| Date: February 2 |
| Speaker: Iven Mareels, Biomedical , University of Melbourne |
| Title: Systems Engineering for Water Management |
Abstract: It is estimated that we harvest and utilize about 65% of the readily available fresh water resources of the world. In general, perhaps because water is perceived as an abundantly available resource, we use water rather poorly. Typically less than half the water taken from the environment serves the objective for which it was intended. The UNESCO World Water reports 2003 and 2005 identify in no uncertain terms a water crisis.
In this lecture we provide an overview of a 10 year collaborative research and development effort, between the University of Melbourne and a local company Rubicon Systems Australia, and more recently with National ICT Australia.
The programme called Water Information Networks (WIN) is a systems engineering approach to water management in irrigation systems. Because irrigation accounts for 70% of the total water consumption, this is a logical place to start. The ultimate goal is to manage water at the level of an entire water catchment basin, accounting for surface and ground water and providing for the needs of all users, including the environment. WIN has developed a sensor/actuator network and a systems engineering approach to water management. The patented technology (commercialized as Total Channel Control™) is now being deployed in Australia’s largest irrigation district Goulburn Murray Water (GMW), consisting of 6800km of open irrigation canals servicing over 22,000 farms.
The objective for the open canal system is to deliver water on demand (in as much this may be feasible) with maximal overall efficiency meeting the competing demands.
We review the research work, including open questions, and discuss the WIN outcomes from a number of substantial pilot and commercial projects in Australia that have realized significant gains in either water efficiency or water productivity in irrigation. |
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| Date: February 9 |
| Speaker: Jennifer Rexford, Computer Science, Princeton University |
| Title: Stable Internet Routing Without Global Coordination |
| Abstract: Global Internet connectivity results from a competitive cooperation of tens of thousands of independently-administered networks (called Autonomous Systems), each with their own preferences for how traffic should flow. The responsibility for reconciling these preferences falls to interdomain routing, realized today by the Border Gateway Protocol (BGP). However, BGP allows ASes to express conflicting local policies that can lead to global routing instability. This talk proposes a set of guidelines for an AS to follow in setting its routing policies, without requiring coordination with other ASes. Our approach exploits the Internet's hierarchical structure and the commercial relationships between ASes to impose a partial order on the set of routes to each destination. The guidelines conform to conventional traffic-engineering practices of ISPs, and provide each AS with significant flexibility in selecting its local policies. Furthermore, the guidelines ensure route convergence even under changes in the topology and routing policies. Drawing on a formal model of BGP, we prove that following our proposed policy guidelines guarantees route convergence. We also describe how our methodology can be applied to new types of relationships between ASes, how to verify the hierarchical AS relationships, and how to realize our policy guidelines. Our approach has significant practical value since it preserves the ability of each AS to apply complex local policies without divulging its BGP configurations to others. |
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| Date: February 16 |
| Speaker: Salvatore Torquato, Chemistry, PMI, PACM, and PCTP |
| Title:"Unusual Classical Ground States of Matter" |
Abstract:A classical ground-state configuration of a system of interacting particles is one that minimizes the system potential energy. In the laboratory, such states are produced by slowly cooling a liquid to a temperature of absolute zero, and usually the ground states are crystal structures. However, our theoretical understanding of ground states is far from complete. For example, it is difficult to prove what are the ground states for realistic interactions. I discuss recent theoretical/computational methods that we have formulated to identify unusual crystal ground states as well as disordered ground state
[1,2,3,4]. Although the latter possibility is counterintuitive, there
is no fundamental reason why classical ground states cannot be aperiodic
or disordered.
1) M. Rechtsman, F. H. Stillinger and S. Torquato, Synthetic Diamond and Wurtzite Structures Self-Assemble with Isotropic Pair Interactions , Physical Review E, vol. 75, 031403 (2007).
2) S. Torquato and F. H. Stillinger, "New Duality Relations for Classical Ground States," Physical Review Letters, vol. 100, 020602 (2008).
3) R. D. Batten, F. H. Stillinger and S. Torquato, "Classical Disordered Ground States: Super-Ideal Gases, and Stealth and Equi-Luminous Materials," Journal of Applied Physics, vol. 104, 033504, (2008).
4) A. Scardicchio, F. H. Stillinger and S. Torquato, "Estimates of the Optimal Density of Sphere Packings in High Dimensions, Journal of Mathematical Physics, vol. 49, 043301 (2008).
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| Date: March 2 |
| Speaker: Jonathan Mattingly, Duke University, Mathematics Department |
| Title: Trouble with a chain of stochastic oscillators |
Abstract: I will discuss some recent (but modest) results showing the existence and slow mixing of a stationary chain of Hamiltonian oscillators subject to a heat bath. Such systems are used as simple models of heat conduction or energy transfer. Though the unlimite goal might be seen to under stand the "fourier" like law in this setting, I will be less ambitious. I will show that under some hypotheses, the chain posses a unique stationary state. Surprisingly, even these simple results
require some delicate stochastic averaging. Furthermore, it is the existence of a stationary measure (not the uniquness) which is difficult. This is joint work with Martin Hairer . |
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| Date: March 9 |
| Speaker: Rebecca Willett, Electrical and Computer Engineering, Duke University |
| Title: High-Dimensional Co-Occurrence Density Estimation |
| Abstract:
Co-occurrence data can represent critical information in a variety of contexts, such as meetings in a social network, routers in a communication network, or genes, proteins, and metabolites in biological research. In this talk, I will present two novel approaches to conducting inference from high-dimensional co-occurrence training observations. First, I will describe an efficient recursive algorithm for computing an orthogonal series density estimate in the Walsh basis, which allows for a flexible trade-off between estimation error and computational complexity. In particular, even when there are 2^d coefficients to estimate and d is very large, we can achieve near- minimax error decay rates with a computational complexity which is polynomial in d and depends on the density’s sparsity in the Walsh basis. Second, I will present an online convex programming approach to estimating the likelihood of sequentially observed co-occurrences. We will see that this approach is minimax optimal relative to an oracle estimator and that the optimization at each time can be computed very efficiently in terms of both time and memory.
Rebecca Willett is an assistant professor in the Electrical and Computer Engineering Department at Duke University. She completed her PhD in Electrical and Computer Engineering at Rice University. She received the National Science Foundation CAREER Award in 2007 and is a member of the DARPA Computer Science Study Panel. In addition to studying at Rice, Prof. Willett has worked as a Fellow of the Institute for Pure and Applied Mathematics at UCLA, as a visiting researcher at the University of Wisconsin-Madison and the French National Institute for Research in Computer Science and Control (INRIA), and as a member of the Applied Science Research and Development Laboratory at GE Medical Systems (now GE Healthcare). Her research interests include signal processing and communications with applications in medical imaging, astrophysics, and networks. Additional information, including publications and software, are available online at http://www.ee.duke.edu/~willett/.
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| Date: March 23 |
| Speaker: Zhaohua Wu, Department of Meteorology & Center for Ocean-Atmospheric Prediction Studies, Florida State University |
| Title: The Empirical Mode Decomposition: the method, its progress, and open questions |
| Abstract: The Empirical Mode Decomposition (EMD) was an empirical one-dimensional data decomposition method invented by Dr. Norden Huang about ten years ago and has been used with great success in many fields of science and engineering. In this talk, I will introduce, from the perspective of a physical scientist, the thinking behind and the algorithm of EMD; and its most recent developments, especially the Ensemble EMD (EEMD), a noise-assisted data analysis method, and the multi-dimensional EMD based on EEMD. I will also outline some open questions that we currently do not have answers, or even clues to the answers, such as how to optimize EMD algorithm, what is the mathematical nature of EMD. To a significant degree, this is a talk intended for obtaining helps from mathematicians. |
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| Date: March 30 |
| Speaker: Olgica Milenkovic, Electrical & Computer Engrg, University of Illinois - Urbana-Champaign |
Title:On the interplay between coding theory and compressed sensing
Olgica Milenkovic, ECE Department, UIUC |
Abstract: Compressed sensing (CS) is a signal processing technique that allows for accurate, polynomial time recovery of sparse data-vectors based on a small number of linear measurements. In its most basic form, robust CS can be viewed as a specialized error-control coding scheme in which the data alphabet does not necessarily have the structure of a finite field and where the notion of a “parity-check” is replaced by a more general functionality. It is therefore possible to combine and extend classical CS and coding-theoretic paradigms in terms of introducing new minimum distance, reconstructions complexity, and quantization precision constraints. In this setting, we derive fundamental lower and upper bounds on the achievable compression rate for such constrained compressed sensing (CCS) schemes, and also demonstrate that sparse reconstruction in the presence of noise can be performed via low-complexity correlation-maximization algorithms that operate based on belief propagation iterations.
Our problem analysis is motivated by a myriad of applications ranging from compressed sensing microarray designs, reliability-reordering decoding of linear block-codes, identification in multi-user communication systems, and fault tolerant computing.
This is a joint work with Wei Dai and Vin Pham Hoa from the ECE Department at UIUC.
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| Date: April 13 |
| Speaker: Yaron Lipman, PACM/Computer Science |
| Title: Surface Correspondence via Discrete Uniformization |
| Abstract: Many applied-science fields like medical imaging, computer graphics and biology use meshes to model surfaces. It is a challenging problem to determine whether, how and to what extent such surfaces correspond to each other, e.g. to see whether they are differently parametrized views of one object, or whether they indicate movement of part of an object with respect to its other parts. In this talk we will show how the Uniformization theory can be used to establish correspondences between simply-connected surfaces. We will present an algorithm for automatically finding corresponding points between two discrete surfaces (meshes). The algorithm is based on the observation that the correspondence problem between nearly isometric surfaces is a low dimensional problem in practice, which is well characterized by the Mobius group of fractional linear transformations. |
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| Date: April 20 |
| Speaker: Jennifer Chayes, Microsoft Corporation |
| Title: Interdisciplinarity in the Age of Networks |
| Abstract: Everywhere we turn these days, we find that networks have become increasing appropriate descriptions of relevant interactions. In the high tech world, we see the Internet, the World Wide Web, mobile phone networks, and a variety of online social networks. In economics, we are increasingly experiencing both the positive and negative effects of a global networked economy. In epidemiology, we find disease spreading over our ever growing social networks, complicated by mutation of the disease agents. In problems of world health, distribution of limited resources, such as water resources, quickly becomes a problem of finding the optimal network for resource allocation. In biomedical research, we are beginning to understand the structure of gene regulatory networks, with the prospect of using this understanding to manage the many diseases caused by gene mis-regulation. In this talk, I look quite generally at some of the models we are using to describe these networks, processes we are studying on the networks, algorithms we have devised for the networks, and finally, methods we are developing to indirectly infer network structure from measured data. In particular, I will discuss models and techniques which cut across many disciplinary boundaries. |
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| Date: April 27 |
| Speaker: Adam Burrows, Astrophysics, Princeton University |
| Title: State-of-the-art Computer Simulations of Supernova Explosions |
| Abstract: To simulate supernova explosions, one must solve simultaneously the non-linear, coupled partial differential equations of radiation hydrodynamics. What's more, due to a variety of instabilities and asymmetries, this must eventually be accomplished in 3D. The current state-of-the-art is 2D, plus rotation and magnetic fields (assuming axisymmetry). Nevertheless, with the current suite of codes, we have been able to explore the evolution of the high-density, high-temperature, high-speed environment at the core of a massive star at death. It is in this core that the supernova explosion is launched. However, the complexity of the problem has to date obscured the essential physics and mechanisms of the phenomenon, making it indeed one of the "Grand Challenges" of 21st century astrophysics. Requiring forefront numerical algorithms and massive computational resources, the resolution of this puzzle awaits the advent of peta- and exa-scale architectures and the software to efficiently use them. In this talk, I will review the current state of the science and simulations as we plan for the fully 3D, multi-physics capabilities that promise credibly to crack open this obdurate astrophysical nut. |
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