics, anthropology, geography, engineering, archaeology and linguistics.

Biosemiotics is a field of semiotics and biology that studies the prelinguistic meaning-making, biological interpretation processes, production of signs and codes and communication processes in the biological realm.

<span class="mw-page-title-main">Computational sociology</span> Branch of the discipline of sociology

Computational sociology is a branch of sociology that uses computationally intensive methods to analyze and model social phenomena. Using computer simulations, artificial intelligence, complex statistical methods, and analytic approaches like social network analysis, computational sociology develops and tests theories of complex social processes through bottom-up modeling of social interactions.

An agent-based model (ABM) is a computational model for simulating the actions and interactions of autonomous agents in order to understand the behavior of a system and what governs its outcomes. It combines elements of game theory, complex systems, emergence, computational sociology, multi-agent systems, and evolutionary programming. Monte Carlo methods are used to understand the stochasticity of these models. Particularly within ecology, ABMs are also called individual-based models (IBMs). A review of recent literature on individual-based models, agent-based models, and multiagent systems shows that ABMs are used in many scientific domains including biology, ecology and social science. Agent-based modeling is related to, but distinct from, the concept of multi-agent systems or multi-agent simulation in that the goal of ABM is to search for explanatory insight into the collective behavior of agents obeying simple rules, typically in natural systems, rather than in designing agents or solving specific practical or engineering problems.

<span class="mw-page-title-main">Generative science</span> Study of how complex behaviour can be generated by deterministic and finite rules and parameters

Generative science is an area of research that explores the natural world and its complex behaviours. It explores ways "to generate apparently unanticipated and infinite behaviour based on deterministic and finite rules and parameters reproducing or resembling the behavior of natural and social phenomena". By modelling such interactions, it can suggest that properties exist in the system that had not been noticed in the real world situation. An example field of study is how unintended consequences arise in social processes.

The expression computational intelligence (CI) usually refers to the ability of a computer to learn a specific task from data or experimental observation. Even though it is commonly considered a synonym of soft computing, there is still no commonly accepted definition of computational intelligence.

In artificial intelligence, artificial immune systems (AIS) are a class of computationally intelligent, rule-based machine learning systems inspired by the principles and processes of the vertebrate immune system. The algorithms are typically modeled after the immune system's characteristics of learning and memory for use in problem-solving.

A cognitive architecture refers to both a theory about the structure of the human mind and to a computational instantiation of such a theory used in the fields of artificial intelligence (AI) and computational cognitive science. The formalized models can be used to further refine a comprehensive theory of cognition and as a useful artificial intelligence program. Successful cognitive architectures include ACT-R and SOAR. The research on cognitive architectures as software instantiation of cognitive theories was initiated by Allen Newell in 1990.

<span class="mw-page-title-main">John Henry Holland</span> American researcher in genetic algorithms (1929–2015)

John Henry Holland was an American scientist and professor of psychology and electrical engineering and computer science at the University of Michigan, Ann Arbor. He was a pioneer in what became known as genetic algorithms.

<span class="mw-page-title-main">Francis Heylighen</span> Belgian cyberneticist (born 1960)

Francis Paul Heylighen is a Belgian cyberneticist investigating the emergence and evolution of intelligent organization. He presently works as a research professor at the Vrije Universiteit Brussel, where he directs the transdisciplinary "Center Leo Apostel" and the research group on "Evolution, Complexity and Cognition". He is best known for his work on the Principia Cybernetica Project, his model of the Internet as a global brain, and his contributions to the theories of memetics and self-organization. He is also known, albeit to a lesser extent, for his work on gifted people and their problems.

The Calouste Gulbenkian Foundation, commonly referred to simply as the Gulbenkian Foundation, is a Portuguese institution dedicated to the promotion of the arts, philanthropy, science, and education. One of the wealthiest charitable foundations in the world, the Gulbenkian Foundation was founded on 18 July 1956 according to the last will and testament of Calouste Sarkis Gulbenkian, a Portugal-based oil magnate who bequeathed his assets to the country in the form of a foundation.

<span class="mw-page-title-main">Instituto Gulbenkian de Ciência</span>

The Instituto Gulbenkian de Ciência (IGC) is an international centre for biological and biomedical research and graduate training based in Oeiras, Portugal. Founded by the Calouste Gulbenkian Foundation (FCG) in 1961, and still supported by the Foundation, the IGC is organised in small independent research groups that work in an environment designed to encourage interactions with minimal hierarchical structure.

Computer simulation is a prominent method in organizational studies and strategic management. While there are many uses for computer simulation, most academics in the fields of strategic management and organizational studies have used computer simulation to understand how organizations or firms operate. More recently, however, researchers have also started to apply computer simulation to understand organizational behaviour at a more micro-level, focusing on individual and interpersonal cognition and behavior such as team working.

<span class="mw-page-title-main">Lawrence Hunter</span>

Lawrence E. Hunter is a Professor and Director of the Center for Computational Pharmacology and of the Computational Bioscience Program at the University of Colorado School of Medicine and Professor of Computer Science at the University of Colorado Boulder. He is an internationally known scholar, focused on computational biology, knowledge-driven extraction of information from the primary biomedical literature, the semantic integration of knowledge resources in molecular biology, and the use of knowledge in the analysis of high-throughput data, as well as for his foundational work in computational biology, which led to the genesis of the major professional organization in the field and two international conferences.

The internal measurement refers to the quantum measurement realized by the endo-observer. Quantum measurement represents the action of a measuring device on the measured system. When the measuring device is a part of measured system, the measurement proceeds internally in relation to the whole system. This theory was introduced by Koichiro Matsuno and developed by Yukio-Pegio Gunji. They further expanded the original ideas of Robert Rosen and Howard Pattee on the quantum measurement in living systems viewed as natural internal observers that belong to the same scale of the observed objects. According to Matsuno, the internal measurement is accompanied by the redistribution of probabilities that leave them entangled in accordance with the many-worlds interpretation of quantum mechanics by Everett. However, this form of quantum entanglement does not survive in the external measurement in which the mapping to real numbers takes place and the result is revealed in the classical time-space as the Copenhagen interpretation suggests. This means that the internal measurement concept unifies the alternative interpretations of quantum mechanics.

<span class="mw-page-title-main">Howard H. Pattee</span> American biologist (born 1926)

Howard Hunt Pattee is an American biologist, Professor Emeritus at Binghamton University and Fellow of the American Association for the Advancement of Science. He graduated at Stanford University in 1948 and completed a Ph.D. there in 1953.

References

  1. 1 2 3 4 5 A.J. Gates, R.B. Correia, X. Wang, L.M. Rocha. "The effective graph reveals redundancy, canalization, and control pathways in biochemical regulation and signaling" PNAS, 118(12): e2022598118. doi:10.1371/journal.pone.0055946. 2013
  2. 1 2 3 4 T. Simas, R.B. Correia, and L.M. Rocha. "The distance backbone of complex networks." Journal of Complex Networks, 9 (6): cnab021, DOI:10.1093/comnet/cnab021, 2021
  3. 1 2 A. Kolchinsky, M. P. Van Den Heuvel, A. Griffa, P. Hagmann, L.M. Rocha, O. Sporns, J. Goni. "Multi-scale Integration and Predictability in Resting State Brain Activity". Frontiers in Neuroinformatics, 8:66. doi: 10.3389/fninf.2014.00066, 2014
  4. 1 2 Gates, A. and L.M. Rocha. "Control of complex networks requires both structure and dynamics". Scientific Reports., 6:24456. doi: 10.1038/srep244564, 2016
  5. ↑ M.E. Wall, A. Rechtesteiner, and L. M. Rocha, Singular Value Decomposition and Principal Component Analysis "A Practical Approach to Microarray Data Analysis". D. P. Berrar, W. Dubitzky, and M. Granzow (Eds.). Kluwer Academic Publishers, pp. 91-109. 2003
  6. 1 2 A. Kolchinsky, A. Lourenço, H. Wu, L. Li, L.M. Rocha. "Extraction of Pharmacokinetic Evidence of Drug-drug Interactions from the literature" PLoS ONE 10(5): e0122199. doi:10.1371/journal.pone.0122199. 2015.
  7. 1 2 A. Lourenco, M. Conover, A. Wong, A. Nematzadeh, F. Pan, H. Shatkay, and L.M. Rocha, A Linear Classifier Based on Entity Recognition Tools and a Statistical Approach to Method Extraction in the Protein-Protein Interaction Literature. "BMC Bioinformatics.12(Suppl 8):S12." 2011
  8. 1 2 A. Abi-Haidar, J. Kaur, A. Maguitman, P. Radivojac, A. Retchsteiner, K. Verspoor, Z. Wang, and L.M. Rocha, Uncovering protein interaction in abstracts and text using a novel linear model and word proximity networks. "Genome Biology. 9(Suppl 2):S11" 2008
  9. 1 2 R.B. Correia, L. Li, L.M. Rocha "Monitoring potential drug interactions and reactions via network analysis of Instagram user timelines". Pacific Symposium on Biocomputing., 21:492-503. DOI: 10.1073/pnas.2022598118, 2021
  10. 1 2 I.B Wood, P.L. Varela, J. Bollen, L.M. Rocha, J. Gonçalves-Sá "Human Sexual Cycles are Driven by Culture and Match Collective Moods". Scientific Reports., 7:17973. doi: 10.1038/s41598-017-18262-5, 2017
  11. ↑ R.B. Correia, I.B Wood, J. Bollen, L.M. Rocha "Mining social media data for biomedical signals and health-related behavior". Annual Review of Biomedical Data Science., 3(1): 433-458. DOI: 10.1146/annurev-biodatasci-030320-040844, 2020.
  12. ↑ R.B. Correia, L.P. de Araújo, M.M. Mattos, L.M. Rocha "City-wide Analysis of Electronic Health Records Reveals Gender and Age Biases in the Administration of Known Drug-Drug Interactions". npj Digital Medicine., 2: 74. DOI: 10.1038/s41746-019-0141-x, 2029.
  13. 1 2 3 4 5 Clark, A. Natural-Born Cyborgs:Minds, Technologies, and the Future of Human Intelligence. Oxford University Press, 2003.
  14. 1 2 3 4 Stark, D. The Sense of Dissonance: Accounts of Worth in Economic Life. Princeton University Press, 2011.
  15. 1 2 3 4 L.M. Rocha. and W. Hordijk, Material Representations: From the Genetic Code to the Evolution of Cellular Automata. "Artificial Life. 11 (1-2), pp. 189 - 214" 2005
  16. 1 2 3 L.M. Rocha, Evolution with material symbol systems. "Biosystems. Vol. 60, pp. 95-121." 2001
  17. 1 2 3 L.M. Rocha, Selected Self-Organization and the Semiotics of Evolutionary Systems. "In: Evolutionary Systems: Biological and Epistemological Perspectives on Selection and Self-Organization." S. Salthe, G. Van de Vijver, and M. Delpos (eds.). Kluwer Academic Publishers, pp. 341-358. 1998
  18. 1 2 3 4 5 L.M. Rocha, Adaptive Recommendation and Open-Ended Semiosis. "Kybernetes. Vol. 30, No. 5-6." 2001
  19. 1 2 3 C. Huang, J. Kaur, A. Maguitman, L.M. Rocha, Agent-Based Model of Genotype Editing. "Evolutionary Computation, 15(3): 253-89." 2007
  20. 1 2 L.M. Rocha, Evidence Sets: Modeling Subjective Categories. "In: International Journal of General Systems. Vol. 27, pp. 457-494." 1997
  21. 1 2 3 A. Abi-Haidar and L.M. Rocha. "Collective Classification of Textual Documents by Guided Self-Organization in T-Cell Cross-Regulation Dynamics". Evolutionary Intelligence. 4(2):69-80, 2011
  22. ↑ L.M. Rocha (Editor), L. S. Yaeger (Editor), M. A. Bedau (Editor), D. Floreano (Editor), R. L. Goldstone (Editor), A. Vespignani (Editor), "Artificial Life X: Proceedings of the Tenth International Conference on the Simulation and Synthesis of Living Systems (Bradford Books).". 2006
  23. ↑ F. Almeida e Costa, "Advances in Artificial Life: 9th European Conference, ECAL 2007, Lisbon, Portugal, September 10–14, 2007, Proceedings (Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence).". 2007
  24. ↑ Rocha, Luis M. (Ed.) The Physics and Evolution of Symbols and Codes: Reflections on the Work of Howard Pattee . BioSystems60 (1-3), 2001.
  25. ↑ Brenner, Sydney. "Turing centenary: Life’s code script." Nature 482 (7386) (February 22): 461-461, 2012.
  26. 1 2 Rocha, Luis M. and Johan Bollen. "Biologically Motivated Distributed Designs for Adaptive Knowledge Management". In: Design Principles for the Immune System and other Distributed Autonomous Systems. L. Segel and I. Cohen (Eds.) Santa Fe Institute Series in the Sciences of Complexity. Oxford University Press, pp. 305-334, 2001
  27. 1 2 G.L. Ciampaglia, P. Shiralkar, L.M. Rocha, J. Bollen, F. Menczer, A. Flammini.Computational fact checking from knowledge networks. PLoS One. 10(6): e0128193. doi:10.1371/journal.pone.0128193, 2015.
  28. ↑ Pattee, H.H. "The Physics and Metaphysics of Biosemiotics." Journal of Biosemiotics. 1:281-301, 2005.
  29. ↑ Luis M. Rocha in the News and Media
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