- talks - lists.cs.princeton.edu

Colloquium Speaker: Dan Boneh, Wed Oct 19, 4:30pm- Reminder
by Nicole E. Wagenblast 18 Oct '16

18 Oct '16

Colloquium Speaker Prof. Dan Boneh, Stanford University Wednesday, October 19, 4:30pm Computer Science 105 Hiding the metadata in chat systems The talk will survey a number of open problems in computer security, and discuss recent progress on communication systems that hide the metadata. We will present a recent system, called Riposte, that uses cryptographic techniques to provide anonymous Tweets for very large anonymity sets. This is joint work with Henry Corrigan-Gibbs and David Mazieres. Dr. Boneh is a Professor of Computer Science at Stanford University where he heads the applied cryptography group and co-directs the computer security lab. Dr. Boneh's research focuses on applications of cryptography to computer security. His work includes cryptosystems with novel properties, security for mobile devices, web security, and cryptanalysis. He is the author of over a 150 publications in the field and is a recipient of the 2014 ACM Infosys award, the 2013 Godel prize, and the Ishii award for education.

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Colloquium Speaker- Ruslan Salakhutdinov, Fri Oct 21, 12:30pm
by Nicole E. Wagenblast 17 Oct '16

17 Oct '16

Colloquium Speaker Ruslan Salakhutdinov, Carnegie Mellon University Friday, October 21, 2016 - 12:30pm Computer Science 105 Learning Multimodal Deep Models Building intelligent systems that are capable of extracting meaningful representations from high-dimensional data lies at the core of solving many Artificial Intelligence tasks, including visual object recognition, information retrieval, speech perception, and language understanding. In this talk I will first introduce a broad class of deep learning models and show that they can learn useful hierarchical representations from large volumes of high-dimensional data with applications in information retrieval, object recognition, and speech perception. I will next introduce deep models that are capable of extracting a unified representation that fuses together multiple data modalities as well as present the Reverse Annealed Importance Sampling Estimator (RAISE) for evaluating these deep generative models. Finally, I will discuss models that can generate natural language descriptions (captions) of images, as well as generate images from captions using attention mechanism. I will show that on several tasks, including modelling images and text, these models significantly improve upon many of the existing techniques. Ruslan Salakhutdinov received his PhD in computer science from the University of Toronto in 2009. After spending two post-doctoral years at the Massachusetts Institute of Technology Artificial Intelligence Lab, he joined the University of Toronto as an Assistant Professor in the Departments of Statistics and Computer Science. In 2016 he joined the Machine Learning Department at Carnegie Mellon University as an Associate Professor. Ruslan's primary interests lie in deep learning, machine learning, and large-scale optimization. He is an action editor of the Journal of Machine Learning Research and served on the senior programme committee of several learning conferences including NIPS and ICML. He is an Alfred P. Sloan Research Fellow, Microsoft Research Faculty Fellow, Canada Research Chair in Statistical Machine Learning, a recipient of the Early Researcher Award, Google Faculty Award, Nvidia's Pioneers of AI award, and is a Senior Fellow of the Canadian Institute for Advanced Research.

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Colloquium Speaker: Dan Boneh, Wed Oct 19, 4:30pm
by Nicole E. Wagenblast 13 Oct '16

13 Oct '16

Colloquium Speaker Prof. Dan Boneh, Stanford University Wednesday, October 19, 4:30pm Computer Science 105 Hiding the metadata in chat systems The talk will survey a number of open problems in computer security, and discuss recent progress on communication systems that hide the metadata. We will present a recent system, called Riposte, that uses cryptographic techniques to provide anonymous Tweets for very large anonymity sets. This is joint work with Henry Corrigan-Gibbs and David Mazieres. Dr. Boneh is a Professor of Computer Science at Stanford University where he heads the applied cryptography group and co-directs the computer security lab. Dr. Boneh's research focuses on applications of cryptography to computer security. His work includes cryptosystems with novel properties, security for mobile devices, web security, and cryptanalysis. He is the author of over a 150 publications in the field and is a recipient of the 2014 ACM Infosys award, the 2013 Godel prize, and the Ishii award for education.

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Colloquium Speaker: Tandy Warnow, Today, 4:30pm
by Nicole E. Wagenblast 05 Oct '16

05 Oct '16

Colloquium Speaker Tandy Warnow, University of Illinois Wednesday, October 5, 2016 - 4:30pm Computer Science 105 Grand Challenges in Phylogenomics Estimating the Tree of Life will likely involve a two-step procedure, where in the first step trees are estimated on many genes, and then the gene trees are combined into a tree on all the taxa. However, the true gene trees may not agree with with the species tree due to biological processes such as deep coalescence, gene duplication and loss, and horizontal gene transfer. Statistically consistent methods based on the multi-species coalescent model have been developed to estimate species trees in the presence of incomplete lineage sorting; however, the relative accuracy of these methods compared to the usual "concatenation" approach is a matter of substantial debate within the research community. In this talk I will present new state of the art methods (Statistical Binning, Science 2014, ASTRAL ECCB 2014 and ISMB 2015) we have developed for estimating species trees in the presence of incomplete lineage sorting (ILS), and show how they can be used to estimate species trees from genome-scale datasets. Tandy Warnow is the Founder Professor of Engineering at the University of Illinois at Urbana-Champaign. She has a dual appointment between Computer Science and Bioengineering, and is a member of the Carl R. Woese Institute for Genomic Biology, a member of the National Center for Supercomputing Applications, and an affiliate in six other departments at UIUC (Statistics, Mathematics, Electrical and Computer Engineering, Plant Biology, Animal Biology, and Entomology). Tandy received her PhD in Mathematics at UC Berkeley under the direction of Gene Lawler, and did postdoctoral training with Simon Tavaré and Michael Waterman at the University of Southern California. She received the National Science Foundation Young Investigator Award in 1994, the David and Lucile Packard Foundation Award in Science and Engineering in 1996, an Emeline Bigelow Conland Fellowship at the Radcliffe Institute for Advanced Study in 2006, a Guggenheim Foundation Fellowship for 2011, and was elected an ACM Fellow in 2016. Her research combines mathematics, computer science, and statistics to develop improved models and algorithms for reconstructing complex and large-scale evolutionary histories in both biology and historical linguistics. Her current research focuses on phylogeny and alignment estimation for very large datasets (10,000 to 1,000,000 sequences), estimating species trees from collections of gene trees, and metagenomics. Overall, Tandy has published more than 130 papers in the area of computational molecular biology. _______________________________________________ talks mailing list talks(a)lists.cs.princeton.edu To edit subscription settings or remove yourself, use this link: https://lists.cs.princeton.edu/mailman/listinfo/talks

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Naga Katta will present his FPO "Building Efficient and Reliable Software-Defined Networks" on Tuesday, 10/11/2016 at 10 am in CS 402.
by Nicki Gotsis 04 Oct '16

04 Oct '16

Naga Katta will present his FPO "Building Efficient and Reliable Software-Defined Networks" on Tuesday, 10/11/2016 at 10 am in CS 402. The members of his committee are: Jennifer Rexford (adviser); David Walker and Michael Freedman (Readers); Nick Feamster and Aarti Gupta (Examiners). A copy of his thesis is available in Room 310. Everyone is invited to attend his talk. The abstract follows below. Software-defined networking (SDN) promises flexible control of computer networks by orchestrating switches in the network dataplane through a centralized controller. However, despite this promise, operators used to fast and fault-tolerant routing using traditional protocols face three important problems while deploying SDN. One, the control plane timescales are too slow to enforce effective load balancing in order to efficiently use the available network capacity. Second, the commodity SDN switches have limited memory to enforce fine-grained policy rules which undermines the promise of flexible control. Third, the centralized controller itself is a single point of failure which is unacceptable for operators used to running distributed fault-tolerant network protocols. This thesis aims to mitigate these problems using novel algorithms that exploit advanced data plane capabilities and enhancements to the control plane software. At the same time, we also provide simple abstractions on top of these systems so that network operators writing control programs need not worry about low-level details of the underlying implementation mechanisms. First, I will present HULA, which gives the abstraction of one big efficient non-blocking switch. Instead of asking the control plane to choose the best path for each new flow, HULA efficiently routes traffic on least congested paths in the network. HULA uses advanced hardware data plane capabilities to infer global congestion information and uses that information to do fine-grained load balancing at RTT timescales. HULA is congestion-aware, scales to large topologies and is robust to topology failures. Second, I will present CacheFlow which helps enforcing fine-grained policies by proposing the abstraction of a switch with logically infinite rule space. CacheFlow uses a combination of software and hardware data paths to bring the best of both worlds to policy enforcement. By dynamically caching a small number of heavy hitting rules in the hardware switch and the rest of the rules in the software data path, it achieves both high throughiii put and high rule capacity. Since cross-rule dependencies make rule caching difficult, CacheFlow uses novel algorithms to do dependency-aware, efficient rule caching in a way transparent to control applications . Finally, I will present Ravana which gives the abstraction of one logically centralized controller. Given this abstraction, the network operator only writes programs for one controller and the Ravana runtime takes care of replicating the control logic for fault-tolerance. Since network switches carry additional state external to the controller state, Ravana uses an enhanced version of traditional replicated state machine protocols to ensure ordered and exactly-once execution of network events. Together these systems propose a new SDN paradigm where basic routing is done effi- ciently at dataplane timescales, policy enforcement is done scalably with the help of software data planes and the control plane is fault-tolerant. This new architecture has the properties of fast routing and fault-tolerance of traditional networks while delivering the promise of efficient enforcement of fine-grained control policies.

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PICSciE-Research Computing Education, Training, and Outreach Program - Fall 2016
by Chris M. Miller 03 Oct '16

03 Oct '16

See below for training and other upcoming events this Fall from PICSciE / Research Computing. -------- Original message -------- From: "Ma. Florevel C. Fusin-Wischusen" <floe(a)PRINCETON.EDU> Date: 9/7/16 3:50 PM (GMT-05:00) To: PICSciE(a)Princeton.EDU Subject: PICSciE-Research Computing Education, Training, and Outreach Program - Fall 2016 Mini-Courses, Tutorials and Workshops Registration is required at the Training site. 1 . Introduction to Programming Using Python by Matthew Cahn There are four different sections. Participants sign up for one of the sections; each section meets twice. Section I — Two Mondays, Sept. 26 and Oct. 3, 3:00-4:30pm Section II — Two Tuesdays, Sept. 27 and Oct. 4, 3:00-4:30pm Section III — Two Wednesdays, Sept. 28 and Oct. 5, 3:00-4:30pm Section IV — Two Thursdays, Sept. 29 and Oct. 6, 3:00-4:30pm Venue: Lewis Thomas Laboratory Room 005 2. Performance Tuning & Optimization for Beginners: A Practical Tutorial on How to Make Your Code Run Faster by Ian Cosden Wednesday, October, 12, 10:30-2:30pm, Princeton Center for Theoretical Science, 407 Jadwin Hall 3. Continuous Integration in Scientific Software Development with Git and Jenkins by David Luet Thursday, October 13, 10:30am-12:00pm, Princeton Center for Theoretical Science, 407 Jadwin Hall 4. Python Programming Techniques by Eliot Feibush Wednesday, October 19, 2:00-3:30pm, Digital Learning Lab, 130 Lewis Library 5. Fundamentals of Performance Tuning for Python Applications by Alexey Svyatkovskiy Tuesday, October 25, 10:00-4:00pm, Princeton Center for Theoretical Science, 407 Jadwin Hall 6. Introduction to Big Data with Apache Spark by Alexey Svyatkovskiy Friday, October 21, 10:00-4:30pm (Beginners), Frist MPR C Thursday, October 27, 10:00-4:30pm (Advanced), Frist MPR B 7. Introduction to Parallel Programming with MPI and OpenMP in C/C++ by Ian Cosden Tuesday & Wednesday, November 1 & 2, 10:00-4:00pm, Princeton Center for Theoretical Science, 407 Jadwin Hall 8. Introduction to Debugging with the Allinea DDT Advanced Debugger by Stephane Ethier Tuesday, December 6, 2:00-4:00pm, Visualization Lab, 346 Lewis Library 9. Scientific Visualization by Eliot Feibush Wednesday, December 7, 2:00-3:30pm, Digital Learning Lab, 130 Lewis Library 10. Geographic Information System (GIS) Workshops by William Guthe and Wangyal Shawa The classes will be held in 225 Lewis Library Electronic Classroom from 1:30 to 3:00pm. 11. Advanced Networking, Date & Location TBD To subscribe to upcoming PICSciE-Research Computing events and workshops, click here . Other Events • Princeton Speaks MATLAB Wednesday, September 28, 4:30 - 7:30pm, 120 Lewis Science Library, Washington Road & Ivy Lane • Research Computing Day Friday, October 14, 8:30 am – 5:30 pm Maeder Hall Auditorium, Andlinger Center Graduate Certificate in Computational and Information Science (The information session in October will be announced soon.) Online application is on-going throughout the year. More details are available at http://www.princeton.edu/researchcomputing/education/graduate-certificate-C… . Outreach 1. Help Sessions • Research Computing Weekly Help Session - Tuesdays, 10:00-11:00am, 245 Lewis Library • Visualization & Research Computing Weekly Help Session - Thursdays, 2:00-3:00pm, 245 Lewis Library 2. High Performance Computing Research Center (HPCRC) Tours • Monday, September 26, 4:00-5:30pm • Thursday, October 20, 4:00-5:30pm Please contact alrubins(a)princeton.edu to register. 3. Scientific Computing/Supercomputing Administrators Meeting (SCAM) First Tuesdays, 2:00-3:00pm 4. User Groups • Python user group (Princetonpy) – The schedule for the bi-monthly presentations will be announced soon. • MATLAB – Additional information on upcoming events will be available soon. 5. High Performance Computing Research Center (HPCRC) Tours • Monday, September 26 th , 4:00-5:30pm • Thursday, October 20 th , 4:00-5:30pm Two tours will be offered. A van will take you over to 151 Forrestal Road for the one-hour long tour and then drop back on campus. Each tour will be limited to 10 people. Please assemble in front of the Lewis Science Library (Washington Road and Ivy Lane) promptly at the time of each tour. Please contact Andrea Rubinstein at alrubins(a)princeton.edu to register. More information on other PICSciE-Research Computing events is available at www.princeton.edu/researchcomputing . To subscribe to upcoming PICSciE-Research Computing events and workshops, click here . Ma. Florevel (Floe) Fusin-Wischusen Princeton Institute for Computational Science & Engineering (PICSciE) 335 Peter B. Lewis Library (609) 258-8071 www.princeton.edu/researchcomputing

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The First Annual Research Computing Day - October 14 - Maeder Hall Auditorium, Andlinger Center
by Chris M. Miller 03 Oct '16

03 Oct '16

The First Annual Research Computing Day Friday • October 14, 2016 8:00 am – 5:30 pm Maeder Hall Auditorium • Andlinger Center • 86 Olden Street The Princeton Institute for Computational Science & Engineering ( PICSciE ) is hosting its first Annual Research Computing Day to showcase computational and data-intensive research by graduate students and postdocs from all disciplines as well as understand research computing support, services and infrastructure available to Princeton researchers. This event is open to undergraduate and graduate students, postdocs, researchers, faculty and technical staff at Princeton and its affiliates. There will be 20-minute presentations by graduate students and postdocs plus talks by PICSciE and OIT-Research Computing staff, poster sessions and open discussions during the event. A buffet lunch and reception after the event will be held in the Andlinger Center’s courtyard. Organized and sponsored by the Princeton Institute for Computational Science & Engineering. Co-sponsored by the Office of Information Technology’s Research Computing department, the Office of the Dean for Research and the Center for Statistics and Machine Learning. Register now Call for Oral and Poster Presentations Schedule of Events www.princeton.edu/researchcomputing/events/research-computing-day Questions? Email floe(a)princeton.edu

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Colloquium Speaker: Tandy Warnow, Wed Oct 5, 12:30pm
by Nicole E. Wagenblast 03 Oct '16

03 Oct '16

Colloquium Speaker Tandy Warnow, University of Illinois Wednesday, October 5, 2016 - 4:30pm Computer Science 105 Grand Challenges in Phylogenomics Estimating the Tree of Life will likely involve a two-step procedure, where in the first step trees are estimated on many genes, and then the gene trees are combined into a tree on all the taxa. However, the true gene trees may not agree with with the species tree due to biological processes such as deep coalescence, gene duplication and loss, and horizontal gene transfer. Statistically consistent methods based on the multi-species coalescent model have been developed to estimate species trees in the presence of incomplete lineage sorting; however, the relative accuracy of these methods compared to the usual "concatenation" approach is a matter of substantial debate within the research community. In this talk I will present new state of the art methods (Statistical Binning, Science 2014, ASTRAL ECCB 2014 and ISMB 2015) we have developed for estimating species trees in the presence of incomplete lineage sorting (ILS), and show how they can be used to estimate species trees from genome-scale datasets. Tandy Warnow is the Founder Professor of Engineering at the University of Illinois at Urbana-Champaign. She has a dual appointment between Computer Science and Bioengineering, and is a member of the Carl R. Woese Institute for Genomic Biology, a member of the National Center for Supercomputing Applications, and an affiliate in six other departments at UIUC (Statistics, Mathematics, Electrical and Computer Engineering, Plant Biology, Animal Biology, and Entomology). Tandy received her PhD in Mathematics at UC Berkeley under the direction of Gene Lawler, and did postdoctoral training with Simon Tavaré and Michael Waterman at the University of Southern California. She received the National Science Foundation Young Investigator Award in 1994, the David and Lucile Packard Foundation Award in Science and Engineering in 1996, an Emeline Bigelow Conland Fellowship at the Radcliffe Institute for Advanced Study in 2006, a Guggenheim Foundation Fellowship for 2011, and was elected an ACM Fellow in 2016. Her research combines mathematics, computer science, and statistics to develop improved models and algorithms for reconstructing complex and large-scale evolutionary histories in both biology and historical linguistics. Her current research focuses on phylogeny and alignment estimation for very large datasets (10,000 to 1,000,000 sequences), estimating species trees from collections of gene trees, and metagenomics. Overall, Tandy has published more than 130 papers in the area of computational molecular biology.

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Reminder about Matthias Niessner's talk today at 1:30PM in CS 302
by Thomas Funkhouser 30 Sep '16

30 Sep '16

Title: Interactive 3D: Static and Dynamic Environment Capture in Real Time Speaker: Matthias Niessner Affiliation: Stanford University Time: Friday Sept 30, 1:30-2:30PM Place: Room CS 302 In recent years, commodity 3D sensors have become easily and widely available. These advances in sensing technology have inspired significant interest in using captured 3D data for mapping and understanding 3D environments. In this talk, I will give an overview of how we can now easily obtain 3D reconstructions of static and dynamic environments in an interactive manner, and how we can process and utilize the data efficiently in real time on modern graphics hardware. More concretely, as an example application for 3D reconstruction, I will talk about facial reenactment (Face2Face), where we use an intermediate 3D reconstruction to interactively edit videos in real time. Last but not least, I will talk about the real-time optimization strategies used in the aforementioned problems, from which have developed 'Opt', a domain-specific language that automates the implementation of non-linear-least-squares from an abstract energy formulations to parallel hardware. This talk is going to be very fun. All are welcome.

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Talk: Prof. Yunhao Liu, Friday, September 30, 10am
by Nicole E. Wagenblast 30 Sep '16

30 Sep '16

Title: On Large Scale Sensor Network and Internet of Things Date: 10:00 AM ~ 11:00AM, 30, September, 2016 (CS402) Speaker: Prof. Yunhao Liu (Tsinghua University), hosted by Prof. Kyle Jamieson Abstract: Yunhao started working on IoT and Sensor Network since early 2000. In the past years, he and his team deployed the world first working sensor network system in the D. L. Coal Mine, the world second largest coal mine, one of the world earliest RFID localization systems called LANDMARC. They implemented the GreenOrbs prototype system in the campus woodland of Zhejiang Forestry University with 330 sensor nodes and each node with several sensors. The system scale reached 400 in April 2010 . Later, the Tianmu Mountain deployment includes 200 nodes and was in continuous operation since August 2009 and lasted for more than three years. The deployment area is around 200,000 square meters. From 2011 through 2016, Yunhao and his team conduct TagSys system in the Beijing International Airport and more than 100 thousand RFID tags are used. The resulted publication was awarded MobiCom 2014 Best Paper. In this talk, he is going to share the experience learned from large scale Sensor Network and IoT system deployments, and also discuss the concept Sensorless Sensing they proposed. Bio: Yunhao Liu, Cheung Kong Professor and Dean of School of Software at Tsinghua University, China. Being an ACM Fellow and an IEEE Fellow, Yunhao serves as the Chair of ACM China Council and also the Associate Editor for IEEE/ACM Transactions on Networking and ACM Transactions on Sensor Network. Yunhao was the Associate Editor-in-Chief for IEEE Transactions on Parallel and Distributed Systems from 2011 through 2014. He served as TPC member for many leading conferences such as ACM MobiCom, IEEE INFOCOM, and PC Co-Chair/Vice Co-Chair for IEEE ICDCS, IEEE MASS, IEEE ICPADS and etc. He was also General Co-Chair for IEEE RTAS 2012, WASA 2010, and Vice General Chair for WWW 2008. Yunhao has published more than 120 papers and received many best paper awards like ACM MobiCom 2014 Best Paper Award, IEEE DCOSS 2011 Best Paper Award, and IEEE ICPADS 2009 Best Paper Award. He also received many prestigious awards including ACM Presidential Award 2012, China National Natural Science Award 2011, and China National Distinguished Young Scholar Award 2011. Yunhao Liu received the BS degree in automation from Tsinghua University, China, in 1995, the MS and PhD degrees in computer science and engineering from Michigan State University, USA, in 2003 and 2004, respectively. He was Assistant Professor and Associate Professor in the Hong Kong University of Science and Technology from 2004-2010, and Joined Tsinghua University as Professor in 2011. His research interests include RFID and sensor network, the Internet and P2P&Cloud Computing. Nicole Wagenblast Computer Science Department Princeton University 35 Olden Street Princeton, NJ 08540 609-258-4624

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