Curriculum Vitae
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Curriculum Vitae
Curriculum Vitae Prof. Michal Feldman School of Computer Science, Tel-Aviv University Personal Details • Born: Israel, 1976 • Gender: Female • email: [email protected] Education • Ph.D.: Information Management and Systems, University of California at Berkeley, May 2005. Thesis title: Incentives for cooperation in peer-to-peer systems. • B.Sc.: Bar-Ilan University, Computer Science, Summa Cum Laude, June 1999. Academic Positions 2013 - present: Associate Professor, School of Computer Science, Tel-Aviv University, Israel. Associate Professor, School of Business Administration and Center for 2011 - 2013: the Study of Rationality, Hebrew University of Jerusalem, Israel. 2007 - 2011: Senior Lecturer, School of Business Administration and Center for the Study of Rationality, Hebrew University of Jerusalem, Israel. Additional Positions 2011 - 2013: Visiting Researcher (weekly visitor), Microsoft Research New England, Cambridge, MA, USA. 2011 - 2013: Visiting Professor, Harvard School of Engineering and Applied Sciences, Center for Research on Computation and Society, School of Computer Science, Cambridge, MA, USA (Marie Curie IOF program). 2008 - 2011: Senior Researcher (part-time), Microsoft Research in Herzliya, Israel. 2007 - 2013: Member, Center for the Study of Rationality, Hebrew University. 2005 - 2007: Post-Doctoral Fellow (Lady Davis fellowship), Hebrew University, School of Computer Science and Engineering. 2004: Ph.D. Intern, HP Labs, Palo Alto, California, USA. 1 Grants (Funding ID) • European Research Council (ERC) Starting Grant: \Algorithmic Mechanism Design - Beyond Truthfulness": 1.4 million Euro, 2013-2017. • FP7 Marie Curie International Outgoing Fellowship (IOF): \Innovations in Algorithmic Game Theory" (IAGT): 313,473 Euro, 2011-2014. • Israel Science Foundation (ISF) grant. \Equilibria Under Coalitional Covenants in Non-Cooperative Games - Existence, Quality and Computation:" 688,000 NIS (172,000 NIS /year), 2009-2013. -
Limitations and Possibilities of Algorithmic Mechanism Design By
Incentives, Computation, and Networks: Limitations and Possibilities of Algorithmic Mechanism Design by Yaron Singer A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Computer Science in the Graduate Division of the University of California, Berkeley Committee in charge: Professor Christos Papadimitriou, Chair Professor Shachar Kariv Professor Scott Shenker Spring 2012 Incentives, Computation, and Networks: Limitations and Possibilities of Algorithmic Mechanism Design Copyright 2012 by Yaron Singer 1 Abstract Incentives, Computation, and Networks: Limitations and Possibilities of Algorithmic Mechanism Design by Yaron Singer Doctor of Philosophy in Computer Science University of California, Berkeley Professor Christos Papadimitriou, Chair In the past decade, a theory of manipulation-robust algorithms has been emerging to address the challenges that frequently occur in strategic environments such as the internet. The theory, known as algorithmic mechanism design, builds on the foundations of classical mechanism design from microeconomics and is based on the idea of incentive compatible pro- tocols. Such protocols achieve system-wide objectives through careful design that ensures it is in every agent's best interest to comply with the protocol. As it turns out, however, implementing incentive compatible protocols as advocated in classical mechanism design the- ory often necessitates solving intractable problems. To address this, algorithmic mechanism design focuses on designing -
120421-24Recombschedule FINAL.Xlsx
Friday 20 April 18:00 20:00 REGISTRATION OPENS in Fira Palace 20:00 21:30 WELCOME RECEPTION in CaixaForum (access map) Saturday 21 April 8:00 8:50 REGISTRATION 8:50 9:00 Opening Remarks (Roderic GUIGÓ and Benny CHOR) Session 1. Chair: Roderic GUIGÓ (CRG, Barcelona ES) 9:00 10:00 Richard DURBIN The Wellcome Trust Sanger Institute, Hinxton UK "Computational analysis of population genome sequencing data" 10:00 10:20 44 Yaw-Ling Lin, Charles Ward and Steven Skiena Synthetic Sequence Design for Signal Location Search 10:20 10:40 62 Kai Song, Jie Ren, Zhiyuan Zhai, Xuemei Liu, Minghua Deng and Fengzhu Sun Alignment-Free Sequence Comparison Based on Next Generation Sequencing Reads 10:40 11:00 178 Yang Li, Hong-Mei Li, Paul Burns, Mark Borodovsky, Gene Robinson and Jian Ma TrueSight: Self-training Algorithm for Splice Junction Detection using RNA-seq 11:00 11:30 coffee break Session 2. Chair: Bonnie BERGER (MIT, Cambrige US) 11:30 11:50 139 Son Pham, Dmitry Antipov, Alexander Sirotkin, Glenn Tesler, Pavel Pevzner and Max Alekseyev PATH-SETS: A Novel Approach for Comprehensive Utilization of Mate-Pairs in Genome Assembly 11:50 12:10 171 Yan Huang, Yin Hu and Jinze Liu A Robust Method for Transcript Quantification with RNA-seq Data 12:10 12:30 120 Zhanyong Wang, Farhad Hormozdiari, Wen-Yun Yang, Eran Halperin and Eleazar Eskin CNVeM: Copy Number Variation detection Using Uncertainty of Read Mapping 12:30 12:50 205 Dmitri Pervouchine Evidence for widespread association of mammalian splicing and conserved long range RNA structures 12:50 13:10 169 Melissa Gymrek, David Golan, Saharon Rosset and Yaniv Erlich lobSTR: A Novel Pipeline for Short Tandem Repeats Profiling in Personal Genomes 13:10 13:30 217 Rory Stark Differential oestrogen receptor binding is associated with clinical outcome in breast cancer 13:30 15:00 lunch break Session 3. -
Satisfiability and Evolution
2014 IEEE Annual Symposium on Foundations of Computer Science Satisfiability and Evolution Adi Livnat Christos Papadimitriou Aviad Rubinstein Department of Biological Sciences Computer Science Division Computer Science Division Virginia Tech. University of California at Berkeley University of California at Berkeley [email protected] [email protected] [email protected] Gregory Valiant Andrew Wan Computer Science Department Simons Institute Stanford University University of California at Berkeley [email protected] [email protected] Abstract—We show that, if truth assignments on n variables genes are able to efficiently arise in polynomial populations reproduce through recombination so that satisfaction of a par- with recombination. In the standard view of evolution, a ticular Boolean function confers a small evolutionary advan- variant of a particular gene is more likely to spread across tage, then a polynomially large population over polynomially many generations (polynomial in n and the inverse of the initial a population if it makes its own contribution to the overall satisfaction probability) will end up almost surely consisting fitness, independent of the contributions of variants of other exclusively of satisfying truth assignments. We argue that this genes. How can complex, multi-gene traits spread in a theorem sheds light on the problem of the evolution of complex population? This may seem to be especially problematic adaptations. for multi-gene traits whose contribution to fitness does not Keywords-evolution; algorithms; Boolean functions decompose into small additive components associated with each gene variant —traits with the property that even if I. INTRODUCTION one gene variant is different from the one that is needed The TCS community has a long history of applying its for the right combination, there is no benefit, or even a net perspectives and tools to better understand the processes negative benefit. -
A Decade of Lattice Cryptography
Full text available at: http://dx.doi.org/10.1561/0400000074 A Decade of Lattice Cryptography Chris Peikert Computer Science and Engineering University of Michigan, United States Boston — Delft Full text available at: http://dx.doi.org/10.1561/0400000074 Foundations and Trends R in Theoretical Computer Science Published, sold and distributed by: now Publishers Inc. PO Box 1024 Hanover, MA 02339 United States Tel. +1-781-985-4510 www.nowpublishers.com [email protected] Outside North America: now Publishers Inc. PO Box 179 2600 AD Delft The Netherlands Tel. +31-6-51115274 The preferred citation for this publication is C. Peikert. A Decade of Lattice Cryptography. Foundations and Trends R in Theoretical Computer Science, vol. 10, no. 4, pp. 283–424, 2014. R This Foundations and Trends issue was typeset in LATEX using a class file designed by Neal Parikh. Printed on acid-free paper. ISBN: 978-1-68083-113-9 c 2016 C. Peikert All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, mechanical, photocopying, recording or otherwise, without prior written permission of the publishers. Photocopying. In the USA: This journal is registered at the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923. Authorization to photocopy items for in- ternal or personal use, or the internal or personal use of specific clients, is granted by now Publishers Inc for users registered with the Copyright Clearance Center (CCC). The ‘services’ for users can be found on the internet at: www.copyright.com For those organizations that have been granted a photocopy license, a separate system of payment has been arranged. -
6.5 X 11.5 Doublelines.P65
Cambridge University Press 978-0-521-87282-9 - Algorithmic Game Theory Edited by Noam Nisan, Tim Roughgarden, Eva Tardos and Vijay V. Vazirani Copyright Information More information Algorithmic Game Theory Edited by Noam Nisan Hebrew University of Jerusalem Tim Roughgarden Stanford University Eva´ Tardos Cornell University Vijay V. Vazirani Georgia Institute of Technology © Cambridge University Press www.cambridge.org Cambridge University Press 978-0-521-87282-9 - Algorithmic Game Theory Edited by Noam Nisan, Tim Roughgarden, Eva Tardos and Vijay V. Vazirani Copyright Information More information cambridge university press Cambridge, New York,Melbourne, Madrid, Cape Town, Singapore, Sao˜ Paulo, Delhi Cambridge University Press 32 Avenue of the Americas, New York, NY 10013-2473, USA www.cambridge.org Information on this title: www.cambridge.org/9780521872829 C Noam Nisan, Tim Roughgarden, Eva´ Tardos, Vijay V. Vazirani 2007 This publication is in copyright. Subject to statutory exception and to the provisions of relevant collective licensing agreements, no reproduction of any part may take place without the written permission of Cambridge University Press. First published 2007 Printed in the United States of America A catalog record for this book is available from the British Library. Library of Congress Cataloging in Publication Data Algorithmic game theory / edited by Noam Nisan ...[et al.]; foreword by Christos Papadimitriou. p. cm. Includes index. ISBN-13: 978-0-521-87282-9 (hardback) ISBN-10: 0-521-87282-0 (hardback) 1. Game theory. 2. Algorithms. I. Nisan, Noam. II. Title. QA269.A43 2007 519.3–dc22 2007014231 ISBN 978-0-521-87282-9 hardback Cambridge University Press has no responsibility for the persistence or accuracy of URLS for external or third-party Internet Web sites referred to in this publication and does not guarantee that any content on such Web sites is, or will remain, accurate or appropriate. -
Extrachromosomal and Other Mechanisms of Oncogene Amplification in Cancer
Title: Extrachromosomal and other mechanisms of oncogene amplification in cancer Abstract: Increase in the number of copies of tumor promoting (onco-) genes is a hallmark of many cancers, and cancers with copy number amplifications are often associated with poor outcomes. Despite their importance, the mechanisms causing these amplifications are incompletely understood. In this talk, we describe our recent results suggesting that a large faction of amplification is due to formation of extrachromosomal DNA (ecDNA). EcDNA play a critical role in tumor heterogeneity, accelerated cancer evolution, and drug resistance through their unique mechanism of non-chromosomal inheritance. While predominant, ecDNA are not the only mechanism to cause amplification. We also describe recent algorithmic methods required to distinguish ecDNA from other mechanisms including Breakage Fusion Bridge formation, Chromothripsis, and simpler events such as tandem duplications and translocations. The talk is a mix of published and unpublished work, largely in collaboration with Paul Mischel's lab at UCSD. EcDNA was recently recognized as one of the grand challenges of cancer research by Cancer Research UK and the National Cancer Institute. Reading Luebeck, 2020, Verhaak 2019 Biography Vineet Bafna, Ph.D., joined the Computer Science faculty at the University of California, San Diego in 2003, after seven years in the biosciences industry. He received his Ph.D. in computer science from The Pennsylvania State University in 1994 and was an NSF postdoctoral researcher at the Center for Discrete Mathematics and Theoretical Computer Science for two years. From 1996-99, Bafna was a senior investigator at SmithKline Beecham, conducting research on DNA signaling, target discovery and EST assembly. -
Linked Decompositions of Networks and the Power of Choice in Polya Urns
Linked Decompositions of Networks and the Power of Choice in Polya Urns Henry Lin¤ Christos Amanatidisy Martha Sideriz Richard M. Karpx Christos H. Papadimitriou{ October 12, 2007 Abstract balls total, and each arriving ball is placed in the least loaded A linked decomposition of a graph with n nodes is a set of m bins, drawn independently at random with probability of subgraphs covering the n nodes such that all pairs of proportional to load. Our analysis shows that in our new subgraphs intersect; we seek linked decompositions such process, with high probability the bin loads become roughly p 2+² that all subgraphs have about n vertices, logarithmic balanced some time before O(n ) further balls have arrived diameter, and each vertex of the graph belongs to either and stay roughly balanced, regardless of how the initial O(n) one or two subgraphs. A linked decomposition enables balls were distributed, where ² > 0 can be arbitrarily small, many control and management functions to be implemented provided m is large enough. locally, such as resource sharing, maintenance of distributed directory structures, deadlock-free routing, failure recovery 1 Introduction and load balancing, without requiring any node to maintain Throwing balls into bins uniformly at random is well- information about the state of the network outside the known to produce relatively well-balanced occupancies subgraphs to which it belongs. Linked decompositions also with high probability. In contrast, when each new ball is enable e±cient routing schemes with small routing tables, added to a bin selected with probability proportional to which we describe in Section 5. -
UC San Diego Electronic Theses and Dissertations
UC San Diego UC San Diego Electronic Theses and Dissertations Title Computational methods for genome-wide non-coding RNA discovery and analysis Permalink https://escholarship.org/uc/item/5qc2h8tf Author Zhang, Shaojie Publication Date 2007 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA, SAN DIEGO Computational Methods for Genome-Wide Non-Coding RNA Discovery and Analysis A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Computer Science by Shaojie Zhang Committee in charge: Professor Vineet Bafna, Chair Professor Sanjoy Dasgupta Professor Pavel Pevzner Professor Glenn Tesler Professor Steven Wasserman 2007 . Copyright Shaojie Zhang, 2007 All rights reserved. The dissertation of Shaojie Zhang is approved, and it is acceptable in quality and form for publication on micro- ¯lm: Chair University of California, San Diego 2007 iii To my parents. iv TABLE OF CONTENTS Signature Page . iii Dedication . iv Table of Contents . v List of Figures . vii List of Tables . viii Acknowledgements . ix Vita, Publications, and Fields of Study . xi Abstract . xiii 1 Introduction . 1 1.1 Non-coding RNAs . 1 1.2 RNA secondary structure . 4 1.3 The Challenge of ncRNA Discovery and Analysis . 6 1.3.1 RNA Homolog Search . 7 1.3.2 RNA Consensus Folding for ncRNA Discovery . 8 1.4 Dissertation Outline . 9 2 FastR: Fast RNA Search Using Structure-based Filters . 11 2.1 Introduction . 11 2.2 Methods . 14 2.2.1 Strucutre-based Filters . 14 2.2.2 Structure-based Filter Design . 17 2.2.3 Optimal Structure-based Filter Design . -
Sharing Non-Anonymous Costs of Multiple Resources Optimally
Sharing Non-Anonymous Costs of Multiple Resources Optimally Max Klimm∗ Daniel Schmand† July 18, 2018 Abstract In cost sharing games, the existence and efficiency of pure Nash equi- libria fundamentally depends on the method that is used to share the resources’ costs. We consider a general class of resource allocation prob- lems in which a set of resources is used by a heterogeneous set of selfish users. The cost of a resource is a (non-decreasing) function of the set of its users. Under the assumption that the costs of the resources are shared by uniform cost sharing protocols, i.e., protocols that use only lo- cal information of the resource’s cost structure and its users to determine the cost shares, we exactly quantify the inefficiency of the resulting pure Nash equilibria. Specifically, we show tight bounds on prices of stabil- ity and anarchy for games with only submodular and only supermodular cost functions, respectively, and an asymptotically tight bound for games with arbitrary set-functions. While all our upper bounds are attained for the well-known Shapley cost sharing protocol, our lower bounds hold for arbitrary uniform cost sharing protocols and are even valid for games with anonymous costs, i.e., games in which the cost of each resource only depends on the cardinality of the set of its users. 1 Introduction Resource allocation problems are omnipresent in many areas of economics, com- puter science, and operations research with many applications, e.g., in routing, network design, and scheduling. Roughly speaking, when solving these prob- arXiv:1412.4456v2 [cs.GT] 4 Feb 2015 lems the central question is how to allocate a given set of resources to a set of potential users so as to optimize a given social welfare function. -
Pairwise Independence and Derandomization
Pairwise Independence and Derandomization Pairwise Independence and Derandomization Michael Luby Digital Fountain Fremont, CA, USA Avi Wigderson Institute for Advanced Study Princeton, NJ, USA [email protected] Boston – Delft Foundations and TrendsR in Theoretical Computer Science Published, sold and distributed by: now Publishers Inc. PO Box 1024 Hanover, MA 02339 USA Tel. +1-781-985-4510 www.nowpublishers.com [email protected] Outside North America: now Publishers Inc. PO Box 179 2600 AD Delft The Netherlands Tel. +31-6-51115274 A Cataloging-in-Publication record is available from the Library of Congress The preferred citation for this publication is M. Luby and A. Wigderson, Pairwise R Independence and Derandomization, Foundation and Trends in Theoretical Com- puter Science, vol 1, no 4, pp 237–301, 2005 Printed on acid-free paper ISBN: 1-933019-22-0 c 2006 M. Luby and A. Wigderson All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, mechanical, photocopying, recording or otherwise, without prior written permission of the publishers. Photocopying. In the USA: This journal is registered at the Copyright Clearance Cen- ter, Inc., 222 Rosewood Drive, Danvers, MA 01923. Authorization to photocopy items for internal or personal use, or the internal or personal use of specific clients, is granted by now Publishers Inc for users registered with the Copyright Clearance Center (CCC). The ‘services’ for users can be found on the internet at: www.copyright.com For those organizations that have been granted a photocopy license, a separate system of payment has been arranged. -
Call for Papers (Page 1)
CALL FOR PAPERS IEEE Computational Systems Bioinformatics Conference Stanford, CA • August 8-11, 2005 You are invited to submit papers to the 2005 IEEE Computational Systems Bioinformatics Conference (CSB2005). The conference’s goal is to facilitate exchange of ideas and collaborations between computer scientists and biologists by presenting cutting-edge computational biology research findings. Such research has an interdisciplinary character. Computer science and mathematical modeling papers must contain a concise description of the biological problem being solved, and biology papers should show how computation or analysis affects the results. Topics of interest include (but are not limited to): • Microarray Data Analysis • Mathematical and Quantitative Models • MicroRNA and RNAi of Cellular and Multicellular Systems • Pathways, Networks, Systems Biology • Synthetic Biological Systems • Biomedical Applications • Sequence Alignment • Biological Data Visualization • Evolution and Phylogenetics • Protein Structures and Complexes • Functional Genomics • Biological Data Mining • High Performance Bio-computing • Pattern Recognition • Comparative Genomics • Microbial Community Analysis • SNPs and Haplotyping • Promoter Analysis and Discovery Full papers are limited to 12 pages, single-spaced, in 12-point type, including title, abstract (250 words or less), figures, tables, text, and bibliography. The first page should give keywords, authors’ postal and electronic mailing addresses. Papers must not have been previously published and must not be currently under consideration for publication elsewhere. Papers will be submitted electronically in MS Word, postscript or PDF format. This year, the conference will also accept short papers, limited to four pages. These papers should describe new research activity in which a complete set of results may not yet be available. Full and short papers will have 25 and 15 minutes, respectively, of presentation time.