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February 2016

Data-driven, Interactive Scientific Articles in a Collaborative Environment with Authorea

February 11, 2016 @ 12:00 pm - 1:00 pm
N928, 300 Jay St., Room N928
Brooklyn, NY 11201 United States
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Alberto Pepe

Most tools that scientists use for the preparation of scholarly manuscripts, such as Microsoft Word and LaTeX, function offline and do not account for the born-digital nature of research objects. Also, most authoring tools in use today are not designed for collaboration, and, as scientific collaborations grow in size, research transparency and the attribution of scholarly credit are at stake. In this talk, I will show how the Authorea platform allows scientists to collaboratively write rich data-driven manuscripts on the web--articles that would natively offer readers a dynamic, interactive experience with an article’s full text, images, data, and code--paving the road to increased data sharing, data reuse, research reproducibility, and Open Science.

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Two Projects in Text Data Mining and Natural Language Processing

February 25, 2016 @ 12:00 pm - 1:00 pm
N928, 300 Jay St., Room N928
Brooklyn, NY 11201 United States
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Elena Filatova

Two Projects in Text Data Mining and Natural Language Processing ELENA FILATOVA Department of Computer Systems Technology, New York City College of Technology, City University of New York   In this presentation I will describe two projects I am working on: Automatic Sarcasm Detection and Information Assymetries in Multilingual Wikipedia. Sarcasm detection: Humans are good at identifying sarcasm in text and speech. Can we teach a computer to identify sarcasm? Is it possible to point out the parts of the review…

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March 2016

Towards Improving Interface Modularity in Legacy Java Software Through Automated Refactoring

March 3, 2016 @ 12:00 pm - 1:00 pm
N928, 300 Jay St., Room N928
Brooklyn, NY 11201 United States
Raffi Khatchadourian

The skeletal implementation pattern is a software design pattern consisting of defining an abstract class that provides a partial interface implementation. However, since Java allows only single class inheritance, if implementers decide to extend a skeletal implementation, they will not be allowed to extend any other class. Also, discovering the skeletal implementation may require a global analysis. Java 8 enhanced interfaces alleviate these problems by allowing interfaces to contain (default) method implementations, which implementers inherit. Java classes are then free to extend a different class, and a separate abstract class…

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Bio-inspired Computation Approach for Tumor Growth with Spatial Randomness Analysis of Kidney Cancer Xenograft Pathology Slides

March 10, 2016 @ 12:00 pm - 1:00 pm
N928, 300 Jay St., Room N928
Brooklyn, NY 11201 United States
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In our research, we analyze digitized images of Hematoxylin-Eosin (H&E) slides equipped with tumorous tissues from patient derived xenograft models to build our bio-inspired computation method, namely Personalized Relevance Parameterization of Spatial Randomness (PReP-SR). Applying spatial pattern analysis techniques of quadrat counts, kernel estimation and nearest neighbor functions to the images of the H&E samples, slide-specific features are extracted to examine the hypothesis that existence of dependency of nuclei positions possesses information of individual tumor characteristics. These features are then used as inputs to PReP-SR to compute tumor growth parameters for exponential-linear model. Differential evolution algorithms are developed for tumor growth parameter computations, where a candidate vector in a population consists of size selection indices for spatial evaluation and weight coefficients for spatial features and their correlations. Using leave-one-out-cross-validation method, we showed that, for a set of H&E slides from kidney cancer patient derived xenograft models, PReP-SR generates personalized model parameters with an average error rate of 13:58%. The promising results indicate that bio-inspired computation techniques may be useful to construct mathematical models with patient specific growth parameters in clinical systems.

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NYC, Media and Technology: What’s Hot

March 24, 2016 @ 12:00 pm - 1:00 pm
N928, 300 Jay St., Room N928
Brooklyn, NY 11201 United States
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Just Hendrix

Founded in 2010, NYC Media Lab is dedicated to driving innovation and ultimately job growth in media and technology by facilitating collaboration between the City’s universities and its companies. Comprised of a consortium including New York City Economic Development Corporation, New York University, Columbia University, The New School, CUNY, and Pratt Institute, NYC Media Lab's goals include generating research and development, knowledge transfer, and talent development across all of the City’s campuses. Justin will describe NYC Media Lab, its projects, and the curiosities of its member companies.

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April 2016

Ontology-based Classification and Faceted Search Interface for APIs

April 7, 2016 @ 12:00 pm - 1:00 pm
N928, 300 Jay St., Room N928
Brooklyn, NY 11201 United States
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This work introduces faceted service discovery. It uses the Programmable Web directory as its corpus of APIs and enhances the search to enable faceted search, given an OWL ontology. The ontology describes semantic features of the APIs. We have designed the API classification ontology using LexOnt, a software we have built for semi-automatic ontology creation tool. LexOnt is geared toward non-experts within a service domain who want to create a high-level ontology that describes the domain. Using well- known NLP algorithms, LexOnt generates a list of top terms and phrases from the Programmable Web corpus to enable users to find high-level features that distinguish one Programmable Web service category from another. To also aid non-experts, LexOnt relies on outside sources such as Wikipedia and Wordnet to help the user identify the important terms within a service category. Using the ontology created from LexOnt, we have created APIBrowse, a faceted search interface for APIs. The ontology, in combination with the use of the Apache Solr search platform, is used to generate a faceted search interface for APIs based on their distinguishing features. With this ontology, an API is classified and displayed underneath multiple categories and displayed within the APIBrowse interface. APIBrowse gives programmers the ability to search for APIs based on their semantic features and keywords and presents them with a filtered and more accurate set of search results.

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December 2017

Energy Management as a Service (EMaaS)

December 7, 2017 @ 12:00 pm - 1:00 pm
N907, 300 Jay Street
Brooklyn, NY 11201 United States

Yu-Wen Chen, PhD Assistant Professor, CST Dept. December 7, 12pm-1pm, Room N907 Dr. Chen presents an introduction to smart grid and cloud computing as the foundation for the design of customer-oriented energy-efficient systems (EmaaS). These systems provide financial incentives to customers thus enhancing the renewable energy sources(solar, wind, electrical) integration with the smart grid community. Smart grid enables the two-way communication between the electricity utility and its customers and adopts new technologies such as electric vehicle and distributed energy resources…

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March 2018

Applied AI Techniques

March 15, 2018 @ 12:00 pm - 1:00 pm
N923

Will Ross Business Development, M& A IBM Watson Group     In a world of open data and consumer platforms it is easy to forget the significant quantities of high-value data still held by entities who view or require those assets to be proprietary.  A myriad of parties from corporations to government entities are keen to explore new advances in AI but do not recognize the challenges that will befall them as they try to protect the data assets that…

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April 2018

Eager Execution in TensorFlow

April 12, 2018 @ 12:00 pm - 1:00 pm
N923

Alexandre Passos Software Engineer, Google             In this talk we'll go over TensorFlow, an open- source cross-platform machine learning library developed by Google, and explore its new feature: eager execution. We'll go over how to use it to write dynamic models, to debug and profile models, and to learn deep learning.

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November 2018

Building Noise Robust Machine Listeners with Data and Inspiration from Humans

November 8, 2018 @ 12:00 pm - 1:00 pm
N919

Michael Mandel Assoc. Professor Brooklyn College, Graduate Center November 8, 12pm-1pm Room N919     Matching human performance is one of the most difficult problems for a variety of speech communication technologies, including automatic speech recognition, voice processing in hearing aids, and mobile telephony.  One theory of human noise robustness is that listeners pick out reliable "glimpses" of a target sound and utilize contextual clues to fill in missing information using top-down knowledge.  This talk presents work that brings both of…

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