Category: Data Science
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talk: Stepping Away From the Edge of Illness, 4:30p Thr 4/6
CHMPR Distinguished Lecturer Series Stepping Away From the Edge of Illness Dr. Ancha Baranova, George Mason University 4:30-5:30pm Thursday, 6 April 2017, UC 310, UMBC 3:30-4:30pm Reception, UC 310 The human body may be afflicted by a multitude of chronic diseases. In principle, any chronic ailment develops along with one or more of the four…
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Free screening: CODE: Debugging the Gender Gap, 3-5 Fri 3/31, UMBC
Join the UMBC Computer Science Education Club and the Center for Women in Technology for a free screening of the award winning film, CODE: Debugging the Gender Gap. The documentary exposes the dearth of American female and minority software engineers and explores the reasons for this gender gap. CODE raises the question: what would society gain…
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talk: Phase synchrony in heart-brain interactions predicts personality and emotions, 1pm 3/17
UMBC CSEE Seminar Series Phase synchrony in heart-brain interactions predicts personality and emotions Ehsan Shokri Kojori NIH, National Institute on Alcoloh Abuse and Alcoholism 1:00-2:00pm Friday, 17 March 2017, ITE 231 Despite the historical interest in the link between brain and heart, it is unknown whether brain and heart interactions provide meaningful information about emotions…
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talk: Semantic Approach to Automating Big Data and Cloud, 12pm Mon 2/20
A Semantically Rich Approach to Automating Big Data and Cloud Dr. Karuna Joshi University of Maryland, Baltimore County 12:00pm Monday, 20 February 2017, ITE 325b, UMBC With the explosion of Big Data and the growth of data science, there is an urgent need to automate the data lifecycle of generation, ingestion, analytics, knowledge extraction, and…
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talk: Bayesianism and the Evidence Problem, 4pm 2/15
Philosophy Department Colloquium Bayesianism and the Evidence Problem Lisa Cassell University of Massachusetts/Amherst 4-6:00pm Wednesday, 15 February 2017, 456 Performing Arts & Humanities Bayesianism is a theory that gives us norms for how the degrees of belief we have in certain propositions — our “credences” — ought to hang together. For instance, it tells me…
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Talk: Lexumo Continuous Open Source Code Security
The UMBC Cyber Defense Lab presents Lexumo Tech Talk: Continuous Open Source Code Security Dr. Richard T. Carback III Lexumo, Inc. 11:15am Friday, 16 December 2016, ITE 237, UMBC Lexumo is a startup which provides the only automated service that continuously monitors IoT software platforms for the latest public vulnerabilities. Funded in January of 2016…
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Event: Wanted, One Million IT Security Specialists by 2018
Students, faculty, staff and community members are invited to join CWIT and STEMRules for a lunch event to hear from and network with diverse professionals from across the cybersecurity industry. Wanted: One Million IT Security Specialists by 2018 You Could be One of Them 12-1:30pm Friday, 2 December 2016 Albin O. Kuhn Library Gallery (1st floor) Lunch…
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talk: Genetic ancestry predicts striatal dopamine D2 receptors, 1pm Dec 2, ITE229
UMBC CSEE Seminar Series Genetic ancestry predicts striatal dopamine D2 receptors Dr. Corinde Wiers National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 1-2pm Friday, 2 December 2016, ITE 229, UMBC Genetic ancestry was recently found to be associated with cortical geometry, cortical surface, and total brain volume in humans. Despite ethnic differences in allele…
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talk: Statistics and Big Data at Google, 5-6pm Thr 11/3, UC310, UMBC
Statistics and Big Data at Google Dr. Tim Hesterberg, Google 5:00-6:00pm Thursday, 3 November 2016, UC 310, UMBC Google lives on data. Search, Ads, YouTube, Maps…they all live on data. Join Senior Quantitative Analyst (and Lady Statistician) Tim Hesterberg, as he shares stories about how we use data, how we’re experimenting to make improvements (yes,…
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talk: Learning to Predict the Future from Unlabeled Data, 1pm Fri 10/28, ITE229, UMBC
The UMBC CSEE Seminar Series Presents Learning to Predict the Future from Unlabeled Data Hamed Pirsiavash, CSEE Department, UMBC 1-2pm Friday, 28 October 2016, ITE 229 Anticipating actions and objects before they start or appear is a difficult problem in computer vision with several real-world applications. This task is challenging partly because it requires leveraging…