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Better Signal Mapping with Machine Learning

Published on March 18, 2019 by

Bad cellular reception is a universal frustration, but keeping the public at four bars takes a lot of work.  Cellular providers constantly test, tune, and develop their infrastructure, with a close eye on their performance – and that of their competitors.   Optimizing the network requires keeping tabs on signal strength, and on identifying problems quickly

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Making the Most of Bad News about Cancer

Published on March 13, 2019 by

When celebrities or other well-known figures go public with the bad news that they have cancer, there’s an opportunity for more than sympathy.  As shown in a new paper in the journal Cancer Control by NCASD Lab PI Carter Butts and alumnus Ben Gibson, with collaborators Sarah Vos and Jeannette Sutton, these announcements can serve

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NCASD Lab PI Butts Elected AAAS Fellow

Published on March 8, 2019 by

NCASD Lab PI Carter Butts recently traveled to Washington, DC, to receive recognition as a newly elected Fellow of the American Association for the Advancement of Science.  Each year, the AAAS recognizes a small number of scientists across all fields for outstanding contributions to the promotion and/or progress of scientific knowledge.  Butts was recognized for

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Dissecting Subgroups in Complex Networks

Published on June 4, 2018 by

Complex social, biological, or other networks often arise from a wide range of mechanisms, acting within a heterogeneous and often dynamic environment.  This complicated “stew” of factors gives rise to networks that are anything but clean and elegant: rather, they are decidedly “lumpy,” consisting of myriad overlapping subgroups of varying size and consistency.  While this

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To Improve Network Measurement, Minimize Opportunities for Error

Published on May 28, 2018 by

Measuring social, biological, and other networks is often a difficult and expensive process, involving surveys, experiments, or other time consuming and costly procedures.  Given that no measurement is perfect, how do we get the greatest “bang for the buck” when trying to assess network ties?  A new paper by NCASD lab members Francis Lee and

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Solving the Mysteries of Butterfly Spit – With Computation

Published on January 5, 2018 by

Heliconius butterflies are unusual in consuming pollen — unlike butterflies that live on nectar — a task made more difficult by the fact that they lack the mouthparts needed to chew it.  How do these insects manage to devour pollen grains too big to swallow, without the ability to chew them?  The answer lies in

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NCASD Lab Publishes Work on New Methods for Simulating Networks

Published on November 6, 2017 by

Simulating the structure of complex networks is an important challenge for problems ranging from the modeling organizational structure to understanding the behavior of protein aggregates.  While recent years have seen many innovations in this area, obtaining provably high quality simulations for networks with complex dependence has remained an elusive goal.  In a forthcoming paper in

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Improving Molecular Dynamics Simulations with Machine Learning

Published on October 13, 2017 by

NCASD Postdoc Gianmarc Grazioli, Lab PI Carter Butts, and Prof. Ioan Andricioaei from the UCI Chemistry Department have published new results showing how the performance of molecular dynamics simulations can be improved with a little help from machine learning.  These results are contained in their forthcoming paper, “Automated Placement of Interfaces in Conformational Kinetics Calculations

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Lab PI Butts Elected to ASA Offices

Published on June 12, 2017 by

Lab PI Carter Butts has been elected to two offices in the American Sociological Association: the Section Council of the ASA Section on Methodology, and Chair-Elect of the ASA Section on Mathematical Sociology.  Butts is currently serving a term on the Section Council of the ASA Section on Mathematical Sociology, and will transition from this

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New Book by Lab Alumna Landivar

Published on June 9, 2017 by

Lab Alumna Liana Landivar (Senior Researcher and Sociologist at the US Department of Labor) has released a new book, Mothers at Work: Who Opts Out?  Landivar’s book examines a key question relating to the labor force participation of high-achieving American women: are mothers in managerial and professional occupations more likely to leave the labor force

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