September 2016 - talks - lists.cs.princeton.edu

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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Talk: Prof. Mo Li, Thursday, Sept 29, 10am
by Nicole E. Wagenblast 27 Sep '16

27 Sep '16

Title: Smart City: Research Experiences in Smart Traffic Monitoring Date: 10:00 AM ~ 11:00AM, 29, September, 2016 (CS402) Speaker: Prof. Mo Li (Nanyang Technological University), hosted by Prof. Kyle Jamieson Abstract: The rapid development of technologies in sensing, wireless communication, IoT, etc. has made it possible to build a smart and connected environment of systems, objects, data, and people for a better living in the city. This talk will introduce my research experiences in developing key IoT techniques to support smart city applications, in particular building a smart traffic monitoring system for the city of Singapore. With the help of the location reports from ~12000 taxis, we are able to provide accurate traffic estimation for the city’s road segments in real time. We further develop a crowdsensing system to derive the traffic conditions that compliment the estimation from taxis data. Bio: Mo Li received his BS degree in the Department of Computer Science and Technology from Tsinghua University and PhD degree in the Department of Computer Science and Engineering from Hong Kong University of Science and Technology. He is currently an associate professor in School of Computer Engineering of Nanyang Technological University, Singapore.

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Colloquium Speaker: Frank Pfenning -Today
by Nicole E. Wagenblast 26 Sep '16

26 Sep '16

Colloquium Speaker Professor Frank Pfenning, Carnegie Mellon University Monday, September 26th, 12:30pm Computer Science 105 Design and Implementation of a Freshman Algorithms Course with Contracts We provide an overview of the introductory computer science curriculum at Carnegie Mellon University and then provide some detail about its perhaps most unusual component: a first-semester freshman-level course on imperative programming, algorithms, data structures, and computational thinking. A key aspect of this course is its use of C0, a small safe subset of C augmented with a language for expressing contracts that capture pre- and post-conditions as well as loop and data structure invariants. We provide some sample lecture material and report on our experience with this course over the last six years. Frank Pfenning studied Mathematics and Computer Science at the Technical University Darmstadt and then left for Carnegie Mellon University on a Fulbright scholarship where he obtained his Ph.D. in Mathematics in 1987 under the supervision of Professor Peter Andrews. He subsequently joined the Department of Computer Science at Carnegie Mellon University as research faculty where he became Professor in 2002 and served as Director of Graduate Programs from 2004 to 2008 and Associate Dean for Graduate Education from 2009 to 2010. He was appointed Head of the Computer Science Department in January 2013 and the Joseph F. Traub Professor of Computer Science in October 2015. He has spent time as visiting scientist at the Max-Planck-Institute for Computer Science in Saarbrücken, as Alexander-von-Humboldt fellow at the Technical University Darmstadt, and as visiting professor at École Polytechnique and INRIA-Futurs. He has advised 24 completed Ph.D. theses and won the Herbert A. Simon Award for Teaching Excellence in the School of Computer Science in 2002. He served as trustee, vice president, and president of CADE, Inc., the governing body of the International Conference on Automated Deduction, and on advisory boards for INRIA, the Max-Planck-Institute for Computer Science, and Seoul National University. He has chaired several conferences and program committees, including CADE and LICS, and has been a member of the editorial boards for Theoretical Computer Science, Journal of Automated Reasoning, and the Journal of Symbolic Computation. He was named Fellow of the ACM in 2015. His research interests include programming languages, logic and type theory, logical frameworks, automated deduction, and computer security. In his spare time he enjoys playing squash, running, hiking, cooking, and reading.

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Invited talk by Matthias Niessner on Friday Sept 30
by Thomas Funkhouser 25 Sep '16

25 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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Colloquium Speaker: Frank Pfenning tomorrow, 12:30pm
by Nicole E. Wagenblast 25 Sep '16

25 Sep '16

Colloquium Speaker Professor Frank Pfenning, Carnegie Mellon University Monday, September 26th, 12:30pm Computer Science 105 Design and Implementation of a Freshman Algorithms Course with Contracts We provide an overview of the introductory computer science curriculum at Carnegie Mellon University and then provide some detail about its perhaps most unusual component: a first-semester freshman-level course on imperative programming, algorithms, data structures, and computational thinking. A key aspect of this course is its use of C0, a small safe subset of C augmented with a language for expressing contracts that capture pre- and post-conditions as well as loop and data structure invariants. We provide some sample lecture material and report on our experience with this course over the last six years. Frank Pfenning studied Mathematics and Computer Science at the Technical University Darmstadt and then left for Carnegie Mellon University on a Fulbright scholarship where he obtained his Ph.D. in Mathematics in 1987 under the supervision of Professor Peter Andrews. He subsequently joined the Department of Computer Science at Carnegie Mellon University as research faculty where he became Professor in 2002 and served as Director of Graduate Programs from 2004 to 2008 and Associate Dean for Graduate Education from 2009 to 2010. He was appointed Head of the Computer Science Department in January 2013 and the Joseph F. Traub Professor of Computer Science in October 2015. He has spent time as visiting scientist at the Max-Planck-Institute for Computer Science in Saarbrücken, as Alexander-von-Humboldt fellow at the Technical University Darmstadt, and as visiting professor at École Polytechnique and INRIA-Futurs. He has advised 24 completed Ph.D. theses and won the Herbert A. Simon Award for Teaching Excellence in the School of Computer Science in 2002. He served as trustee, vice president, and president of CADE, Inc., the governing body of the International Conference on Automated Deduction, and on advisory boards for INRIA, the Max-Planck-Institute for Computer Science, and Seoul National University. He has chaired several conferences and program committees, including CADE and LICS, and has been a member of the editorial boards for Theoretical Computer Science, Journal of Automated Reasoning, and the Journal of Symbolic Computation. He was named Fellow of the ACM in 2015. His research interests include programming languages, logic and type theory, logical frameworks, automated deduction, and computer security. In his spare time he enjoys playing squash, running, hiking, cooking, and reading.

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Colloquium Speaker: Frank Pfenning Monday, September 26th
by Nicole E. Wagenblast 20 Sep '16

20 Sep '16

Colloquium Speaker Professor Frank Pfenning, Carnegie Mellon University Monday, September 26th, 12:30pm Computer Science 105 Design and Implementation of a Freshman Algorithms Course with Contracts We provide an overview of the introductory computer science curriculum at Carnegie Mellon University and then provide some detail about its perhaps most unusual component: a first-semester freshman-level course on imperative programming, algorithms, data structures, and computational thinking. A key aspect of this course is its use of C0, a small safe subset of C augmented with a language for expressing contracts that capture pre- and post-conditions as well as loop and data structure invariants. We provide some sample lecture material and report on our experience with this course over the last six years. Frank Pfenning studied Mathematics and Computer Science at the Technical University Darmstadt and then left for Carnegie Mellon University on a Fulbright scholarship where he obtained his Ph.D. in Mathematics in 1987 under the supervision of Professor Peter Andrews. He subsequently joined the Department of Computer Science at Carnegie Mellon University as research faculty where he became Professor in 2002 and served as Director of Graduate Programs from 2004 to 2008 and Associate Dean for Graduate Education from 2009 to 2010. He was appointed Head of the Computer Science Department in January 2013 and the Joseph F. Traub Professor of Computer Science in October 2015. He has spent time as visiting scientist at the Max-Planck-Institute for Computer Science in Saarbrücken, as Alexander-von-Humboldt fellow at the Technical University Darmstadt, and as visiting professor at École Polytechnique and INRIA-Futurs. He has advised 24 completed Ph.D. theses and won the Herbert A. Simon Award for Teaching Excellence in the School of Computer Science in 2002. He served as trustee, vice president, and president of CADE, Inc., the governing body of the International Conference on Automated Deduction, and on advisory boards for INRIA, the Max-Planck-Institute for Computer Science, and Seoul National University. He has chaired several conferences and program committees, including CADE and LICS, and has been a member of the editorial boards for Theoretical Computer Science, Journal of Automated Reasoning, and the Journal of Symbolic Computation. He was named Fellow of the ACM in 2015. His research interests include programming languages, logic and type theory, logical frameworks, automated deduction, and computer security. In his spare time he enjoys playing squash, running, hiking, cooking, and reading.

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Allison Chaney will present her FPO, Computational Methods for Exploring Human Behavior", on Thursday, 9/8/2016 at 3:00pm in CS 402.
by Nicki Gotsis 01 Sep '16

01 Sep '16

Allison Chaney will present her FPO, Computational Methods for Exploring Human Behavior", on Thursday, 9/8/2016 at 3:00pm in CS 402. The members of her committee are David Blei (adviser), readers: David Blei and Barbara Engelhardt; Examiners: David Blei, Elad Hazan, and Brandon Stewart (Sociology). A copy of her thesis is available in Room 310. Everyone is invited to attend her talk. The abstract follows below: Researchers and analysts from many diverse fields are interested in unstructured observations of human behavior; this variety of data is constantly increasing in quantity. In this dissertation, we describe a suite of computational methods to assist investigators in interpreting, organizing, and exploring this data. We develop two Bayesian latent variable models for human-centered applications; specifically, we rely on additive Poisson models, which allow behavior to be associated with various sources of influence. Given observed data, we estimate the posterior distributions of these models with scalable variational inference algorithms. These models and inference algorithms are validated on real-world data. Developing statistical models and corresponding inference algorithms only addresses part of the needs of investigators. Non-technical researchers faced with analyzing large quantities of human behavior data are not able to use the results of inference algorithms without tools to translate estimated posterior distributions into accessible visualizations, browsers, or navigators. We present visualization based on an underlying statistical model as a first-class research problem, and provide principles to guide the construction of these systems. We demonstrate these principles with exploratory tools for two latent variable models. By considering the interplay between developing statistical models and tools for visualization, we are able to develop computational methods that provide for the full needs of investigators interested in exploring human behavior.

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