November 2014 - talks - lists.cs.princeton.edu

Fwd: EE Seminar - November 24, 2014, 4:30 pm, E-Quad B205 - Prof. Lakshminarayanan Subramanian
by Jennifer Rexford 18 Nov '14

18 Nov '14

> From: "Lori A. Bailey" <lbailey(a)Princeton.EDU> > Date: November 18, 2014 at 3:12:35 PM EST > To: ee-seminar(a)Princeton.EDU > Subject: EE Seminar - November 24, 2014, 4:30 pm, E-Quad B205 - Prof. Lakshminarayanan Subramanian > Reply-To: "Lori A. Bailey" <lbailey(a)Princeton.EDU> > > > > Speaker: Prof. Lakshminarayanan Subramanian > New York University > Title: Societal Network Science: Where Societal Networks … [View More]meets Data Science > Date: Monday, November 24, 2014 > Time: 4:30 p.m. > Room: E-Quad, Room B205 > Host: Prof. Prateek Mittal > > Abstract: This talk focuses on a new emerging area of research, which we term "Societal Network Science", where the goal is to understand important societal, social and human indicators based on the network characteristics of how humans, physical and digital entities interact. Societal networks aim to capture meaningful human interaction patterns and the potential causal relationships between these interactions. In this talk, we will outline our recent results on three related but seemingly disparate problems in societal network science: disease surveillance, road traffic networks and event networks. In the space of disease surveillance, our group has worked on a 3-year long project to build a fine-grained dengue surveillance system in the country of Pakistan, where we can predict the incidence level of dengue using citizen driven data at a sub-city granularity, 14 days ahead of time. In the space of road traffic networks, we will illustrate how one can predict sudden traffic jams in NY city with high confidence 3 minutes before they happen; surprisingly, 3 minutes is sufficient to potentially avoid the jam too! In the space of event networks, we will show how one can use NLP techniques to learn networks of real world events from news corpora and how such event networks can be used in the prediction of real-world social phenomena like drought, price variations and disease outbreaks. Our longer term vision is to build an automated analytics engine for societal network science that can learn and infer socio-economic phenomena from highly diverse and noisy data sources. > > Biography: Lakshminarayanan Subramanian is an Associate Professor in the Courant Institute of Mathematical Sciences at NYU. His research interests are in the areas of networked systems, big data analytics and computing for development. He is a member of the NYU Systems group and co-established the Center for Technology and Economic Development (CTED) at NYU. He is also affiliated with the Center for Data Science and the Global Institute of Public Health (GIPH) at NYU. He is the co-founder of Entrupy Inc, a startup on surface fingerprinting. He completed his PhD from UC Berkeley and undergraduate studies from IIT-Madras. > > [View Less]

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Colloquium Speaker Emma Brunskill Wed Nov 19, 4:30pm
by Nicole E. Wagenblast 18 Nov '14

18 Nov '14

Colloquium Speaker Emma Brunskill , Carnegie Mellon University Wednesday, November 19, 2014 - 4:30pm Computer Science 105 Interactive ML for People: The Small Data Problem Consider an intelligent tutoring system or an autonomous decision support tool for a doctor. Though such systems may in aggregate have a huge amount of data, the data collected for a single individual is typically very small, and the policy space (of what to next teach a student or how to help treat a patient) is … [View More]

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Distinguished Colloquium Speaker Dahlia Malkhi, Today, 4:30pm
by Nicole E. Wagenblast 18 Nov '14

18 Nov '14

Distinguished Colloquium Speaker Dahlia Malkhi, until recently from Microsoft Research, Silicon Valley Tuesday, November 18, 4:30pm Computer Science 105 CorfuDB: Transactional Data Services over a Shared Log Conventional wisdom has it that the only way to scale replicated services is by partitioning the data. What would you do if given an infrastructure that breaks the seeming tradeoff between consistency and scale? The talk will describe our experience with building CorfuDB, a … [View More]

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Distinguished Colloquium Speaker Dahlia Malkhi, Tues Nov 18, 4:30pm
by Nicole E. Wagenblast 17 Nov '14

17 Nov '14

Distinguished Colloquium Speaker Dahlia Malkhi, until recently from Microsoft Research, Silicon Valley Tuesday, November 18, 4:30pm Computer Science 105 CorfuDB: Transactional Data Services over a Shared Log Conventional wisdom has it that the only way to scale replicated services is by partitioning the data. What would you do if given an infrastructure that breaks the seeming tradeoff between consistency and scale? The talk will describe our experience with building CorfuDB, a … [View More]

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Colloquium Speaker Sebastian Burckhardt Thurs Nov 20, 4:30pm
by Nicole E. Wagenblast 14 Nov '14

14 Nov '14

Colloquium Speaker Sebastian Burckhardt , from Microsoft Research Thursday, November 20, 2014 - 4:30pm Computer Science Small Auditorium (Room 105) Robust Abstractions for Replicated Shared State In the age of cloud-connected mobile devices, users want responsive apps that read and write shared data everywhere, at all times, even if network connections are slow or unavailable. Replication and eventual consistency, while able to deliver this experience, require us to face the complexity … [View More]

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ORFE Optimization Seminar: Moses Charikar, Thursday, Nov 20th at 4:30pm, Sherrerd Hall 101
by Nicole E. Wagenblast 13 Nov '14

13 Nov '14

************************************************************************************** === ORFE Optimization Seminar === DATE: Thursday, November 20, 2014 TIME: 4:30pm ***new time*** LOCATION: Sherrerd Hall room 101 ***new room*** SPEAKER: Moses Charikar, Computer Science Dept., Princeton University TITLE: Spectral Embedding of k-Cliques, Graph Partitioning and k-Means ABSTRACT: We introduce and study a new notion of graph partitioning, intimately connected to k-means clustering. … [View More]

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Colloquium Speaker Emma Brunskill Wed Nov 19, 4:30pm
by Nicole E. Wagenblast 13 Nov '14

13 Nov '14

Colloquium Speaker Emma Brunskill , Carnegie Mellon University Wednesday, November 19, 2014 - 4:30pm Computer Science 105 Interactive ML for People: The Small Data Problem Consider an intelligent tutoring system or an autonomous decision support tool for a doctor. Though such systems may in aggregate have a huge amount of data, the data collected for a single individual is typically very small, and the policy space (of what to next teach a student or how to help treat a patient) is … [View More]

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Colloquium Speaker Ryan Adams Today, 4:30pm
by Nicole E. Wagenblast 13 Nov '14

13 Nov '14

Better Science Through Better Bayesian Computation Ryan Adams, Harvard University Thursday, November 13, 4:30pm Computer Science 105 As we grapple with the hype of "big data" in computer science, it is important to remember that the data are not the central objects: we collect data to answer questions and inform decisions in science, engineering, policy, and beyond. In this talk, I will discuss my work in developing tools for large-scale data analysis, and the scientific collaborations in … [View More]

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Distinguished Colloquium Speaker Dahlia Malkhi, Tues Nov 18, 4:30pm
by Nicole E. Wagenblast 12 Nov '14

12 Nov '14

Distinguished Colloquium Speaker Dahlia Malkhi, until recently from Microsoft Research, Silicon Valley Tuesday, November 18, 4:30pm Computer Science 105 CorfuDB: Transactional Data Services over a Shared Log Conventional wisdom has it that the only way to scale replicated services is by partitioning the data. What would you do if given an infrastructure that breaks the seeming tradeoff between consistency and scale? The talk will describe our experience with building CorfuDB, a … [View More]

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Colloquium Speaker Ryan Adams Thurs Nov 13, 4:30pm
by Nicole E. Wagenblast 12 Nov '14

12 Nov '14

Better Science Through Better Bayesian Computation Ryan Adams, Harvard University Thursday, November 13, 4:30pm Computer Science 105 As we grapple with the hype of "big data" in computer science, it is important to remember that the data are not the central objects: we collect data to answer questions and inform decisions in science, engineering, policy, and beyond. In this talk, I will discuss my work in developing tools for large-scale data analysis, and the scientific collaborations in … [View More]

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