- talks - lists.cs.princeton.edu

Colloquium Speaker: Robert Calderbank, Tues Feb 14, 4:30pm-reminder
by Nicole E. Wagenblast 13 Feb '17

13 Feb '17

Joint talk with CS , PACM , CSML Robert Calderbank, Duke University Tuesday, February 14th- 4:30pm Computer Science 105 In this talk I will explore how data science is changing the way we practice education and research. My title Data+ is that of a ten-week summer research experience offered by the Information Institute at Duke (iiD) in which undergraduates join small project teams, working alongside other teams in a communal environment. They learn how to marshal, analyze, and visualize data, as well as how to communicate with the client sponsoring the project. The 2016 program involved about 70 undergraduate students and 30 graduate student and postdoctoral mentors working on 25 projects. I will describe projects that illuminate different ways in which student centered enquiry can transform university institutions. Our ambition for research is that it impacts society. We used to think of impact as starting with an idea, then developing that idea into a prototype, then turning the prototype into a product, then marketing the product, and so on – it is a long march and the problem with long marches is that most ideas don’t make it. I will describe an example of a different model, one where society is part of the research process. It is a collaboration with Apple on child mental health led by Guillermo Sapiro.

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Colloquium Speaker: Jacob Eisenstein, Thursday, February 16- 12:30pm
by Nicole E. Wagenblast 13 Feb '17

13 Feb '17

Colloquium Speaker Prof. Jacob Eisenstein, Georgia Institute of Technology Thursday, February 16, 12:30pm Computer Science 105 Host: Prof. Elad Hazan Putting language in context: social networks and discourse structures for robust language technology The creation of software that can use and understand natural human language would be a transformative technological advance, enabling computational inference to be brought to bear on the vast stores of knowledge that are encoded only as text. Supervised machine learning approaches have brought this possibility into view, but existing methods rely on annotated datasets that focus overwhelmingly on a narrow set of news texts, while failing to generalize to high-impact application domains such as social media and electronic health records. Human readers and listeners successfully comprehend language under difficult circumstances by relying on various forms of contextual information -- knowing who is speaking, and what they might be trying to say. My research brings this same contextual awareness to automated language processing, using deep learning architectures that are constructed to reflect theoretical ideas from sociolinguistics and discourse semantics. I will describe three applications of this methodology: (1) incorporating sociolinguistic variation into document classification; (2) linking textual references to canonicalized entities; (3) predicting the discourse relations that hold between sentences. I will also briefly describe research that uses computational linguistic analysis to obtain new evidence on sociocultural affinity and influence. Jacob Eisenstein is an Assistant Professor in the School of Interactive Computing at Georgia Tech. He works on statistical natural language processing, focusing on computational sociolinguistics, social media analysis, discourse, and machine learning. He is a recipient of the NSF CAREER Award, a member of the Air Force Office of Scientific Research (AFOSR) Young Investigator Program, and was a SICSA Distinguished Visiting Fellow at the University of Edinburgh. His work has also been supported by the National Institutes for Health, the National Endowment for the Humanities, and Google. Jacob was a Postdoctoral researcher at Carnegie Mellon and the University of Illinois. He completed his Ph.D. at MIT in 2008, winning the George M. Sprowls dissertation award. Jacob's research has been featured in the New York Times, National Public Radio, and the BBC. Thanks to his brief appearance in If These Knishes Could Talk, Jacob has a Bacon number of 2.

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Cyber-Physical Systems in Aerospace Engineering
by Scott Karlin 11 Feb '17

11 Feb '17

Cyber-Physical Systems in Aerospace Engineering Eric Feron, Georgia Institute of Technology Monday, February 13, 2017, 3:30pm EQUAD Rm J223 The Cyber-Physical Systems (CPS) of today are, in principle, no different from the controlled systems of yesterday. However, what justifies the new name, especially in Aerospace Engineering, is the spectacular increase in available embedded computing power allowing the systems to offer a vastly expanded range of functionalities. In addition, the safety-critical or mission-critical nature of anything that aerospace engineering builds makes it very important that the systems be verified and validated every step of the way from concept to operation. However, on the one hand, software verification and validation (V&V) alone has been reported to burn in excess of 50% of the B787's development budget. On the other hand, the proponents of novel air vehicles, such as Amazon, Google, Zee, or A^3 by Airbus group, challenge the high cost of CPS development and would like to see a "lite" V&V approved by certification agencies. This talk will concentrate on the basic principles of Aerospace CPS development, indicating the traditional way such systems are specified, built, verified, and validated. The author's specific attempts at addressing the high cost of V&V, notably credible embedded software synthesis, will be highlighted along the way, but current needs and existing challenges will be equally emphasized, regardless of who ends up meeting them. The difficult question of certifying advanced autonomy algorithms will be discussed, along with the recent solutions proposed by the engineering and policy research community. Eric Feron received the B.S. degree from École Polytechnique, Palaiseau, France, the M.S. degree from the École Normale Supérieure, Paris, France, and the Ph.D. degree from Stanford University, Stanford, CA. He is the Dutton–Ducoffe Professor of Aerospace Software Engineering, Georgia Institute of Technology, Atlanta, GA and a consulting Professor of Applied Mathematics at École Nationale de l’Aviation Civile, Toulouse, France. Prior to that, he was with the faculty of the Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, for 12 years. His former research students are distributed throughout academia, government, and industry. He has published three books and several research papers. His research interests include using fundamental concepts of control systems, optimization, and computer science to address important problems in aerospace engineering such as agile control of unmanned aerial vehicles and multi-agent operations in air transportation systems, and aerospace cyber-physical system certification.

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Colloquium Speaker: Robert Calderbank, Tues Feb 14, 4:30pm
by Nicole E. Wagenblast 08 Feb '17

08 Feb '17

Joint talk with CS , PACM , CSML Robert Calderbank, Duke University Tuesday, February 14th- 4:30pm Computer Science 105 In this talk I will explore how data science is changing the way we practice education and research. My title Data+ is that of a ten-week summer research experience offered by the Information Institute at Duke (iiD) in which undergraduates join small project teams, working alongside other teams in a communal environment. They learn how to marshal, analyze, and visualize data, as well as how to communicate with the client sponsoring the project. The 2016 program involved about 70 undergraduate students and 30 graduate student and postdoctoral mentors working on 25 projects. I will describe projects that illuminate different ways in which student centered enquiry can transform university institutions. Our ambition for research is that it impacts society. We used to think of impact as starting with an idea, then developing that idea into a prototype, then turning the prototype into a product, then marketing the product, and so on – it is a long march and the problem with long marches is that most ideas don’t make it. I will describe an example of a different model, one where society is part of the research process. It is a collaboration with Apple on child mental health led by Guillermo Sapiro.

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ORFE Talk: The Implications of Privacy-Aware Choice, Today, 4:30pm
by Nicole E. Wagenblast 07 Feb '17

07 Feb '17

ORFE Colloquium Speaker Rachel Cummings, from California Institute of Technology Tuesday, February 7th- 4:30pm Sherrerd Hall, Room 101 The Implications of Privacy-Aware Choice Privacy concerns are becoming a major obstacle to using data in the way that we want. It's often unclear how current regulations should translate into technology, and the changing legal landscape surrounding privacy can cause valuable data to go unused. In addition, when people know that their current choices may have future consequences, they might modify their behavior to ensure that their data reveal less --- or perhaps, more favorable --- information about themselves. Given these concerns, how can we continue to make use of potentially sensitive data, while providing satisfactory privacy guarantees to the people whose data we are using? Answering this question requires an understanding of how people reason about their privacy and how privacy concerns affect behavior. In this talk, we will see how strategic and human aspects of privacy interact with existing tools for data collection and analysis. I will begin by adapting the standard model of consumer choice theory to a setting where consumers are aware of, and have preferences over, the information revealed by their choices. In this model of privacy-aware choice, I will show that little can be inferred about a consumer's preferences once we introduce the possibility that she has concerns about privacy, even when her preferences are assumed to satisfy relatively strong structural properties. Next, I will analyze how privacy technologies affect behavior in a simple economic model of data-driven decision making. Intuition suggests that strengthening privacy protections will both increase utility for the individuals providing data and decrease usefulness of the computation. I will demonstrate that this intuition can fail when strategic concerns affect consumer behavior. Finally, I'll discuss ongoing behavioral experiments, designed to empirically measure how people trade off privacy for money, and to test whether human behavior is consistent with theoretical models for the value of privacy.

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ORFE Talk: The Implications of Privacy-Aware Choice, Tuesday, Feb 7, 4:30pm- Reminder
by Nicole E. Wagenblast 06 Feb '17

06 Feb '17

ORFE Colloquium Speaker Rachel Cummings, from California Institute of Technology Tuesday, February 7th- 4:30pm Sherrerd Hall, Room 101 The Implications of Privacy-Aware Choice Privacy concerns are becoming a major obstacle to using data in the way that we want. It's often unclear how current regulations should translate into technology, and the changing legal landscape surrounding privacy can cause valuable data to go unused. In addition, when people know that their current choices may have future consequences, they might modify their behavior to ensure that their data reveal less --- or perhaps, more favorable --- information about themselves. Given these concerns, how can we continue to make use of potentially sensitive data, while providing satisfactory privacy guarantees to the people whose data we are using? Answering this question requires an understanding of how people reason about their privacy and how privacy concerns affect behavior. In this talk, we will see how strategic and human aspects of privacy interact with existing tools for data collection and analysis. I will begin by adapting the standard model of consumer choice theory to a setting where consumers are aware of, and have preferences over, the information revealed by their choices. In this model of privacy-aware choice, I will show that little can be inferred about a consumer's preferences once we introduce the possibility that she has concerns about privacy, even when her preferences are assumed to satisfy relatively strong structural properties. Next, I will analyze how privacy technologies affect behavior in a simple economic model of data-driven decision making. Intuition suggests that strengthening privacy protections will both increase utility for the individuals providing data and decrease usefulness of the computation. I will demonstrate that this intuition can fail when strategic concerns affect consumer behavior. Finally, I'll discuss ongoing behavioral experiments, designed to empirically measure how people trade off privacy for money, and to test whether human behavior is consistent with theoretical models for the value of privacy.

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Shilpa Nadimpalli will present her pre-FPO for on Monday, February 13, 2017 at 9am in CS 401.
by Nicki Gotsis 03 Feb '17

03 Feb '17

Shilpa Nadimpalli will present her pre-FPO for on Monday, February 13, 2017 at 9am in CS 401. The members of her committee are as follows: Mona Singh (Adviser); Readers: Ben Raphael and Olga Troyanskaya; Nonreaders: Barbara Engelhardt and Tom Funkhouser The talk abstract follows below: Proteins play essential roles in nearly every biological process, from metabolism and sensory perception to immune response and gene regulation. The vast majority of these functions are carried out through specific protein interactions with DNA, metabolites and other ligands, forming complex biological networks. Although mutations affecting protein interactions have resulted in human disease, other protein interactions evolve naturally within the human population and across species. Experimental techniques to determine the prevalence and functional impact of mutations affecting protein interactions are prohibitively costly and time-consuming (e.g., x-ray crystallography, protein binding microarrays). In my thesis, I develop and use novel computational approaches to measure the extent to which protein interactions are perturbed across healthy individuals, across individuals with disease, and across species. In my talk, I will first describe a tool I have developed to automatically infer interaction sites from sequence data. This tool can infer interaction sites in over 60% of human genes---a nearly threefold increase in coverage over related state-of-the-art methods. Next, I will focus on utilizing this tool to identify genes whose interaction sites are enriched in cancer mutations by contrasting observed natural variants from tens of thousands of healthy individuals to observed cancer mutations from thousands of tumor samples. These genes, often rarely mutated across a cohort of patients and thus easily missed by more standard approaches, are likely to be critically relevant for cancer development. In the last part of my talk, I will discuss my application of a comparative genomics framework to quantify changes in protein-DNA interactions across species. I find substantial evidence suggesting that, contrary to popular convention, gene regulatory network perturbation can stem from changes in non-duplicated DNA-binding proteins. --

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ORFE Talk: The Implications of Privacy-Aware Choice, Tuesday, Feb 7, 4:30pm
by Nicole E. Wagenblast 01 Feb '17

01 Feb '17

ORFE Colloquium Speaker Rachel Cummings, from California Institute of Technology Tuesday, February 7th- 4:30pm Sherrerd Hall, Room 101 The Implications of Privacy-Aware Choice Privacy concerns are becoming a major obstacle to using data in the way that we want. It's often unclear how current regulations should translate into technology, and the changing legal landscape surrounding privacy can cause valuable data to go unused. In addition, when people know that their current choices may have future consequences, they might modify their behavior to ensure that their data reveal less --- or perhaps, more favorable --- information about themselves. Given these concerns, how can we continue to make use of potentially sensitive data, while providing satisfactory privacy guarantees to the people whose data we are using? Answering this question requires an understanding of how people reason about their privacy and how privacy concerns affect behavior. In this talk, we will see how strategic and human aspects of privacy interact with existing tools for data collection and analysis. I will begin by adapting the standard model of consumer choice theory to a setting where consumers are aware of, and have preferences over, the information revealed by their choices. In this model of privacy-aware choice, I will show that little can be inferred about a consumer's preferences once we introduce the possibility that she has concerns about privacy, even when her preferences are assumed to satisfy relatively strong structural properties. Next, I will analyze how privacy technologies affect behavior in a simple economic model of data-driven decision making. Intuition suggests that strengthening privacy protections will both increase utility for the individuals providing data and decrease usefulness of the computation. I will demonstrate that this intuition can fail when strategic concerns affect consumer behavior. Finally, I'll discuss ongoing behavioral experiments, designed to empirically measure how people trade off privacy for money, and to test whether human behavior is consistent with theoretical models for the value of privacy.

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EE Department Colloquium - Korhammer Lecture Series
by Nicole E. Wagenblast 30 Jan '17

30 Jan '17

Having trouble viewing this email? Click here Korhammer Lecture Series The Science of Information: Case Studies from DNA and RNA Assembly David Tse Professor, Information Systems Laboratory, Department of Electrical Engineering Stanford University February 22, 2017 5:00 pm - 6:00 pm Bowen Hall Auditorium Reception to follow Click here for more information This seminar is supported by the Korhammer Lecture Fund Copyright © 20XX. All Rights Reserved. Princeton University, Department of Electrical Engineering , Olden Street , Princeton , NJ 08544 SafeUnsubscribe™ heathere(a)princeton.edu Forward this email | Update Profile | About our service provider Sent by heathere(a)princeton.edu in collaboration with Try it free today Save

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Aaron Blankstein will present his Pre FPO on Tuesday, February 7, 2017 at 10am in CS 302.
by Nicki Gotsis 27 Jan '17

27 Jan '17

Aaron Blankstein will present his Pre FPO on Tuesday, February 7, 2017 at 10am in CS 302. The members of his committee are as follows: Readers: Michael Freedman (adviser), Jennifer Rexford, and Nick Feamster; Non-Readers: Robert Tarjan and Kyle Jamieson Everyone is invited to attend his talk. The talk abstract follows below. Abstract: In my thesis, I will show how, in many respects, modern web applications are built with implicit structure, such that several classic problems in computer systems can be tackled in new ways allowing applications to reap security and performance benefits. I will apply this thesis in two separate contexts. In the first, I will look at the problems of providing some automatic security to web applications by partitioning the server-side code of the application, isolating those partitions, learning access control policies for those partitions, and extending this isolation to front-end code with javascript sandboxing. In the second, I will look at how modern web applications interact with application caches, and develop a family of cache eviction policies tailored to these needs by focusing on prioritizing individual items to capture how item request frequencies, associated costs, and expiration times affect cache performance.

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