This comprehensive and accessible series features some of today’s most pressing issues. This series will not only inform the public about the connection between math and sustainability but will also encourage progress toward solving some of planet Earth’s fundamental problems and foster communication between science and mathematics educators.
Deligne, of the Institute for Advanced Study in Princeton, New Jersey, has long been a leader in mathematics innovation and exploration. This year, the Norwegian Academy of Science and Letters recognized his pioneering contributions to algebraic geometry by awarding him the Abel Prize.
In this talk, Ila Fiete will argue that it is time to develop and apply information-theoretic principles specific to coding in the noisy brain.
In this talk, Ila Fiete will argue that it is time to develop and apply information-theoretic principles specific to coding in the noisy brain.
In this talk, Ila Fiete will argue that it is time to develop and apply information-theoretic principles specific to coding in the noisy brain.
The inaugural Annual Meeting was an opportunity for awardees to get to know each other and their work.
In this talk, Roger E. Summons outlines approaches to seeking evidence of life in Earth’s oldest sedimentary rocks and shows, by analogy, how the Mars Science Laboratory mission is designed to investigate Mars’ capacity for supporting a biosphere.
No one knows when life first colonized planet Earth, nor if or when Mars ever supported life. We see numerous, unequivocal lines of evidence for life on Earth from some 3.5 billion years ago to the present day. But the further back in time we look, the more clues about our earliest ancestors are clouded by doubts, uncertainties and controversies.
No one knows when life first colonized planet Earth, nor if or when Mars ever supported life. We see numerous, unequivocal lines of evidence for life on Earth from some 3.5 billion years ago to the present day. But the further back in time we look, the more clues about our earliest ancestors are clouded by doubts, uncertainties and controversies.
In this talk, Mike Shelley discusses problems in fluid-structure interaction ranging from the macroscopic, i.e. flapping of flags and bending of tree leaves, to the micro – collective behaviors of micro-organisms and the transport of subcellular structures.
Autism and epilepsy are often comorbid disorders with overlapping epidemiology, genetics, clinical features, neuroanatomic abnormalities and neurophysiological mechanisms. Defining the genetics and clinical features of individuals with comorbid autism and epilepsy is ongoing, and development of genotype-phenotype correlations has just begun. Understanding shared and distinct mechanisms underlying autism and epilepsy is likely to improve prognosis, therapy and prevention.
Autism and epilepsy are often comorbid disorders with overlapping epidemiology, genetics, clinical features, neuroanatomic abnormalities and neurophysiological mechanisms. Defining the genetics and clinical features of individuals with comorbid autism and epilepsy is ongoing, and development of genotype-phenotype correlations has just begun. Understanding shared and distinct mechanisms underlying autism and epilepsy is likely to improve prognosis, therapy and prevention.
On November 1, 2013, the Simons Foundation hosted the sixth annual New York Computer Science and Economics (NYCE) day.
Burgeoning evidence shows that in typical development, the ability to structure actions according to intentions emerges during infancy. And recent evidence reveals that infancy is a period of rapid change and development in this ability. Early social knowledge depends critically on infants’ active engagement with the physical and social world.
Burgeoning evidence shows that in typical development, the ability to structure actions according to intentions emerges during infancy. And recent evidence reveals that infancy is a period of rapid change and development in this ability. Early social knowledge depends critically on infants’ active engagement with the physical and social world.
The Large Hadron Collider (LHC) at the European Organization for Nuclear Research (CERN) near Geneva, Switzerland has performed spectacularly well in its first major running period: from December 2009 through February 2013. Data of unprecedented quality and quantity have been recorded for proton-proton collisions at energies of 7 and 8 trillion electron volts — the highest energies ever obtained.
In this talk, Joe Incandela will present an overview of the LHC physics program, including highlights from the discovery of a Higgs boson and a summary of more recent studies that incorporate more data. He will briefly discuss expectations for future results in years to come.
In this talk, Joe Incandela will present an overview of the LHC physics program, including highlights from the discovery of a Higgs boson and a summary of more recent studies that incorporate more data. He will briefly discuss expectations for future results in years to come.
This Biotech Symposium will focus on computational methods for detecting structural variants, which include large chromosomal insertions, deletions, inversions and translocations.
This Biotech Symposium will focus on computational methods for detecting structural variants, which include large chromosomal insertions, deletions, inversions and translocations.
This Biotech Symposium will focus on computational methods for detecting structural variants, which include large chromosomal insertions, deletions, inversions and translocations.
Thought experiments have played an important role in figuring out the laws of physics. For the unification of quantum mechanics and gravity, where the phenomena take place in extreme regimes, they are even more crucial. Hawking’s 1976 paper “Breakdown of Predictability in Gravitational Collapse” presented one of the great thought experiments in the history of physics, arguing that black holes destroy information in a way that requires a modification of the laws of quantum mechanics. Skeptics for years failed to poke holes in Hawking’s argument, but concluded that if quantum mechanics is to be saved then our understanding of spacetime must break down in a radical way.
L. Mahadevan will explain how a combination of biological and physical experiments, together with mathematical models and computations, begin to unravel the physical basis for morphogenesis. He will go on to explore how these pan-disciplinary problems enrich the origins of this topic, creating new questions in mathematics, physics and biology.
L. Mahadevan will explain how a combination of biological and physical experiments, together with mathematical models and computations, begin to unravel the physical basis for morphogenesis. He will go on to explore how these pan-disciplinary problems enrich the origins of this topic, creating new questions in mathematics, physics and biology.
L. Mahadevan will explain how a combination of biological and physical experiments, together with mathematical models and computations, begin to unravel the physical basis for morphogenesis. He will go on to explore how these pan-disciplinary problems enrich the origins of this topic, creating new questions in mathematics, physics and biology.
In biological systems, there are striking examples where complicated structures (i.e., the bacterial ribosome) can spontaneously assemble, driven by specific interactions between the components. But how can systems be designed to have this property? Recent technological advances have created the opportunity for making technologically relevant systems that self assemble, using strands of DNA or objects coated with DNA. We will use these systems as inspiration to formulate theoretical models to understand how self assembly works in these systems, through theory, numerical simulation and experiment — and start to speculate as to whether resulting principles might be useful for unravelling the rules of biological self-assembly.
January 26 – February 1, 2014 Organizers: Werner Mueller, University of Bonn Sug Woo Shin, Massachussets Institute of Technology Nicolas Templier, Princeton University The Simons Symposium on Families of Automorphic...
New evidence of exoplanets reveals a higher-than-expected occurrence of potentially habitable worlds in our galactic neighborhood. What does this evidence tell us about life on other planets? How can we search for signs of life on other planets?
New evidence of exoplanets reveals a higher-than-expected occurrence of potentially habitable worlds in our galactic neighborhood. What does this evidence tell us about life on other planets? How can we search for signs of life on other planets?
New evidence of exoplanets reveals a higher-than-expected occurrence of potentially habitable worlds in our galactic neighborhood. What does this evidence tell us about life on other planets? How can we search for signs of life on other planets?
Integral equation methods play an important role in the numerical simulation of electromagnetic scattering. They are easy to employ in complex geometry and impose the desired radiation conditions at infinity without the need for artificial numerical boundaries. Two of the obstacles faced by current forward simulation tools are “low-frequency breakdown” and the lack of easy to use high order quadrature rules for complicated surfaces. In this talk, I will review the relevant background material, discuss a new mathematical formalism for scattering from perfect conductors and briefly describe a new quadrature technique that yields easily implementable high order rules for singular and weakly singular integrals. The scheme, denoted QBX (quadrature by expansion) is compatible with fast hierarchical algorithms such as the fast multipole method.
Organizers: Boris Altshuler, Columbia University Vladimir Falko, Lancaster University Charles Marcus, Neils Bohr Institute The Simons Symposium on Quantum Physics Beyond Simple Systems was the second symposium organized on...
While autism clearly involves altered function of the central nervous system, the neuropathology of the disorder remains controversial. This is due in part,to the enormous complexity of the disorder, which likely has many causes and many biological trajectories. It is also due to the fact that few neuroimaging studies involve very young children or severely affected individuals. This lack of information is compounded by the fact that findings at the magnetic resonance imaging (MRI) level of analysis cannot be confirmed and extended to the cellular level due to a lack of postmortem brains.
While autism clearly involves altered function of the central nervous system, the neuropathology of the disorder remains controversial. This is due in part,to the enormous complexity of the disorder, which likely has many causes and many biological trajectories. It is also due to the fact that few neuroimaging studies involve very young children or severely affected individuals. This lack of information is compounded by the fact that findings at the magnetic resonance imaging (MRI) level of analysis cannot be confirmed and extended to the cellular level due to a lack of postmortem brains.
Circadian (~24 hour) clocks are endogenous mechanisms that time the recurring, daily activities observed in most organisms. These clocks are genetically regulated, and generate biochemical oscillations within individual cells composing most tissues. Recently our laboratory has searched for and identified genes that affect the homeostatic regulation of sleep in Drosophila. This research has uncovered specific neurons whose activity promotes sleep.
This Biotech Symposium will focus on perspectives on big data in biology from leading practitioners in the field.
This Biotech Symposium will focus on perspectives on big data in biology from leading practitioners in the field.
March 9 – 15, 2014 Organizers: Elchanan Mossel, UC Berkeley Ryan O'Donnell, Carnegie Mellon University Krzysztof Oleszkiewicz, University of Warsaw The Simons Symposium on Discrete Analysis: Beyond the Boolean Cube...
Learning Using Privileged Information (LUPI) is a new paradigm that uses an intelligent agent (a ‘nontrivial teacher’) to supplement standard training data in the context of supervised learning algorithms. Rather than using standard, brute-force methods to address the general problem of inference and the construction of intelligent machines, the LUPI learning model allows the teacher to add additional (privileged) information to the training examples.
Learning Using Privileged Information (LUPI) is a new paradigm that uses an intelligent agent (a ‘nontrivial teacher’) to supplement standard training data in the context of supervised learning algorithms. Rather than using standard, brute-force methods to address the general problem of inference and the construction of intelligent machines, the LUPI learning model allows the teacher to add additional (privileged) information to the training examples.
March 23 - 29, 2014 Organizers: Andrew Benson, Carnegie Observatories Juna Kollmeier, Carnegie Observatories The goal of this symposium was to bring together leading experts in the theory and observation...
Advances in molecular genetics have implicated a variety of genetic variations in autism, yet understanding of what these variations mean is still limited. Advances in classification of diseases have made autism among the most reliably diagnosed neurodevelopmental or neuropsychiatric disorders. But symptoms used to define autism are likely outcomes of earlier disruptions in normative social and communication development rather than causally linked to genetic perturbations.
Advances in molecular genetics have implicated a variety of genetic variations in autism, yet understanding of what these variations mean is still limited. Advances in classification of diseases have made autism among the most reliably diagnosed neurodevelopmental or neuropsychiatric disorders. But symptoms used to define autism are likely outcomes of earlier disruptions in normative social and communication development rather than causally linked to genetic perturbations.
Depression is a common, chronic, and debilitating disease. Although many patients benefit from antidepressant medications or other therapies, only about half show complete remission. Factors that precipitate depression, such as stress, are incompletely understood. We have used chronic social defeat stress as an animal model of depression. Prolonged exposure to an aggressor induces lasting changes in behavior such as social avoidance and anhedonia-like symptoms, which are reversed by chronic (but not acute) treatment with available antidepressants.
This day-long conference will highlight areas where theoretical ideas are having an impact on the life sciences, and will be of interest to established researchers, postdoctoral fellows and graduate students working in the life sciences and allied fields.
In this lecture, Gerald Joyce focuses on the perpetuation of genetic information as a defining characteristic of life. He draws a connection between digital computers (von Neumann machines), especially those with the capacity to self-reproduce, and molecular Darwinian systems that maintain heritable ‘bits’ of information, which are refined through evolution.
In this lecture, Gerald Joyce focuses on the perpetuation of genetic information as a defining characteristic of life. He draws a connection between digital computers (von Neumann machines), especially those with the capacity to self-reproduce, and molecular Darwinian systems that maintain heritable ‘bits’ of information, which are refined through evolution.
In this lecture, Gerald Joyce focuses on the perpetuation of genetic information as a defining characteristic of life. He draws a connection between digital computers (von Neumann machines), especially those with the capacity to self-reproduce, and molecular Darwinian systems that maintain heritable ‘bits’ of information, which are refined through evolution.
A central goal in neuroscience is determining the genetic basis of neurological disorders — from autism to brain tumors. Many of these pathological states result from defects in gene regulatory programs that are fundamental to all cell types but lead to dysfunction specifically within the nervous system. Gail Mandel investigates the basis of this phenomenon and has identified cell-cell interactions between neurons and glia involved in pathological states of brain development. Mandel has ameliorated the neuropathology of one autism spectrum disorder, Rett syndrome, by genetically replacing the defective MeCP2 gene with a good copy of the gene in astrocytes – glia cells in the brain. She is now exploring the underlying mechanisms crucial for neuronal signaling.
A central goal in neuroscience is determining the genetic basis of neurological disorders — from autism to brain tumors. Many of these pathological states result from defects in gene regulatory programs that are fundamental to all cell types but lead to dysfunction specifically within the nervous system. Gail Mandel investigates the basis of this phenomenon and has identified cell-cell interactions between neurons and glia involved in pathological states of brain development. Mandel has ameliorated the neuropathology of one autism spectrum disorder, Rett syndrome, by genetically replacing the defective MeCP2 gene with a good copy of the gene in astrocytes – glia cells in the brain. She is now exploring the underlying mechanisms crucial for neuronal signaling.
In recent decades, physicists and astronomers have discovered two beautiful standard models, one for the quantum world of extremely short distances and one for the universe as a whole. Both models have had spectacular success, but there are also strong arguments for new physics beyond these models.
In recent decades, physicists and astronomers have discovered two beautiful standard models, one for the quantum world of extremely short distances and one for the universe as a whole. Both models have had spectacular success, but there are also strong arguments for new physics beyond these models.
Dr. Schadt provides an overview of how his team organizes very large scale data across many different types, and then integrates these data using sophisticated mathematical algorithms to construct predictive network models of disease, and discusses the application of this type of modeling in the cancer arena.
Probabilistic topic models provide a suite of tools for analyzing large collections of electronic documents. A traditional topic model analyzes a collection of documents to discover its hidden themes. These themes can be used to organize, visualize, summarize and navigate the collection. Many collections are associated with corresponding reader behavior data, which is useful both for making predictions about readers (such as which articles they will like) and in understanding patterns in how they read.
Probabilistic topic models provide a suite of tools for analyzing large collections of electronic documents. A traditional topic model analyzes a collection of documents to discover its hidden themes. These themes can be used to organize, visualize, summarize and navigate the collection. Many collections are associated with corresponding reader behavior data, which is useful both for making predictions about readers (such as which articles they will like) and in understanding patterns in how they read.
