Institute for Mathematics and its Applications University of Minnesota 400 Lind Hall 207 Church Street SE Minneapolis, MN 55455 
20112012 Program
See http://www.ima.umn.edu/20112012/ for a full description of the 20112012 program on Mathematics of Information.
8:30am9:00am  Coffee  Keller Hall 3176  SW1.302.1.12  
9:00am10:00am  The Milnor Conjectures and Quadratic Forms  Parimala Raman (Emory University)  Keller Hall 3180  SW1.302.1.12 
10:00am10:30am  Coffee break  Keller Hall 3176  SW1.302.1.12  
10:30am11:30am  A solution to the ArfKervaire invariant problem  Douglas Conner Ravenel (University of Rochester)  Keller Hall 3180  SW1.302.1.12 
11:30am11:40am  Break  SW1.302.1.12  
11:40am12:40pm  On the homology of Lie groups made discrete  Fabien Morel (LudwigMaximiliansUniversität München)  Keller Hall 3180  SW1.302.1.12 
12:40pm1:00pm  Closing remarks  Keller Hall 3180  SW1.302.1.12  
2:30pm3:00pm  Coffee break  Lind Hall 400 
2:30pm3:00pm  Coffee break  Lind Hall 400  
3:00pm4:00pm  Computational Knot Theory with KnotPlot  Robert Glenn Scharein (Hypnagogic Software)  Lind Hall 305  PS 
2:30pm3:00pm  Coffee break  Lind Hall 400 
2:30pm3:00pm  Coffee break  Lind Hall 400 
2:30pm3:00pm  Coffee break  Lind Hall 400  
3:00pm4:00pm  TBD  Arthur Szlam (University of Minnesota)  Lind Hall 305  PS 
2:30pm3:00pm  Coffee break  Lind Hall 400 
2:30pm3:00pm  Coffee break  Lind Hall 400 
2:30pm3:00pm  Coffee break  Lind Hall 400 
9:00am9:45am  Coffee and Registration  Keller Hall 3176  W2.1317.12  
9:45am10:00am  Welcome and Introduction  Keller Hall 3180  W2.1317.12  
10:00am11:00am  Tutorial: Cost effective sequencing of rare genetic variations  Yaniv Erlich (Whitehead Institute for Biomedical Research)  Keller Hall 3180  W2.1317.12 
11:00am11:15am  Break  Keller Hall 3176  W2.1317.12  
11:15am12:15pm  Tutorial: Sparse signal recovery  Anna Gilbert (AT&T Laboratories  Research)  Keller Hall 3180  W2.1317.12 
12:15pm2:00pm  Lunch  W2.1317.12  
2:00pm3:00pm  Identification of rare alleles and their carriers using compressed se(que)nsing  Noam Shental (Open University of Israel)  Keller Hall 3180  W2.1317.12 
3:00pm3:15pm  Break  Keller Hall 3176  W2.1317.12  
3:15pm3:45pm  Mining Rare Human Variations using Combinatorial Pooling  Dina Esposito (Whitehead Institute for Biomedical Research)  Keller Hall 3180  W2.1317.12 
3:45pm4:15pm  RNA Structure Characterization from HighThroughput Chemical Mapping Experiments  Sharon Aviran (University of California, Berkeley)  Keller Hall 3180  W2.1317.12 
4:15pm4:30pm  Break  Keller Hall 3176  W2.1317.12  
4:30pm5:30pm  RUMP session  Olgica Milenkovic (University of Illinois at UrbanaChampaign)  Keller Hall 3180  W2.1317.12 
6:30pm8:00pm  Social Hour at the Campus Club 403 Coffman Memorial Union Map  Campus Club  W2.1317.12 
8:30am9:00am  Coffee  Keller Hall 3176  W2.1317.12  
9:00am10:00am  Tutorial: Group Testing and Coding Theory  Atri Rudra (University at Buffalo (SUNY))  Keller Hall 3180  W2.1317.12 
10:00am10:15am  Group Photo  Keller Hall 3180  W2.1317.12  
10:15am11:15am  Network topology as a source of biological information  Natasha Przulj (Imperial College London)  Keller Hall 3180  W2.1317.12 
11:15am11:30am  Break  Keller Hall 3176  W2.1317.12  
11:30am12:30pm  Superimposed Codes and Designs for Group Testing Models  Vyacheslav V. Rykov (University of Nebraska)  Keller Hall 3180  W2.1317.12 
12:30pm2:00pm  Lunch  W2.1317.12  
2:00pm3:00pm  Testing Boolean functions  Alex Samorodnitsky (Hebrew University)  Keller Hall 3180  W2.1317.12 
3:00pm3:15pm  Coffee Break  Keller Hall 3176  W2.1317.12  
3:15pm3:45pm  Combinatorial Pooling Enables Selective Sequencing of the Barley Gene Space  Stefano Lonardi (University of California, Riverside)  Keller Hall 3180  W2.1317.12 
3:45pm4:15pm  Superimposed codes  Zoltan Furedi (Hungarian Academy of Sciences (MTA))  Keller Hall 3180  W2.1317.12 
4:15pm5:30pm  Poster Session and Reception  Lind Hall 400  W2.1317.12  
Poster  Finding one of m defective elements  Christian Deppe (Universität Bielefeld)  
Poster  Upgraded Separate Testing of Inputs in Compressive Sensing  Mikhail B Malyutov (Northeastern University) 
8:30am9:00am  Coffee  Keller Hall 3176  W2.1317.12  
9:00am10:00am  Shifted Transversal Design Smartpooling: increasing sensitivity, specificity and efficiency in highthroughput biology  Nicolas ThierryMieg (Centre National de la Recherche Scientifique (CNRS))  Keller Hall 3180  W2.1317.12 
10:00am10:15am  Break  Keller Hall 3176  W2.1317.12  
10:15am11:15am  Weighted Pooling  Simple and Effective Techniques for Pooled High Throughput Sequencing Design  David Golan (Tel Aviv University)  Keller Hall 3180  W2.1317.12 
11:15am11:30am  Break  Keller Hall 3176  W2.1317.12  
11:30am12:30pm  Genomic Privacy and the Limits of Individual Detection in a Pool  Sriram Sankararaman (Harvard Medical School)  Keller Hall 3180  W2.1317.12 
12:30pm2:00pm  Lunch  W2.1317.12  
2:00pm3:00pm  Superselectors: Efficient Constructions and Applications  Ferdinando Cicalese (Università di Salerno)  Keller Hall 3180  W2.1317.12 
3:00pm3:15pm  Coffee Break  Keller Hall 3176  W2.1317.12  
3:15pm3:45pm  Probabilistic and combinatorial models for quantized group testing  Olgica Milenkovic (University of Illinois at UrbanaChampaign)  Keller Hall 3180  W2.1317.12 
3:45pm4:15pm  Improved Constructions for Nonadaptive Threshold Group Testing  Mahdi Cheraghchi (Carnegie Mellon University)  Keller Hall 3180  W2.1317.12 
4:15pm4:30pm  Break  W2.1317.12  
4:30pm5:30pm  RUMP session  Yaniv Erlich (Whitehead Institute for Biomedical Research)  Keller Hall 3180  W2.1317.12 
8:30am9:00am  Coffee  Keller Hall 3176  W2.1317.12  
9:00am10:00am  Tutorial: The Data Stream Model  David P. Woodruff (IBM Research Division)  Keller Hall 3180  W2.1317.12 
10:00am10:15am  Break  Keller Hall 3176  W2.1317.12  
10:15am11:15am  Sparser JohnsonLindenstrauss Transforms  Jelani Nelson (Princeton University)  Keller Hall 3180  W2.1317.12 
11:15am11:30am  Break  W2.1317.12  
11:30am12:30pm  Length Reduction via Polynomials  Amihood Amir (BarIlan University)  Keller Hall 3180  W2.1317.12 
12:30pm2:00pm  Lunch  W2.1317.12  
2:00pm3:00pm  Reconstruction of bacterial communities using sparse representation  Or Zuk (Broad Institute)  Keller Hall 3180  W2.1317.12 
3:00pm3:15pm  Break  Keller Hall 3176  W2.1317.12  
3:15pm3:45pm  TBD  Mikhail B Malyutov (Northeastern University)  Keller Hall 3180  W2.1317.12 
3:45pm4:15pm  A dynamic and quantitative protein interaction network regulating angiogenesis  Sylvie RicardBlum (Université ClaudeBernard (Lyon I))  Keller Hall 3180  W2.1317.12 
4:15pm4:30pm  Break  Keller Hall 3176  W2.1317.12  
4:30pm5:30pm  RUMP session  Ely Porat (BarIlan University)  Keller Hall 3180  W2.1317.12 
8:30am9:00am  Coffee  Keller Hall 3176  W2.1317.12  
9:00am10:00am  Streaming algorithms for approximating the length of the longest increasing subsequence  Anna Gal (University of Texas at Austin)  Keller Hall 3180  W2.1317.12 
10:00am10:15am  Break  Keller Hall 3176  W2.1317.12  
10:15am11:15am  From screening clone libraries to detecting biological agents  Alexander Schliep (Rutgers University)  Keller Hall 3180  W2.1317.12 
11:15am11:30am  Break  Keller Hall 3176  W2.1317.12  
11:30am12:30pm  A Group Testing Approach to Corruption Localizing Hashing  Annalisa De Bonis (Università di Salerno)  Keller Hall 3180  W2.1317.12 
2:30pm3:00pm  Coffee break  Lind Hall 400 
2:30pm3:00pm  Coffee break  Lind Hall 400 
2:30pm3:00pm  Coffee break  Lind Hall 400 
2:30pm3:00pm  Coffee break  Lind Hall 400 
1:25pm2:25pm  Computing the demagnetizing field in micromagnetics with periodic boundaries  Michael J. Donahue (National Institute of Standards and Technology)  Lind Hall 305  IPS 
2:30pm3:00pm  Coffee break  Lind Hall 400 
2:30pm3:00pm  Coffee break  Lind Hall 400 
2:30pm3:00pm  Coffee break  Lind Hall 400 
2:30pm3:00pm  Coffee break  Lind Hall 400 
Event Legend: 

IPS  Industrial Problems Seminar 
PS  IMA Postdoc Seminar 
SW1.302.1.12  Second Abel Conference: A Celebration of John Milnor 
W2.1317.12  Group Testing Designs, Algorithms, and Applications to Biology 
Amihood Amir (BarIlan University)  Length Reduction via Polynomials 
Abstract: Efficient handling of sparse data is a key challenge in Computer Science. Binary convolutions, such as the Fast Fourier Transform or theWalsh Transform are a useful tool in many applications and are efficiently solved.
In the last decade, several problems required efficient solution of sparse binary convolutions. Both randomized and deterministic algorithms were developed for efficiently computing the sparse FFT. The key operation in all these algorithms was length reduction. The sparse data is mapped into small vectors that preserve the convolution result. The reduction method used todate was the modulo function since it preserves location (of the ”1” bits) up to cyclic shift. In this paper we present a new method for length reduction  polynomials. We show that this method allows a faster deterministic computation of the sparse FFT than currently known in the literature. It also enables the development of an efficient algorithm for computing the binary sparse Walsh Transform. To our knowledge, this is the first such algorithm in the literature. (Joint work with Oren Kappah, Ely Porat, and Amir Rothschild) 

Sharon Aviran (University of California, Berkeley)  RNA Structure Characterization from HighThroughput Chemical Mapping Experiments 
Abstract: New regulatory roles continue to emerge for both natural and engineered noncoding RNAs, many of which have specific secondary and tertiary structures essential to their function. This highlights a growing need to develop technologies that enable rapid and accurate characterization of structural features within complex RNA populations. Yet, available structure characterization techniques that are reliable are also vastly limited by technological constraints, while the accuracy of popular computational methods is generally poor. These limitations thus pose a major barrier to the comprehensive determination of structure from sequence and thereby to the development of mechanistic understanding of transcriptome dynamics. To address this need, we have recently developed a highthroughput structure characterization technique, called SHAPESeq, which simultaneously measures quantitative, single nucleotideresolution, secondary and tertiary structural information for hundreds of RNA molecules of arbitrary sequence. SHAPESeq combines selective 2’hydroxyl acylation analyzed by primer extension (SHAPE) chemical mapping with multiplexed pairedend deep sequencing of primer extension products. This generates millions of sequencing reads, which are then analyzed using a fully automated data analysis pipeline. Previous bioinformatics methods, in contrast, are laborious, heuristic, and expertbased, and thus prohibit highthroughput chemical mapping. In this talk, I will review recent developments in experimental RNA structure characterization as well as advances in sequencing technologies. I will then describe the SHAPESeq technique, focusing on its automated data analysis method, which relies on a novel probabilistic model of a SHAPESeq experiment, adjoined by a rigorous maximum likelihood estimation framework. I will demonstrate the accuracy and simplicity of our approach as well as its applicability to a general class of chemical mapping techniques and to more traditional SHAPE experiments that use capillary electrophoresis to identify and quantify primer extension products. This is joint work with Lior Pachter, Julius Lucks, Stefanie Mortimer, Shujun Luo, Cole Trapnell, Gary Schroth, Jennifer Doudna and Adam Arkin. 

Mahdi Cheraghchi (Carnegie Mellon University)  Improved Constructions for Nonadaptive Threshold Group Testing 
Abstract: The basic goal in combinatorial group testing is to identify a set of up to d defective items within a large population of size n >> d using a pooling strategy. Namely, the items can be grouped together in pools, and a single measurement would reveal whether there are one or more defectives in the pool. The threshold model is a generalization of this idea where a measurement returns positive if the number of defectives in the pool exceeds a fixed threshold u, negative if this number is below a fixed lower threshold L 0.  
Ferdinando Cicalese (Università di Salerno)  Superselectors: Efficient Constructions and Applications 
Abstract: Superselectors subsume several important combinatorial structures used in the past few years to solve problems in group testing, compressed sensing, multichannel conflict resolution and data security. We prove close upper and lower bounds on the size of superselectors and we provide efficient algorithms for their constructions. Albeit our bounds are very general, when they are instantiated on the combinatorial structures that are particular cases of superselectors (e.g., $(p,k,n)$selectors cite{DGV}, $(d,ell)$listdisjunct matrices, $MUT_k(r)$families, $FUT(k, alpha)$families, etc.) they match the best known bounds in terms of size of the structures (the relevant parameter in the applications). For appropriate values of parameters, our results also provide the first efficient deterministic algorithms for the construction of such structures.  
Annalisa De Bonis (Università di Salerno)  A Group Testing Approach to Corruption Localizing Hashing 
Abstract: Efficient detection of integrity violations is crucial for the reliability of both data at rest and data in transit. In addition to detecting corruptions, it is often desirable to have the capability of obtaining information about the location of corrupted data blocks. While ideally one would want to always find all changes in the corrupted data, in practice this capability may be expensive, and one may be content with localizing or finding a superset of any changes. Corruptionlocalizing hashing is a cryptographic primitive that enhances collisionintractable hash functions thus improving the detection property of these functions into a suitable localization property. Besides allowing detection of changes in the input data, corruptionlocalizing hash schemes also obtain some superset of the changes location, where the accuracy of this superset with respect to the actual changes is a metric of special interest, called localization factor. In this talk we will address the problem of designing corruptionlocalizing hash schemes with reduced localization factor and with small time and storage complexity. We will show that this problem corresponds to a particular variant of nonadaptive group testing, and illustrate a construction technique based on superimposed codes. This group testing approach allowed to obtain corruptionlocalizing hash schemes that greatly improve on previous constructions. In particular, we will present a corruptionlocalizing hash scheme that achieves an arbitrarily small localization factor while only incurring a sublinear time and storage complexity.  
Christian Deppe (Universität Bielefeld)  Poster  Finding one of m defective elements 
Abstract: In contrast to the classical goal of group testing we want to find onw defective elements of $D$ defective elements. We examine four different test functions. We give adaptive strategies and lower bounds for the number of tests. We treat the cases if the number of defectives are known and if the number of defectives are bounded.  
Michael J. Donahue (National Institute of Standards and Technology)  Computing the demagnetizing field in micromagnetics with periodic boundaries 
Abstract: Micromagnetics is a classical model of magnetism in magnetic materials,
operative at the nanometer length scale. Typical micromagnetic
simulations model magnetic parts of dimensions ranging from tens of
nanometers up to a few micrometers. The most computationally expensive
portion of a micromagnetic simulation is the evaluation of the
longrange selfmagnetostatic (aka dipole or demagnetizing) field. In
this talk I will provide some history of micromagnetics at NIST, and
discuss in detail some of the numerical and computational challenges
involved in a fast, accurate method for computing the demagnetizing
field in a simulation with periodic boundaries. Michael Donahue is a mathematician in the Applied and Computational Mathematics Division at the National Institute of Standards and Technology (NIST) in Gaithersburg, Maryland, where he does research on micromagnetics and leads development of the OOMMF public domain micromagnetics package. Prior to joining NIST, he was an industrial postdoctoral research associate at the IMA, working in conjunction with Siemens Corporate Research on artificial neural networks and computer vision. Dr. Donahue holds PhDs in mathematics and engineering from The Ohio State University, and has authored over 50 journal publications. 

Yaniv Erlich (Whitehead Institute for Biomedical Research)  Tutorial: Cost effective sequencing of rare genetic variations 
Abstract: In the past few years, we have experienced a paradigm shift in human genetics. Accumulating lines of evidence have highlighted the pivotal role of rare genetic variations in a wide variety of traits and diseases. Studying rare variations is a needle in a haystack problem, as large cohorts have to be assayed in order to trap the variations and gain statistical power. The performance of DNA sequencing is exponentially growing, providing sufficient capacity to profile an extensive number of specimens. However, sample preparation schemes do not scale as sequencing capacity. A brute force approach of preparing hundredths to thousands of specimens for sequencing is cumbersome and costprohibited. The next challenge, therefore, is to develop a scalable technique that circumvents the bottleneck in sample preparation. My tutorial will provide background on rare genetic variations and DNA sequencing. I will present our sample prep strategy, called DNA Sudoku, that utilizes combinatorial pooling/compressed sensing approach to find rare genetic variations. More importantly, I will discuss several major distinction from the classical combinatorial due to sequencing specific constraints. 

Dina Esposito (Whitehead Institute for Biomedical Research)  Mining Rare Human Variations using Combinatorial Pooling 
Abstract: Finding rare genetic variations in large cohorts requires tedious preparation of large numbers of specimens for sequencing. We are developing a solution, called DNA Sudoku, to reduce prep time and increase the throughput of samples. By using a combinatorial pooling approach, we multiplex specimens and then barcode the pools, rather than individuals, for sequencing in a single lane on the Illumina platform. We have developed a protocol for quantifying, calibrating, and pooling DNA samples using a liquidhandling robot, which has required a significant amount of testing in order to reduce volume variation. I will discuss our protocol and the steps we have taken to reduce CV. For accurate decoding and to reduce the possibility of specimen dropout, it is important that the DNA samples are accurately quantified and calibrated so that equal amounts can be pooled and sequenced. We can determine the number of carriers in each pool from sequencing output and reconstruct the original identity of individual specimens based on the pooling design, allowing us to identify a small number of carriers in a large cohort. 

Zoltan Furedi (Hungarian Academy of Sciences (MTA))  Superimposed codes 
Abstract: There are many instances in Coding Theory when codewords must be restored from
partial information, like defected data (error correcting codes), or some superposition of the strings. These lead to superimposed codes, a close relative of group testing problems. There are lots of versions and related problems, like Sidon sets, sumfree sets, unionfree families, locally thin families, coverfree codes and families, etc. We discuss two cases cancellative and unionfree codes. A family of sets Ƒ (and the corresponding code of 01 vectors) is called unionfree if A ∪ B≠ C ∪ D and A,B,C,D ∈ F imply {A,B} = {C,D}. Ƒ is called tcancellative if for all distict t + 2 members A_{1}, … ,A_{t} and B,C ∈ Ƒ Let c_{t}(n) be the size of the largest tcancellative code on n elements. We significantly improve the previous upper bounds of Körner and Sinaimeri, e.g., we show c2(n) ≤ 2^{0:322n} (for n > n_{0}). 

Anna Gal (University of Texas at Austin)  Streaming algorithms for approximating the length of the longest increasing subsequence 
Abstract: The data stream model allows only one way access to the data, possibly with several passes. This model is motivated by problems related to processing very large data sets, when it is desirable to keep only a small part of the data in active memory at any given point during the computation. I will talk about proving lower bounds on how much space (memory) is necessary to still be able to solve the given task. I will focus on the problem of approximating the length of the longest increasing subsequence, which is a measure of how well the data is sorted. Joint work with Parikshit Gopalan. 

Anna Gilbert (AT&T Laboratories  Research)  Tutorial: Sparse signal recovery 
Abstract: My talk will be a tutorial about sparse signal recovery but, more importantly, I will provide an overview of what the research problems are at the intersection of biological applications of group testing, streaming algorithms, sparse signal recovery, and coding theory. The talk should help set the stage for the rest of the workshop.  
David Golan (Tel Aviv University)  Weighted Pooling  Simple and Effective Techniques for Pooled High Throughput Sequencing Design 
Abstract: Despite the rapid decrease in sequencing costs, sequencing a large group of individuals is still prohibitively expensive. Recently, several sophisticated pooling designs were suggested that can identify carriers of rare alleles in large cohorts with a significantly smaller number of lanes, thus dramatically reducing the cost of such large scale genotyping projects. These approaches all use combinatorial pooling designs where each individual is either present in a pool or absent from it. One can then infer the number of carriers in a pool, and by combining information across pools, reconstruct the identity of the carriers. We show that one can gain further efficiency and cost reduction by using “weighted” designs, in which different individuals donate different amounts of DNA to the pools. Intuitively, in this situation the number of mutant reads in a pool does not only indicate the number of carriers, but also of the identity of the carriers. We describe and study a simple but powerful example of such weighted designs, with nonoverlapping pools. We demonstrate that even this naive approach is not only easier to implement and analyze but is also competitive in terms of accuracy with combinatorial designs when identifying very rare variants, and is superior to the combinatorial designs when genotyping more common variants. We then discuss how weighting can be further incorporated into existing designs to increase their accuracy and demonstrate the resulting improvement in reconstruction efficiency using simulations. Finally, we argue that these weighted designs have enough power to facilitate detection of common alleles, so they can be used as a cornerstone of wholeexome or even wholegenome sequencing projects. 

Stefano Lonardi (University of California, Riverside)  Combinatorial Pooling Enables Selective Sequencing of the Barley Gene Space 
Abstract: We propose a new sequencing protocol that combines recent advances in
combinatorial pooling design and secondgeneration sequencing
technology to efficiently approach de novo selective genome
sequencing. We show that combinatorial pooling is a costeffective
and practical alternative to exhaustive DNA barcoding when dealing
with hundreds or thousands of DNA samples, such as genometiling
generich BAC clones. The novelty of the protocol hinges on the
computational ability to efficiently compare hundreds of million of
short reads and assign them to the correct BAC clones so that the
assembly can be carried out clonebyclone. Experimental results on
simulated data for the rice genome show that the deconvolution is
extremely accurate (99.57% of the deconvoluted reads are assigned to
the correct BAC), and the resulting BAC assemblies have very high
quality (BACs are covered by contigs over about 77% of their length,
on average). Experimental results on real data for a generich subset of
the barley genome confirm that the deconvolution is accurate (almost
70% of left/right pairs in pairedend reads are assigned to the same
BAC, despite being processed independently) and the BAC assemblies have
good quality (the average sum of all assembled contigs is about 88%
of the estimated BAC length). Joint work with D. Duma (UCR), M. Alpert (UCR), F. Cordero (U of Torino), M. Beccuti (U of Torino), P. R. Bhat (UCR and Monsanto), Y. Wu (UCR and Google), G. Ciardo (UCR), B. Alsaihati (UCR), Y. Ma (UCR), S. Wanamaker (UCR), J. Resnik (UCR), and T. J. Close (UCR). Preprint available at http://arxiv.org/abs/1112.4438 

Mikhail B Malyutov (Northeastern University)  Poster  Upgraded Separate Testing of Inputs in Compressive Sensing 
Abstract: Screening experiments (SE) deal with finding a small number s Active Inputs (AIs) out of a vast total amount t of inputs in a regressionmodel. Of special interest in the SE theory is finding the socalled maximal rate (capacity). For a set of t elements, denote the set of its ssubsets by (s, t). Introduce a noisy system with t binary inputs and one output y. Suppose that only s 0. The fcapacity Cf (s) = limt!1(log t/Nf (s, t, )) for any > 0 is the ‘limit for the per formance of the fanalysis’. We obtained tight capacity bounds [4], [5] by formalizing CSS as a special case of MultiAccess Communication Channels (MAC) of information transmission capacity region construction developed by R. Ahlswede in [1] and comparing CSS’ maximal rate (capacity) with small error for two practical methods of outputs’ analysis under the optimal CSS design motivated by applications like [2] . Recovering Active Inputs with small error probability and accurate parameter estimation are both possible with rates less than capacity and impossible with larger rates. A staggering amount of attention was recently devoted to the study of compressive sensing and related areas using sparse priors in over parameterized linear models which may be viewed as a special case of our models with continuous input levels. The threshold phenomenon was empirically observed in early papers [3], [6] : as the dimension of a randominstance of a problem grows there is a sharp transition from successful recovery to failure as a function of the number of observations versus the dimension and sparsity of the unknown signal. Finding this threshold is closely related to our capacity evaluation. Some threshold bounds for the compressive sensing were made using standard informationtheoretic tools, e.g. in [15]  
Olgica Milenkovic (University of Illinois at UrbanaChampaign)  Probabilistic and combinatorial models for quantized group testing 
Abstract: We consider a novel group testing framework where defectives obey a probabilistic model in which the number and set of defectives is governed by a graphical model. We furthermore assume that the defectives have importance factors that influence their strength on the test outcomes and the accuracy with which the outcomes are read. This kind of scenario arises, for example, in MAC channels with networked users using different communication powers, or in DNA pooling schemes which involve large families.  
Fabien Morel (LudwigMaximiliansUniversität München)  On the homology of Lie groups made discrete 
Abstract: In this talk I will recall and discuss the conjecture of John Milnor on the homology of Lie groups made discrete, as well as its algebraic analogue, the Friedlander conjecture. In a work still partially in progress, we give a proof of that conjecture for algebraic groups G over algebraically closed fields. I will sketch some ideas behind this proof, in particular the role of A1homotopy theory (already used by V. Voevodsky to prove other conjectures of John Milnor concerning mod 2 Galois cohomology and quadratic forms) and the role of a new object attached to G, its simplicial building. We will emphasize the case G = SL_2, SL_3,... 

Jelani Nelson (Princeton University)  Sparser JohnsonLindenstrauss Transforms 
Abstract: The JohnsonLindenstrauss (JL) lemma (1984) states that any n points
in ddimensional Euclidean space can be embedded into k = O((log
n)/eps^2) dimensions so that all pairwise distances are preserved up
to 1+/eps. Furthermore, this embedding can be achieved via a linear
mapping. The JL lemma is a useful tool for speeding up solutions to
several highdimensional problems: closest pair, nearest neighbor,
diameter, minimum spanning tree, etc. It also speeds up some
clustering and string processing algorithms, reduces the amount of
storage required to store a dataset, and can be used to reduce memory
required for numerical linear algebra problems such as linear
regression and low rank approximation. The original proofs of the JL lemma let the linear mapping be specified by a random dense k x d matrix (e.g. i.i.d. Gaussian entries). Thus, performing an embedding requires dense matrixvector multiplication. We give the first construction of linear mappings for JL in which only a subconstant fraction of the embedding matrix is nonzero, regardless of how eps and n are related, thus always speeding up the embedding time. Previous constructions only achieved sparse embedding matrices for 1/eps >> log n. This is joint work with Daniel Kane (Stanford). 

Natasha Przulj (Imperial College London)  Network topology as a source of biological information 
Abstract: Sequencebased computational approaches have revolutionized biological understanding. However, they can fail to explain some biological phenomena. Since proteins aggregate to perform a function instead of acting in isolation, the connectivity of a protein interaction network (PIN) will provide additional insight into the inner working on the cell, over and above sequences of individual proteins. We argue that sequence and network topology give insights into complementary slices of biological information, which sometimes corroborate each other, but sometimes do not. Hence, the advancement depends on the development of sophisticated graphtheoretic methods for extracting biological knowledge purely from network topology before being integrated with other types of biological data (e.g., sequence). However, dealing with large networks is nontrivial, since many graphtheoretic problems are computationally intractable, so heuristic algorithms are sought. Analogous to sequence alignments, alignments of biological networks will likely impact biomedical understanding. We introduce a family of topologybased network alignment (NA) algorithms, (that we call GRAAL algorithms), that produces by far the most complete alignments of biological networks to date: our alignment of yeast and human PINs demonstrates that even distant species share a surprising amount of PIN topology. We show that both species phylogeny and protein function can be extracted from our topological NA. Furtermore, we demonstrate that the NA quality improves with integration of additional data sources (including sequence) into the alignment algorithm: surprisingly, 77.7% of proteins in the baker’s yeast PIN participate in a connected subnetwork that is fully contained in the human PIN suggesting broad similarities in internal cellular wiring across all life on Earth. Also, we demonstrate that topology around cancer and noncancer genes is different and when integrated with functional genomics data, it successfully predicts new cancer genes in melanogenesisrelated pathways. 

Parimala Raman (Emory University)  The Milnor Conjectures and Quadratic Forms 
Abstract: The Milnor conjectures relating the graded Witt ring and the mod2 Galois cohomology ring of a field have been a driving force in the algebraic theory of quadratic forms. The degree 2 norm residue isomorphism, due to Merkurjev, established the first case of the Milnor conjectures and ushered in a new era in the theory of quadratic forms. We shall explain some of the consequences of the Milnor conjectures, with particular reference to invariants of fields associated to quadratic forms.  
Douglas Conner Ravenel (University of Rochester)  A solution to the ArfKervaire invariant problem 
Abstract: The 1963 work of KervaireMilnor on the classification of exotic spheres in terms of the stable homotopy groups of spheres left one unanswered question in dimensions congruent to two modulo four. Subsequent work by BrownPeterson and Browder gave the answer in all dimensions that are not two less than a power of two. We solve the problem in all remaining cases except 126. Our answer is the opposite of the one that many sought in the 1970s.  
Sylvie RicardBlum (Université ClaudeBernard (Lyon I))  A dynamic and quantitative protein interaction network regulating angiogenesis 
Abstract: Angiogenesis, consisting in the formation of blood vessels from preexisting ones, is of crucial importance in pathological situations such as cancer and diabetes and is a therapeutic target for these two diseases. We have developed protein and sugar arrays probed by surface plasmon resonance (SPR) imaging to identify binding partners of proteins, polysaccharides and receptors regulating angiogenesis. Interactions collected from our own experiments and from literature curation have been used to build a network comprising proteinprotein and proteinpolysaccharide interactions. To switch from a static to a dynamic and quantitative interaction network, we have measured kinetics and affinity of interactions by SPR to discriminate transient from stable interactions and to prioritize interactions in the network. We have also identified protein interaction sites either experimentally or by molecular modeling to discriminate interactions occurring simultaneously from those taking place sequentially. The ultimate step is to integrate, using bioinformatics tools, all these parameters in the interaction network together with inhibitors of these interactions and with gene and protein expression data available from Array Express or Gene Expression Omnibus and from the Human Protein Atlas. This dynamic network will allow us to understand how angiogenesis is regulated in a concerted fashion via several receptors and signaling pathways, to identify crucial interactions for the integrity of the network that are potential therapeutic targets, and to predict the side effects of antiangiogenic treatments.  
Atri Rudra (University at Buffalo (SUNY))  Tutorial: Group Testing and Coding Theory 
Abstract: Group testing was formalized by Dorfman in his 1943 paper and was originally used in WWII to identify soldiers with syphilis. The main insight in this application is that blood samples from different soldiers can be combined to check if at least one of soldiers in the pool has the disease. Since then group testing has found numerous applications in many areas such as (computational) biology, combinatorics and (theoretical) computer science. Theory of errorcorrecting codes, or coding theory, was born in the works of Shannon in 1948 and Hamming in 1950. Codes are ubiquitous in our daily life and have also found numerous applications in theoretical computer science in general and computational complexity in particular. Kautz and Singleton connected these two areas in their 1964 paper by using "code concatenation" to design good group testing schemes. All of the (asymptotically) best know explicit constructions of group testing schemes use the code concatenation paradigm. In this talk, we will focus on the "decoding" problem for group testing: i.e. given the outcomes of the tests on the pools, identify the infected soldiers. Recent applications of group testing in data stream algorithm require sublinear time decoding, which is not guaranteed by the traditional constructions. The talk will first survey the KautzSingleton construction and then will will show how recent developments in list decoding of codes lead in a modular way to sublinear time decodable group testing schemes. 

Vyacheslav V. Rykov (University of Nebraska)  Superimposed Codes and Designs for Group Testing Models 
Abstract: We will discuss superimposed codes and nonadaptive group testing designs arising from the potentialities of compressed genotyping models in molecular biology. The given survey is also motivated by the 30th anniversary of our recurrent upper bound on the rate of superimposed codes published in 1982.  
Alex Samorodnitsky (Hebrew University)  Testing Boolean functions 
Abstract: I will talk about property testing of Boolean functions, concentrating on two topics: testing monotonicity (an example of a combinatorial property) and testing the property of being a lowdegree polynomial (an algebraic property).  
Sriram Sankararaman (Harvard Medical School)  Genomic Privacy and the Limits of Individual Detection in a Pool 
Abstract: Statistical power to detect associations in genomewide association studies can be enhanced by combining data across studies in metaanalysis or replication studies. Such methods require data to flow freely in the scientific community, however, and this raises privacy concerns. Till recently, many studies pooled individuals together, making only the allele frequencies of each SNP in the pool publicly available. However a technique that could be used to detect the presence of individual genotypes from such data prompted organizations such as the NIH to restrict public access to summary data . To again allow public access to data from association studies, we need to determine which set of SNPs can be safely exposed while preserving an acceptable level of privacy. To answer this question, we provide an upper bound on the power achievable by any detection method as a function of factors such as the number and the allele frequencies of exposed SNPs, the number of individuals in the pool, and the false positive rate of the method. Our approach is based on casting the problem in a statistical hypothesis testing framework for which the likelihood ratio test (LRtest) attains the maximal power achievable. Our analysis provides quantitative guidelines for researchers to make SNPs public without compromising privacy. We recommend, based on our analysis, that only common independent SNPs be exposed. The final decision regarding the exposed SNPs should be based on the analytical bound in conjunction with empirical estimates of the power of the LR test. To this end, we have implemented a tool, SecureGenome, that determines the set of SNPs that can be safely exposed for a given dataset. 

Robert Glenn Scharein (Hypnagogic Software)  Computational Knot Theory with KnotPlot 
Abstract: Mathematical knot theory is an exciting branch of topology that is relevant to physics, chemistry and biology. After a brief introduction to knot theory, we will explore several applications where computational methods play a useful role. When experimenting with knots on a computer, it is helpful to have powerful tools for the creation of initial conformations, for performing simulations on those conformations and also to compute topological and geometric properties of any resulting products. One such tool is the software KnotPlot, developed by the speaker over a period of many years. KnotPlot permits a wide range of interesting experiments to be performed. Several of these will be discussed, one important area being the tangling and untangling of DNA. Finally, we will dip into the more esoteric realm of higher dimensional knotting.  
Alexander Schliep (Rutgers University)  From screening clone libraries to detecting biological agents 
Abstract: Group testing has made many contributions to modern molecular biology.
In the Human Genome Project large clone libraries where created
to amplify DNA. Widely used group testing schemes vastly accelerated
the detection of overlaps between the individual clones in these libraries through experiments, realizing savings both in effort and materials. Modern molecular biology also contributed to group testing. The problem of generalized group testing (in the combinatorial sense) arises naturally, when one uses oligonucleotide probes to identify biological agents present in a sample. In this setting a group testing design cannot be chosen arbitrarily. The possible columns of a group testing design matrix are prescribed by the biology, namely by the hybridization reactions between target DNA and probes 

Noam Shental (Open University of Israel)  Identification of rare alleles and their carriers using compressed se(que)nsing 
Abstract: Identification of rare variants by resequencing is important both for detecting novel variations and for screening individuals for known disease alleles. New technologies enable lowcost resequencing of target regions, although it is still prohibitive to test more than a few individuals. We propose a novel pooling design that enables the recovery of novel or known rare alleles and their carriers in groups of individuals. The method is based on combining nextgeneration sequencing technology with a Compressed Sensing (CS) approach. The approach is general, simple and efficient, allowing for simultaneous identification of multiple variants and their carriers.
It reduces experimental costs, i.e., both sample preparation related costs and direct sequencing costs, by up to 70 fold, and thus allowing to scan much larger cohorts.
We demonstrate the performance of our approach over several publicly available data sets, including the 1000 Genomes Pilot 3 study.
We believe our approach may significantly improve cost effectiveness of future association studies, and in screening large DNA cohorts for specific risk alleles. We will present initial results of two projects that were initiated following publication. The first project concerns identification of de novo SNPs in genetic disorders common among Ashkenazi Jews, based on sequencing 3000 DNA samples. The second project in plant genetics involves identifying SNPs related to water and silica homeostasis in Sorghum bicolor, based on sequencing 3000 DNA samples using 12 Illumina lanes. Joint work with Amnon Amir from the Weizmann Institute of Science, and Or Zuk from the Broad Institute of MIT and Harvard 

Nicolas ThierryMieg (Centre National de la Recherche Scientifique (CNRS))  Shifted Transversal Design Smartpooling: increasing sensitivity, specificity and efficiency in highthroughput biology 
Abstract: Group testing, also know as smartpooling, is a promising strategy for achieving high efficiency, sensitivity, and specificity in systemslevel projects. It consists in assaying wellchosen pools of probes, such that each probe is present in several pools, hence tested several times. The goal is to construct the pools so that the positive probes can usually be directly identified from the pattern of positive pools, despite the occurrence of false positives and false negatives. While striving for this goal, two interesting mathematical or computational problems emerge: the pooling problem (how should the pools be designed?), and the decoding problem (how to interpret the outcomes?). In this talk I will discuss these questions and the solutions we have proposed: a flexible and powerful combinatorial construction for designing smartpools (the Shifted Transveral Design, STD), and an efficient exact algorithm for interpreting results (interpool). I will then present the results of validation experiments that we have performed in the context of yeast twohybrid interactome mapping.  
David P. Woodruff (IBM Research Division)  Tutorial: The Data Stream Model 
Abstract: The data stream model has emerged as a way of analyzing algorithmic efficiency in the presence of massive data sets. Typically the algorithm is allowed a few (usually one) passes over the input, and must use limited memory and have very fast per input item processing time. I will give a survey of algorithms and lower bounds in this area, with an emphasis on problems such as norm estimation, numerical linear algebra, empirical entropy, l_psampling, and heavy hitters. Timepermitting I'll also discuss the extension to functional monitoring, in which there are multiple sites each with a data stream and a central coordinator should continuously maintain a statistic over the union of the data streams.  
Or Zuk (Broad Institute)  Reconstruction of bacterial communities using sparse representation 
Abstract: Determining the identities and frequencies of species present in a sample is a central problem in metagenomics, with scientific, environmental and clinical implications. A popular approach to the problem is sequencing the Ribosomal 16s RNA gene in the sample using universal primers, and using variation in the gene's sequence between different species to identify the species present in the sample. We present a novel framework for community reconstruction, based on sparse representation; while millions of microorganisms are present on earth, with known 16s sequences stored in a database, only a small minority (typically a few hundreds) are likely to be present in any given sample, We discuss the statistical framework, algorithms used and results in terms of accuracy and species resolution. 
Alejandro Adem  University of British Columbia  1/29/2012  2/1/2012 
Anar Akhmedov  University of Minnesota  1/30/2012  2/1/2012 
Zack W Almquist  University of California, Irvine  2/26/2012  3/2/2012 
Brendan P.W. Ames  University of Minnesota  8/31/2011  8/30/2012 
Amihood Amir  BarIlan University  2/12/2012  2/16/2012 
John David Arellano  Rice University  2/25/2012  3/2/2012 
Amir Asiaee Taheri  University of Minnesota  2/27/2012  3/2/2012 
Sharon Aviran  University of California, Berkeley  2/12/2012  2/15/2012 
Gary Bader  University of Toronto  2/26/2012  3/1/2012 
Joel S Bader  Johns Hopkins University  2/26/2012  3/2/2012 
Arindam Banerjee  University of Minnesota  9/1/2011  6/30/2012 
Alexander Barg  University of Maryland  2/12/2012  2/16/2012 
Hyman Bass  University of Michigan  1/29/2012  2/1/2012 
Maria Basterra  University of New Hampshire  1/29/2012  2/1/2012 
Jeremy Bellay  University of Maryland  2/26/2012  3/2/2012 
Tanya BergerWolf  University of Illinois at Chicago  2/26/2012  3/2/2012 
Julie Bergner  University of California, Riverside  1/29/2012  2/1/2012 
Andrew John Beveridge  Macalester College  9/1/2011  5/15/2012 
Smriti Bhagat  Technicolor Inc.  2/27/2012  2/29/2012 
Manisha Bhardwaj  University of Houston  2/26/2012  3/2/2012 
Jodi Black  Bucknell University  1/29/2012  2/1/2012 
Mathieu Blanchette  McGill University  2/26/2012  3/3/2012 
Sergey G Bobkov  University of Minnesota  9/1/2011  6/30/2012 
Shyam Boriah  University of Minnesota  2/27/2012  3/2/2012 
William Browder  Princeton University  1/29/2012  2/1/2012 
Yiqing Cai  University of Pennsylvania  2/26/2012  3/2/2012 
Luca Capogna  University of Minnesota  8/15/2011  6/10/2012 
Sylvain Edward Cappell  New York University  1/29/2012  2/1/2012 
Aycil Cesmelioglu  University of Minnesota  9/30/2010  8/30/2012 
Huilan Chang  National University of Kaohsiung  2/12/2012  2/17/2012 
Mahdi Cheraghchi  Carnegie Mellon University  2/12/2012  2/17/2012 
Mung Chiang  Princeton University  2/27/2012  3/2/2012 
SouCheng Choi  Argonne National Laboratory  2/12/2012  2/16/2012 
Ferdinando Cicalese  Università di Salerno  2/11/2012  2/16/2012 
Ionut CiocanFontanine  University of Minnesota  1/31/2012  2/1/2012 
Barry Cipra  NONE  1/30/2012  2/1/2012 
Paolo Codenotti  University of Minnesota  9/1/2011  8/30/2012 
Frederick R. Cohen  University of Rochester  1/29/2012  2/1/2012 
Graham Cormode  AT&T Laboratories  Research  2/27/2012  3/2/2012 
Lenore J. Cowen  Tufts University  2/26/2012  3/2/2012 
Mark Crovella  Boston University  2/26/2012  3/2/2012 
Jintao Cui  University of Minnesota  8/31/2010  8/30/2012 
Xiaoyi Cui  University of Minnesota  1/30/2012  2/1/2012 
Phuong Dao  Simon Fraser University  2/26/2012  3/2/2012 
Isabel K. Darcy  University of Iowa  9/1/2011  6/30/2012 
Ingrid Daubechies  Duke University  2/12/2012  2/17/2012 
James F Davis  Indiana University  1/29/2012  2/1/2012 
Annalisa De Bonis  Università di Salerno  2/12/2012  2/17/2012 
Christian Deppe  Universität Bielefeld  2/12/2012  2/18/2012 
Raamesh Deshpande  University of Minnesota  2/27/2012  3/2/2012 
Michael J. Donahue  National Institute of Standards and Technology  2/23/2012  2/24/2012 
DingZhu Du  University of Texas  2/12/2012  2/15/2012 
William G. Dwyer  University of Notre Dame  1/29/2012  2/2/2012 
Robert Edwards  University of California, Los Angeles  1/30/2012  2/1/2012 
Geir Ellingsrud  University of Oslo  1/29/2012  2/1/2012 
Amin Emad  University of Illinois at UrbanaChampaign  2/12/2012  2/17/2012 
Yaniv Erlich  Whitehead Institute for Biomedical Research  2/12/2012  2/17/2012 
Leonardo Espin  NONE  9/1/2011  6/30/2012 
Dina Esposito  Whitehead Institute for Biomedical Research  2/12/2012  2/17/2012 
Pedro Andres Forero  University of Minnesota  2/27/2012  3/2/2012 
John Fornaess  University of Michigan  1/28/2012  2/1/2012 
Zoltan Furedi  Hungarian Academy of Sciences (MTA)  2/12/2012  2/17/2012 
Anna Gal  University of Texas at Austin  2/12/2012  2/17/2012 
Tingran Gao  Duke University  1/29/2012  2/1/2012 
Carlos Andres GaravitoGarzon  University of Minnesota  9/8/2011  6/30/2012 
Nikolaos Gatsis  University of Minnesota  2/27/2012  3/2/2012 
Hillel H. Gershenson  NONE  1/30/2012  2/1/2012 
Lise Getoor  University of Maryland  2/26/2012  3/1/2012 
Georgios B Giannakis  University of Minnesota  2/27/2012  3/2/2012 
Anna Gilbert  AT&T Laboratories  Research  2/12/2012  2/17/2012 
Samuel Gitler  CINVESTAV  1/29/2012  2/1/2012 
David Golan  Tel Aviv University  2/12/2012  2/17/2012 
Manuel Gomez Rodriguez  MaxPlanckInstitut für Intelligente Systeme  2/26/2012  3/3/2012 
Robert Gulliver  University of Minnesota  1/30/2012  2/1/2012 
Ian Hambleton  McMaster University  1/29/2012  2/1/2012 
Michael Hill  University of Virginia  1/29/2012  2/1/2012 
Shawndra Hill  University of Pennsylvania  2/26/2012  3/1/2012 
Michael J. Hopkins  Harvard University  1/28/2012  2/1/2012 
Yulia Hristova  University of Minnesota  9/1/2010  8/31/2012 
Miriam Huntley  Harvard University  1/30/2012  2/1/2012 
Dale Husemoller  Max Planck Institute for Mathematics  1/29/2012  2/1/2012 
Ali Jadbabaie  University of Pennsylvania  2/29/2012  3/2/2012 
Bjørn Jahren  University of Oslo  1/29/2012  2/2/2012 
Vuk Janjic  Imperial College London  2/26/2012  3/2/2012 
Dihua Jiang  University of Minnesota  1/30/2012  2/1/2012 
Niles Johnson  University of Georgia  1/29/2012  2/1/2012 
Igor Jurisica  University of Toronto  2/26/2012  3/2/2012 
Donald Kahn  University of Minnesota  1/30/2012  2/1/2012 
Jaya Kawale  University of Minnesota  2/27/2012  3/2/2012 
Hee Jung Kim  Pohang University of Science and Technology (POSTECH)  1/29/2012  2/1/2012 
Carl Kingsford  University of Maryland  2/26/2012  3/2/2012 
Robion Kirby  University of California, Berkeley  1/29/2012  2/1/2012 
Elizabeth Koch  University of Minnesota  2/27/2012  3/2/2012 
Eric Kolaczyk  Boston University  2/26/2012  2/29/2012 
Mehmet Koyuturk  Case Western Reserve University  2/28/2012  3/2/2012 
Ravi Kumar  Yahoo! Inc.  2/27/2012  3/2/2012 
Kee Yuen Lam  University of British Columbia  1/29/2012  2/1/2012 
Tsit Yuen Lam  University of California, Berkeley  1/29/2012  2/1/2012 
Tyler Lawson  University of Minnesota  1/30/2012  2/1/2012 
YoungJu Lee  Rutgers University  2/19/2012  2/21/2012 
Gilad Lerman  University of Minnesota  9/1/2011  6/30/2012 
Jure Leskovec  Stanford University  2/29/2012  3/2/2012 
Lizao Li  University of Minnesota  1/30/2012  2/1/2012 
TianJun Li  University of Minnesota  1/30/2012  2/1/2012 
Tong Li  University of Iowa  2/26/2012  3/3/2012 
Wenbo Li  University of Delaware  9/1/2011  5/30/2012 
David LibenNowell  Carleton College  2/27/2012  3/2/2012 
LekHeng Lim  University of Chicago  2/1/2012  6/10/2012 
Ayelet Lindenstrauss  Indiana University  1/29/2012  2/1/2012 
Xin Liu  University of Minnesota  8/31/2011  8/30/2012 
Stefano Lonardi  University of California, Riverside  2/12/2012  2/16/2012 
Ying Lu  University of Minnesota  2/27/2012  3/2/2012 
Tom Lyche  University of Oslo  1/29/2012  2/1/2012 
Shiqian Ma  University of Minnesota  8/31/2011  8/30/2013 
Ib Madsen  University of Copenhagen  1/29/2012  2/1/2012 
Mikhail B Malyutov  Northeastern University  2/12/2012  2/18/2012 
Yi Mao  Michigan State University  2/12/2012  2/17/2012 
Yu (David) Mao  University of Minnesota  8/31/2010  8/30/2012 
Albert Marden  University of Minnesota  1/30/2012  2/1/2012 
Athina Markopoulou  University of California, Irvine  2/26/2012  3/2/2012 
Gabriela Martínez  University of Minnesota  8/31/2011  8/30/2013 
John McCleary  Vassar College  1/29/2012  2/2/2012 
Dusa McDuff  Barnard College  1/27/2012  2/2/2012 
Danielle Paola Mersch  Université de Lausanne  2/25/2012  3/3/2012 
William Messing  University of Minnesota  1/30/2012  2/1/2012 
Olgica Milenkovic  University of Illinois at UrbanaChampaign  2/12/2012  2/18/2012 
Tijana Milenkovic  University of Notre Dame  2/26/2012  3/2/2012 
John Milnor  SUNY  1/27/2012  2/2/2012 
Tom Milnor  University of British Columbia  1/27/2012  2/1/2012 
Dimitrios Mitsotakis  University of Minnesota  10/27/2010  8/31/2012 
Jack Morava  Johns Hopkins University  1/29/2012  2/2/2012 
Fabien Morel  LudwigMaximiliansUniversität München  1/28/2012  2/2/2012 
Chad Myers  University of Minnesota  2/27/2012  3/2/2012 
Jelani Nelson  Princeton University  2/12/2012  2/17/2012 
Jennifer Neville  Purdue University  2/26/2012  3/2/2012 
Hung Ngo  University at Buffalo (SUNY)  2/12/2012  2/17/2012 
Peter J. Olver  University of Minnesota  1/30/2012  2/1/2012 
Kent Orr  Indiana University  1/29/2012  2/1/2012 
Peter Ozsvath  Massachusetts Institute of Technology  1/29/2012  2/1/2012 
Mary Therese Padberg  University of Iowa  2/12/2012  2/17/2012 
Aditya Pal  University of Minnesota  2/26/2012  3/2/2012 
Hyungju Park  Pohang University of Science and Technology (POSTECH)  1/29/2012  2/1/2012 
Scott Pauls  Dartmouth College  2/26/2012  3/2/2012 
Erik Kjær Pedersen  University of Copenhagen  1/29/2012  2/1/2012 
John Pinney  Imperial College London  2/25/2012  3/1/2012 
Carles Pons  University of Minnesota  2/27/2012  3/2/2012 
Ely Porat  BarIlan University  2/12/2012  2/18/2012 
Candice Renee Price  University of Iowa  8/1/2011  7/31/2012 
Natasha Przulj  Imperial College London  2/26/2012  3/3/2012 
Natasha Przulj  Imperial College London  2/12/2012  2/17/2012 
Teresa M Przytycka  National Center for Biotechnology Information  2/26/2012  3/2/2012 
Karthik Pulivendal  University of Minnesota  1/30/2012  2/1/2012 
Weifeng (Frederick) Qiu  University of Minnesota  8/31/2010  8/30/2012 
Changzheng Qu  University of Minnesota  1/30/2012  2/1/2012 
Anca Ruxandra Radulescu  University of Colorado  1/29/2012  2/1/2012 
Ketan Rajawat  University of Minnesota  2/27/2012  3/2/2012 
Parimala Raman  Emory University  1/29/2012  2/1/2012 
Andrew Ranicki  University of Edinburgh  1/29/2012  2/1/2012 
Ben J. Raphael  Brown University  2/26/2012  3/3/2012 
Holger Rauhut  Rheinische FriedrichWilhelmsUniversität Bonn  2/25/2012  3/17/2012 
Douglas Conner Ravenel  University of Rochester  1/29/2012  2/1/2012 
Victor Reiner  University of Minnesota  1/30/2012  2/1/2012 
Sylvie RicardBlum  Université ClaudeBernard (Lyon I)  2/12/2012  2/17/2012 
Luis Rocha  Indiana University  2/26/2012  3/2/2012 
Jonathan Rogness  University of Minnesota  1/30/2012  2/1/2012 
Dale Preston Odin Rolfsen  University of British Columbia  1/29/2012  2/1/2012 
Xavier Ronaled  University of Minnesota  1/30/2012  2/1/2012 
Frederick Roth  University of Toronto  2/26/2012  3/1/2012 
Lee Rudolph  Clark University  1/29/2012  2/1/2012 
Atri Rudra  University at Buffalo (SUNY)  2/12/2012  2/17/2012 
Derek Ruths  McGill University  2/26/2012  3/2/2012 
Vyacheslav V. Rykov  University of Nebraska  2/12/2012  2/19/2012 
S. Cenk Sahinalp  Simon Fraser University  2/26/2012  3/3/2012 
Venkatesh Saligrama  Boston University  2/12/2012  2/17/2012 
Alex Samorodnitsky  Hebrew University  2/11/2012  2/17/2012 
Sriram Sankararaman  Harvard Medical School  2/12/2012  2/17/2012 
Guillermo R. Sapiro  University of Minnesota  9/1/2011  5/31/2012 
Radmila Sazdanović  University of Pennsylvania  1/29/2012  2/1/2012 
Robert Glenn Scharein  Hypnagogic Software  1/5/2012  2/4/2012 
Alexander Schliep  Rutgers University  2/12/2012  2/17/2012 
Michelle Kristin Schwalbe  National Research Council  2/26/2012  3/2/2012 
George R Sell  University of Minnesota  1/30/2012  2/1/2012 
Roded Sharan  Tel Aviv University  2/26/2012  3/1/2012 
Noam Shental  Open University of Israel  2/12/2012  2/16/2012 
Laurence Carl Siebenmann  Université de Paris XI (ParisSud)  1/29/2012  2/3/2012 
Mona Singh  Princeton University  2/26/2012  2/29/2012 
Steven Sperber  University of Minnesota  1/30/2012  2/1/2012 
Karsten Steinhaeuser  University of Minnesota  2/27/2012  3/2/2012 
Nathalie Stroeymeyt  Université de Lausanne  2/25/2012  3/3/2012 
Karthik Subbian  University of Minnesota  2/27/2012  3/2/2012 
ChiungJue Sung  National Tsing Hua University  1/30/2012  2/1/2012 
Arthur Szlam  University of Minnesota  8/31/2011  8/30/2012 
Vladimir Temlyakov  University of South Carolina  2/1/2012  5/31/2012 
Nicolas ThierryMieg  Centre National de la Recherche Scientifique (CNRS)  2/12/2012  2/17/2012 
Ulrike Tillmann  University of Oxford  1/28/2012  2/1/2012 
Vladimir D Tonchev  Michigan Technological University  2/13/2012  2/18/2012 
Donald Towsley  University of Massachusetts  2/27/2012  3/2/2012 
Masashi Toyoda  University of Tokyo  2/26/2012  3/2/2012 
Victor Turchin  Kansas State University  1/29/2012  2/1/2012 
Eric van den Berg  Telcordia  2/26/2012  3/2/2012 
Benjamin VanderSluis  University of Minnesota  2/27/2012  3/2/2012 
Fabio Vandin  Brown University  2/26/2012  3/2/2012 
Divyanshu Vats  University of Minnesota  8/31/2011  8/30/2012 
Jonathan Wahl  University of North Carolina  1/30/2012  2/1/2012 
Adwait Walimbe  University of Minnesota  1/30/2012  2/1/2012 
Lan Wang  University of Minnesota  1/24/2012  5/12/2012 
Walter Willinger  AT&T Laboratories  Research  2/26/2012  3/2/2012 
David P. Woodruff  IBM Research Division  2/15/2012  2/17/2012 
Mary Wootters  University of Michigan  2/12/2012  2/17/2012 
Zheyang Wu  Worcester Polytechnic Institute  2/12/2012  2/17/2012 
Lingzhou Xue  University of Minnesota  9/1/2011  6/30/2012 
Teng Zhang  University of Minnesota  8/31/2011  8/30/2012 
Ke Zhu  University of Minnesota  1/30/2012  2/1/2012 
Or Zuk  Broad Institute  2/12/2012  2/17/2012 