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X-WR-CALDESC:Events for Columbia Entrepreneurship
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BEGIN:VEVENT
DTSTART;TZID=UTC:20190201T153000
DTEND;TZID=UTC:20190201T173000
DTSTAMP:20260414T225931
CREATED:20190114T220206Z
LAST-MODIFIED:20190114T220206Z
UID:15487-1549035000-1549042200@entrepreneurship.columbia.edu
SUMMARY:DSI Health Analytics Center
DESCRIPTION:OPEN TO ALL \n\nThe Data Science Institute invites you to poster session that will highlight some of the recent and current research done by our centers. Open to the public and larger Columbia community. Light refreshments provided.\n\n\nFriday\, February 1\, 2019 \n3:30 PM – 5:30 PM\n\nMudd Hall\, 500 W. 120 St.\, New York\, NY 10027\nRoom/Area: 407 (Data Science Institute)
URL:https://entrepreneurship.columbia.edu/event/dsi-health-analytics-center/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20190129T130000
DTEND;TZID=UTC:20190129T140000
DTSTAMP:20260414T225931
CREATED:20190114T214956Z
LAST-MODIFIED:20190114T214956Z
UID:15483-1548766800-1548770400@entrepreneurship.columbia.edu
SUMMARY:Learning Engines for Healthcare: Using Machine Learning to Transform Clinical Practice and Discovery
DESCRIPTION:OPEN TO ALL COLUMBIANS\n\nLecture in Precision Medicine: Mihaela van der Schaar\n\n\n \n“Learning Engines for Healthcare: Using Machine Learning to Transform Clinical Practice and Discovery” \n \nProf. Mihaela van der Schaar\, John Humphrey Plummer Professor of Machine Learning\, Artificial Intelligence and Medicine\, University of Cambridge  \n \nJanuary 29\, 2019\n\n1:00PM – 2:00PM\nWilliam Black Building\, Alumni Auditorium\, \n650 W. 168th Street\, New York\, NY 10032\n\n\nProfessor van der Schaar is John Humphrey Plummer Professor of Machine Learning\, Artificial Intelligence and Medicine at the University of Cambridge and a Turing Faculty Fellow at The Alan Turing Institute in London\, where she leads the effort on data science and machine learning for personalized medicine. Prior to this\, she was a Chancellor’s Professor at UCLA and MAN Professor of Quantitative Finance at University of Oxford. She is an IEEE Fellow (2009). She has received the Oon Prize on Preventative Medicine from the University of Cambridge (2018). She has also been the recipient of an NSF Career Award\, 3 IBM Faculty Awards\, the IBM Exploratory Stream Analytics Innovation Award\, the Philips Make a Difference Award and several best paper awards\, including the IEEE Darlington Award. She holds 33 granted USA patents. Her current research focus is on data science and machine learning for medicine and education.\n\nThe overarching goal of her research is to develop cutting-edge machine learning\, AI and operations research theory\, methods\, algorithms and systems to understand the basis of health and disease; develop methodology to catalyze clinical research; support clinical decisions through individualized medicine; inform clinical pathways\, better utilize resources & reduce costs; and inform public health.\n\nTo do this\, she is creating what she call Learning Engines for Healthcare (LEH’s). An LEH is an integrated ecosystem that uses machine learning\, AI and operations research to provide clinical insights and healthcare intelligence to all the stakeholders (patients\, clinicians\, hospitals\, administrators). In contrast to an Electronic Health Record\, which provides a static\, passive\, isolated display of information\, an LEH provides dynamic\, active\, holistic & individualized display of information including alerts.
URL:https://entrepreneurship.columbia.edu/event/learning-engines-healthcare-using-machine-learning-transform-clinical-practice-discovery/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20181128T180000
DTEND;TZID=UTC:20181128T200000
DTSTAMP:20260414T225931
CREATED:20181107T205120Z
LAST-MODIFIED:20181107T205120Z
UID:14971-1543428000-1543435200@entrepreneurship.columbia.edu
SUMMARY:Data Science Institute Poster Session: Computing Systems
DESCRIPTION:OPEN TO ALL\n\n\nREGISTER HERE\n\n\nMudd Hall\, 500 W. 120 St.\, New York\, NY 10027\nRoom/Area: 407 (Data Science Institute)\n\n\nThe Data Science Institute invites you to poster session that will highlight some of the recent and current research done by our centers. Open to the public an larger Columbia community. Light refreshments provided.\n\nEvent Contact Information: \nData Science Institute\n212-854-5660\ndatascience@columbia.edu
URL:https://entrepreneurship.columbia.edu/event/data-science-institute-poster-session-computing-systems/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20181126T180000
DTEND;TZID=UTC:20181126T200000
DTSTAMP:20260414T225931
CREATED:20181107T204931Z
LAST-MODIFIED:20181107T204931Z
UID:14969-1543255200-1543262400@entrepreneurship.columbia.edu
SUMMARY:Data Science Institute Poster Session: Financial & Business Analytics
DESCRIPTION:OPEN TO ALL\n\n\nREGISTER HERE\n\n\nMudd Hall\, 500 W. 120 St.\, New York\, NY 10027\nRoom/Area: 407 (Data Science Institute)\n\n\nThe Data Science Institute invites you to poster session that will highlight some of the recent and current research done by our centers. Open to the public an larger Columbia community. Light refreshments provided.\n\nEvent Contact Information: \nData Science Institute\n212-854-5660\ndatascience@columbia.edu
URL:https://entrepreneurship.columbia.edu/event/data-science-institute-poster-session-financial-business-analytics/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20181119T180000
DTEND;TZID=UTC:20181119T200000
DTSTAMP:20260414T225931
CREATED:20181107T204800Z
LAST-MODIFIED:20181107T204800Z
UID:14965-1542650400-1542657600@entrepreneurship.columbia.edu
SUMMARY:Data Science Institute Poster Session: Foundations of Data Science
DESCRIPTION:OPEN TO ALL\n\nRSVP HERE\n\nMudd Hall\, 500 W. 120 St.\, New York\, NY 10027\nRoom/Area: 407 (Data Science Institute)\n\n\nThe Data Science Institute invites you to poster session that will highlight some of the recent and current research done by our centers. Open to the public an larger Columbia community. Light refreshments provided.\n\nEvent Contact Information: \nData Science Institute\n212-854-5660\ndatascience@columbia.edu
URL:https://entrepreneurship.columbia.edu/event/data-science-institute-poster-session-foundations-data-science/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20181114T180000
DTEND;TZID=UTC:20181114T200000
DTSTAMP:20260414T225931
CREATED:20181107T204419Z
LAST-MODIFIED:20181107T204431Z
UID:14962-1542218400-1542225600@entrepreneurship.columbia.edu
SUMMARY:Data Science Institute Poster Session: Smart Cities
DESCRIPTION:Mudd Hall\, 500 W. 120 St.\, New York\, NY 10027\nRoom/Area: 407 (Data Science Institute)\n\n\n\nThe Data Science Institute invites you to poster session that will highlight some of the recent and current research done by our centers. Open to the public an larger Columbia community. Light refreshments provided.\n\nEvent Contact Information: \nData Science Institute\n212-854-5660\ndatascience@columbia.edu
URL:https://entrepreneurship.columbia.edu/event/data-science-institute-poster-session-smart-cities-center/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20181114T103000
DTEND;TZID=UTC:20181114T120000
DTSTAMP:20260414T225931
CREATED:20180907T144746Z
LAST-MODIFIED:20180907T144746Z
UID:14390-1542191400-1542196800@entrepreneurship.columbia.edu
SUMMARY:Data Science Institute-Industry-Innovation Seminar: Johnson & Johnson
DESCRIPTION:OPEN TO ALL\n\n\nREGISTER HERE\n\n\nAmel Lageat\, Senior Director\, Consumer Business: “People centric approach to optimize Data Science\, Commercial impact and Leadership”\n\n \nWednesday\, November 14\, 2018\n10:30AM – 12:00PM\nSchapiro CEPSR\, Davis Auditorium (412)\n \n\n\n\nAbstract: In a world of Infobesity\, analysts\, engineers\, professionals\, executive leaders\, and people now have access to more data and analytics opportunities that we can ever make sense of. However\, a genuine people centric approach can provide the sharpest guidance in designing relevant strategies and solutions: it makes data\, models\, and analytics more meaningful and purposeful\, and also leads to marketing and commercial impact in global organizations.  In this talk\, I will use various business examples to discuss this premise\, including negative targeting (voluntarily deciding to not advertise to a person)\, the UX of marketing mix modeling (who is the real user?)\, and servant leadership to data experts (what does it look like?).\n\n\n–\nBio: Amel Lageat is heading up Global Analytics for the Johnson &Johnson Consumer Division. She has spent the last 20 years leading various commercial organizations within J&J (Marketing\, Market research and analytics)\, in France\, the UK and the US. Her recipe for impact is a fruitful combination of data\, curiosity and empathy.
URL:https://entrepreneurship.columbia.edu/event/data-science-institute-industry-innovation-seminar-johnson-johnson/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20181108T160000
DTEND;TZID=UTC:20181108T180000
DTSTAMP:20260414T225931
CREATED:20180907T144414Z
LAST-MODIFIED:20180907T144414Z
UID:14388-1541692800-1541700000@entrepreneurship.columbia.edu
SUMMARY:Foundations for Research Computing Distinguished Lecture Series: Dr. Eric Xing\, Professor\, Department of Machine Learning\, Carnegie Mellon University Founder\, Chief Executive Officer\, and Chief Scientist\, Petuum\, Inc.
DESCRIPTION:OPEN TO ALL\n\nREGISTER HERE\n\nThursday\, November 8\, 2018\n\n4:00 p.m. – 5:00 p.m. Lecture\n5:00 p.m. – 6:00 p.m. Reception\nBrown Institute | 2nd Floor\, Pulitzer Hall (2950 Broadway)\n \n\nDr. Eric P. Xing is Founder\, CEO and Chief Scientist at Petuum Inc. He is a Professor in the School of Computer Science at Carnegie Mellon University. He is also the Associate Department Head for Research of the Machine Learning Department and the Founding Director of the Center for Machine Learning and Health at CMU. For his distinguished contributions in AI/ML\, he was elected a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI).\n\nDr. Xing is a thought and innovation leader in Machine Learning and Artificial Intelligence. His principal research interests are in the development of machine learning and statistical methodology and large-scale computational system and architectures\, for solving problems involving automated learning\, reasoning\, and decision-making in high-dimensional\, multimodal\, and dynamic complex systems. His pioneering research has created numerous AI/ML foundational techniques\, such as the Parameter Server\, distance metric learning\, distributed network inference\, dynamic networks\, dynamic nonparametric Bayesian models\, spectral graphical models\, and variational inference. He has authored or co-authored over 300 publications\, while receiving multiple Best Paper Awards.\n\nDr. Xing is a board member of the International Machine Learning Society\, program chair and general chair of the International Conference of Machine Learning (ICML)\, and a former member of the U.S. Department of Defense Advanced Research Projects Agency (DARPA) Information Science and Technology (ISAT) Advisory group. He is the recipient of numerous awards including: The National Science Foundation (NSF) Career Award; Alfred P. Sloan Research Fellowship in Computer Science; United States Air Force Office of Scientific Research Young Investigator Award; and the IBM Open Collaborative Research Faculty Award.
URL:https://entrepreneurship.columbia.edu/event/foundations-research-computing-distinguished-lecture-series-dr-eric-xing-professor-department-machine-learning-carnegie-mellon-university-founder-chief-executive-officer-chief-scient/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20181012T130000
DTEND;TZID=UTC:20181012T143000
DTSTAMP:20260414T225931
CREATED:20181008T215045Z
LAST-MODIFIED:20181008T215045Z
UID:14703-1539349200-1539354600@entrepreneurship.columbia.edu
SUMMARY:Truth-Seeking in the Age of Disinformation
DESCRIPTION:Friday\, October 12\, 2018\n1:00PM – 2:30PM\nPupin Hall\, Room 428\n \n\n“Truth-Seeking in the Age of Disinformation”\n \nAbstract: Given the constantly growing proliferation of false claims online in recent years\, there has been also a growing research interest in automatically distinguishing false rumors from factually true claims. In this talk\, we will present several related problems. First\, in the context of investigative journalism\, we will address the problem of automatically identifying which claims in a political debate are most worthy and should be prioritized for fact-checking. We will then present a general-purpose deep learning framework for fully automatic fact checking using external sources\, which taps the potential of the entire Web as a knowledge source to confirm or reject a claim. We will further extend this framework to the context of community question answering\, where the goal is to decide whether an answer to a factual question is factually true or false. We will also cover some related problems such as stance detection\, trust-worthiness estimation for Web sites\, political ideology\, bias and propaganda detection\, as well as finding seminar users and opinion manipulation trolls in news community forums.\n \nBio: Dr. Preslav Nakov is a Senior Scientist at the Qatar Computing Research Institute\, HBKU. His research interests include computational linguistics and natural language processing\, machine translation\, question answering\, fact-checking\, sentiment analysis\, lexical semantics\, Web as a corpus\, and biomedical text processing.\n \nAt QCRI\, he leads a project whose aim is to develop a news aggregation application to limit the effect of fake news\, propaganda and media bias by helping users step out of their bubble and achieve a healthy news diet. He is also a co-PI of an MIT-QCRI collaboration project on Arabic Speech and Language Processing for Cross-Language Informatio n Search and Fact Verification\, and he was a co-PI of another MIT-QCRI collaboration project on Speech and Language Processing for Arabic (2013-2016).\n \nPreslav Nakov received his PhD degree in Computer Science from the University of California at Berkeley (supported by a Fulbright grant and a UC Berkeley fellowship)\, and a MSc degree from the Sofia University. He was a Research Fellow at the National University of Singapore\, a honorary lecturer in the Sofia University\, and a research staff in the Bulgarian Academy of Sciences.
URL:https://entrepreneurship.columbia.edu/event/truth-seeking-age-disinformation/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20181011T160000
DTEND;TZID=UTC:20181011T180000
DTSTAMP:20260414T225931
CREATED:20180907T144110Z
LAST-MODIFIED:20180907T144110Z
UID:14386-1539273600-1539280800@entrepreneurship.columbia.edu
SUMMARY:Foundations for Research Computing Distinguished Lecture Series: Dr. Lorena Barba\, Associate Professor\, Department of Mechanical and Aerospace Engineering\, George Washington University
DESCRIPTION:OPEN TO ALL\n\nREGISTER HERE\n\nThursday\, October 11\, 2018\n4:00 p.m. – 5:00 p.m. Lecture\n5:00 p.m. – 6:00 p.m. Reception\nBrown Institute | 2nd Floor\, Pulitzer Hall (2950 Broadway)\n \n\nLorena A. Barba is an associate professor of mechanical and aerospace engineering at the George Washington University in Washington\, DC. She holds a PhD in aeronautics from the California Institute of Technology and BSc/PEng degrees in mechanical engineering from Universidad Técnica Federico Santa María\, Chile. Her research includes computational fluid dynamics\, high-performance computing\, computational biophysics\, and animal flight.\n\nAn international leader in computational science and engineering\, she is also a long-standing advocate of open source software for science and education\, and she is well known for her courses and open educational resources. She was a recipient of the 2016 Leamer-Rosenthal Award for Open Social Sciences\, and in 2017\, was nominated and received an honorable mention in the Open Education Awards for Excellence of the Open Education Consortium.\n\nProf. Barba received the NSF Faculty Early CAREER award (2012)\, was named CUDA Fellow by NVIDIA Corp. (2012)\, is an awardee of the UK Engineering and Physical Sciences Research Council (EPSRC) First Grant program (2007)\, is an Amelia Earhart Fellow of the Zonta Foundation (1999) and a leader in computational science and engineering internationally. She is a member of the Board of Directors for the NumFOCUS non-profit\, and a member of the editorial board for IEEE/AIP Computing in Science and Engineering\, The Journal of Open Source Software\, and The ReScience Journal.
URL:https://entrepreneurship.columbia.edu/event/foundations-research-computing-distinguished-lecture-series-dr-lorena-barba-associate-professor-department-mechanical-aerospace-engineering-george-washington-university/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20181004T170000
DTEND;TZID=UTC:20181004T183000
DTSTAMP:20260414T225931
CREATED:20180907T143856Z
LAST-MODIFIED:20180914T135301Z
UID:14384-1538672400-1538677800@entrepreneurship.columbia.edu
SUMMARY:Data Science Institute-Industry-Innovation Seminar: GE
DESCRIPTION:OPEN TO ALL\n\n\nREGISTER HERE\n\n\nDr. Paul Ardis\, Research Mission Leader at GE Global Research | “Going Further: Changing the Airline Industry Beyond the Aircraft”\n\n \nThursday\, October 4\, 2018\n5:00PM – 6:30PM\nSchapiro CEPSR\, Davis Auditorium (412)\n \nAbstract: Analytics are opening up new possibilities in the aviation sector as we think beyond the airplane during flight. Putting together GE’s expertise in AI for manufacturing and service with airline passenger analytics and intelligent supply chains\, we are working towards a future where efficiency and agility is realized to maximize efficiency and minimize disruption.\n\nBio: Dr. Ardis has been leading AI research in the aviation sector at GE Global Research since 2013\, having previously served as a professor at Rochester Institute of Technology and as a research contractor to the Air Force Research Laboratory.
URL:https://entrepreneurship.columbia.edu/event/data-science-institute-industry-innovation-seminar-ge/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20180928T100000
DTEND;TZID=UTC:20180928T113000
DTSTAMP:20260414T225931
CREATED:20180907T143615Z
LAST-MODIFIED:20180927T170225Z
UID:14382-1538128800-1538134200@entrepreneurship.columbia.edu
SUMMARY:Data Science Institute | Annual Town Hall | 2018
DESCRIPTION:OPEN TO ALL\n\nREGISTER HERE\n\nFriday\, September 28\, 2018\n10:00AM – 11:30AM\n** NOTE NEW LOCATION: Maison Francaise | East Gallery | Buelle Hall**\n\nThe Data Science Institute of Columbia University’s mission is to advance the state-of-the-art in data science; to transform all fields\, professions\, and sectors through the application of data science; and to ensure the responsible use of data for the benefit of society.\n\nThe Institute invites the Columbia Community to join us at our annual Town Hall to hear about recent highlights and to discover existing and emerging opportunities for engagement with the Institute.
URL:https://entrepreneurship.columbia.edu/event/data-science-institute-annual-town-hall-2018/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20180926T170000
DTEND;TZID=UTC:20180926T183000
DTSTAMP:20260414T225931
CREATED:20180907T143344Z
LAST-MODIFIED:20180907T143344Z
UID:14380-1537981200-1537986600@entrepreneurship.columbia.edu
SUMMARY:Cross-device User Clustering at Adobe
DESCRIPTION:OPEN TO ALL\n\nREGISTER HERE\n\nWednesday\, September 26\, 2018\n5:00PM – 6:30PM\nSchapiro CEPSR\, Davis Auditorium (412)\n \nABSTRACT: As people now engage with digital properties using a myriad of devices such as laptops\, smart phones\, tablets\, connected TVs and gaming consoles\, the traditional cookie-based or device-level views of online user interaction are too narrow. Even when using a single device\, a person may be assigned multiple IDs due to cookie churn or the use of different browsers. Marketers are looking through a fragmented lens and are spending their marketing dollars without understanding more than a fractional part of consumer interactions.\n\n\nThis talk will give an overview of how Adobe is tackling this problem using graph processing techniques\, going over our journey from the initial research ideas to a fully productized product that works at scale running in the cloud while respecting user privacy. Focus will be on our open-source technology stack\, including Apache Spark\, GraphX\, OpenTSDB\, … along with a description of our algorithms and the challenges we went through to run them at very large scale on Amazon Web Services.\n\nBio: Charles is a data engineer/scientist at Adobe\, where he has been involved on many projects revolving around big data\, infrastructure and data science. Passionate about data\, Charles is constantly on the lookout for the newest technologies and applications related to data science at scale. After graduating with a Master’s degree in Computer Science and Artificial Intelligence from EPITA\, France\, in 2010\, Charles has since focused his career on the online advertising industry\, working at an ad network\, a Demand-Side Platform\, and currently Adobe’s Data Management Platform.
URL:https://entrepreneurship.columbia.edu/event/cross-device-user-clustering-adobe/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20180914T130000
DTEND;TZID=UTC:20180914T143000
DTSTAMP:20260414T225931
CREATED:20180907T142911Z
LAST-MODIFIED:20180913T182821Z
UID:14376-1536930000-1536935400@entrepreneurship.columbia.edu
SUMMARY:Data for Good (or Scary AI and Other Dangers of Big Data)
DESCRIPTION:OPEN TO ALL \nRSVP HERE \n  \nFriday\, September 14\, 2018\nLocation: Pupin 428\n1:00PM – 2:30PM\n\n\nAbstract: In our data-rich world\, we in the technology community have a responsibility to ensure that we use data for good. In this talk\, under the acronym FATES\, I will focus on these aspects of the responsible use of data: fairness\, accountability\, transparency\, ethics\, safety and security. I will give examples of how data-hungry AI-based systems can lead to harmful decisions and even fatal errors. But I will also give examples of new techniques we can use to reduce some of these bad effects. Above all\, we need to work with ethicists\, social scientists\, and humanists to build systems with FATES in mind as we design our technology not after we deploy it. \n  \nBio: Biography: Jeannette M. Wing is Avanessians Director of the Data Science Institute and Professor of Computer Science at Columbia University. From 2013 to 2017\, she was a Corporate Vice President of Microsoft Research. She is Consulting Professor of Computer Science at Carnegie Mellon where she twice served as the Head of the Computer Science Department and had been on the faculty since 1985. From 2007-2010 she was the Assistant Director of the Computer and Information Science and Engineering Directorate at the National Science Foundation. She received her S.B.\, S.M.\, and Ph.D. degrees in Computer Science\, all from the Massachusetts Institute of Technology. \nProfessor Wing’s general research interests are in the areas of trustworthy computing\, specification and verification\, concurrent and distributed systems\, programming languages\, and software engineering. Her current interests are in the foundations of security and privacy\, with a new focus on trustworthy AI. She was or is on the editorial board of twelve journals\, including the Journal of the ACM and Communications of the ACM. \nShe is currently a member of: the National Library of Medicine Blue Ribbon Panel\, the Science\, Engineering\, and Technology Advisory Committee for the American Academy for Arts and Sciences; the Board of Trustees for the Institute of Pure and Applied Mathematics; the Advisory Board for the Association for Women in Mathematics; and the Alibaba DAMO Technical Advisory Board. She has been chair and/or a member of many other academic\, government\, and industry advisory boards. She received the CRA Distinguished Service Award in 2011 and the ACM Distinguished Service Award in 2014. She is a Fellow of the American Academy of Arts and Sciences\, American Association for the Advancement of Science\, the Association for Computing Machinery (ACM)\, and the Institute of Electrical and Electronic Engineers (IEEE).
URL:https://entrepreneurship.columbia.edu/event/data-good-scary-ai-dangers-big-data/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20180913T160000
DTEND;TZID=UTC:20180913T180000
DTSTAMP:20260414T225931
CREATED:20180907T143116Z
LAST-MODIFIED:20180910T155032Z
UID:14378-1536854400-1536861600@entrepreneurship.columbia.edu
SUMMARY:C++: An Invisible Foundation
DESCRIPTION:OPEN TO ALL\n\n\nREGISTER HERE\n\n\nThursday\, September 13th\, 2018\n4:00 p.m. – 5:00 p.m. Lecture\n5:00 p.m. – 6:00 p.m. Reception\nBrown Institute | 2nd Floor\, Pulitzer Hall (2950 Broadway)\n\n\n\nC++ is one of the key foundations of our software. It is invisible to most people because they use it only indirectly. It’s in your computer and your phone. It’s in the machines that manufacture\, your computer\, and your phone. It’s in most cars\, including all the self-driving ones. It’s on Mars\, and in deep sea-robots. It’s what runs your Java virtual machine and your Python AI/ML scripts.\n\nIn this Distinguished Lecture\, Dr. Stroustrup will briefly explain what technical aspects of C++ makes it so useful. He will focus on design principles\, but also touch upon resource management and what it takes to be efficient in various contexts. Finally\, he will comment on the challenges facing the C++ community.\n\nAbout Bjarne Stroustrup\n\nDr. Bjarne Stroustrup is the designer and original implementer of C++ as well as the author of The C++ Programming Language (Fourth Edition)\, A Tour of C++\, Programming: Principles and Practice using C++ (Second Edition)\, and many popular and academic publications. Dr. Stroustrup is a Managing Director in the technology division of Morgan Stanley in New York City as well as a visiting professor in Columbia University’s Department of Computer Science. He is a member of the U.S. National Academy of Engineering\, and an IEEE\, ACM\, and CHM fellow. He received the 2018 Charles Stark Draper Prize\, the IEEE Computer Society’s 2018 Computer Pioneer Award\, and the 2017 IET Faraday Medal. His research interests include distributed systems\, design\, programming techniques\, software development tools\, and programming languages. He is actively involved in the ISO standardization of C++. He holds a master’s degree in mathematics from Aarhus University\, where he is an honorary professor\, and a Ph.D. in computer science from the University of Cambridge\, where he is an honorary fellow of Churchill College.\n\nThe Distinguished Lectures in Computational Innovation series highlights programmers\, data scientists\, and other practitioners from the private sector who lead cutting-edge technology initiatives such as Python\, C++\, and the Open Source Initiative. The events include a presentation\, question & answer session\, and post-event networking reception.\n\nAll Columbia University students\, faculty\, postdocs\, and administrators are welcome to register for and attend these events.
URL:https://entrepreneurship.columbia.edu/event/c-invisible-foundation/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20180328T090000
DTEND;TZID=UTC:20180328T170000
DTSTAMP:20260414T225931
CREATED:20171208T205951Z
LAST-MODIFIED:20171208T205951Z
UID:11733-1522227600-1522256400@entrepreneurship.columbia.edu
SUMMARY:Data Science Day (Event)
DESCRIPTION:Open to all \nRegiser here \nCelebrating 5 years of Data Science at Columbia University \nJoin us for demos and lightning talks by Columbia researchers presenting their latest work in data science. The event provides a forum for innovators in academia\, industry and government to connect. \nRoone Arledge Auditorium\nLerner Hall | Columbia University\n2920 Broadway\, New York\, NY 10027
URL:https://entrepreneurship.columbia.edu/event/data-science-day-event/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20180227T110000
DTEND;TZID=UTC:20180227T121500
DTSTAMP:20260414T225931
CREATED:20180219T170656Z
LAST-MODIFIED:20180219T170656Z
UID:12603-1519729200-1519733700@entrepreneurship.columbia.edu
SUMMARY:Data-Driven Discovery and Decision Making - A Paradigm Shift for Large-Scale Experimental Science
DESCRIPTION:Tuesday\, February 27\, 2018\n11:00AM-12:15PM\nCEPSR 414\, DAVIS AUDITORIUM\n\n“Data-Driven Discovery and Decision Making – A Paradigm Shift for Large-Scale Experimental Science” \nNew instrument technologies are enabling a new generation of in-situ and in-operando experiments\, with extremely fine spatial and temporal resolution\, that allows researchers to observe as physics\, chemistry and biology are happening. These new methodologies go hand in hand with an exponential growth in data volumes and rates – petabyte scale data collections and terabyte/sec. At the same time\, scientists are pushing for a paradigm shift. As they can now observe processes in intricate details\, they want to analyze\, interpret and control those processes. Given the multitude of voluminous\, heterogenous data streams involved in every single experiment\, novel real-time\, data-driven analysis and decision support approaches are needed to realize their vision. This talk will discuss state-of-the-art streaming analysis for experimental facilities\, its challenges and early successes. It will present work currently carried out at Brookhaven National Laboratory and identify areas for collaboration. \nKerstin Kleese van Dam is the director of the Computational Science Initiative (CSI) at the Department of Energy’s Brookhaven National Laboratory (BNL)\, in Long Island\, NY. With 100 petabytes\, BNL hosts the second largest scientific data archive in the US and the fourth largest in the world\, it processes annually in access of 400 petabytes of scientific results. \nCSI conducts leading edge computer science and applied mathematics research to address the associated analysis challenges\, specific focus areas are machine learning\, visual analytics and programming models. \n \nBefore she joined BNL Kerstin was associated division director at Pacific Northwest National Laboratory\, Director of Computing at University College London Medical School and Data Management Group Lead at the Science and Technology Facilities Council in the UK.\n \nHosted by Prof. Steven Nowick (Dept. of Computer Science)
URL:https://entrepreneurship.columbia.edu/event/data-driven-discovery-decision-making-paradigm-shift-large-scale-experimental-science/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20180220T173000
DTEND;TZID=UTC:20180220T193000
DTSTAMP:20260414T225931
CREATED:20180219T203809Z
LAST-MODIFIED:20180219T203809Z
UID:12608-1519147800-1519155000@entrepreneurship.columbia.edu
SUMMARY:Data for Good
DESCRIPTION:LOCATION\nBloomberg Center\, Cornell Tech\n2 West Loop Road\nNew York\, NY 10044 \nFebruary 20\, 2018\nReception: 5:30pm-6:30pm\nTalk: 6:30pm-7:30pm  \nEvery field has data. We use data to discover new knowledge\, to interpret the world\, to make decisions\, and even to predict the future. The recent convergence of big data\, cloud computing\, and novel machine learning algorithms and statistical methods is causing an explosive interest in data science and its applicability to all fields. This convergence has already enabled the automation of some tasks that better human performance. The novel capabilities we derive from data science will drive our cars\, treat disease\, and keep us safe. At the same time\, such capabilities risk leading to biased\, inappropriate\, or unintended action. The design of data science solutions requires both excellence in the fundamentals of the field and expertise to develop applications which meet human challenges without creating even greater risk. \nThe Data Science Institute at Columbia University promotes “Data for Good”: using data to address societal challenges and bringing humanistic perspectives as—not after—new science and technology is invented. Started in 2012\, the Institute is now a university-level institute representing over 250 affiliated faculty from 12 different schools across campus. Data science literally touches every corner of the university. \nIn this talk\, Jeannette Wing\, Director of the Data Science Institute\, will present the vision on how the Institute plans to address some of the key challenges and opportunities of data science\, highlighting educational and research activities\, as well as future initiatives that may directly impact the data science community at Columbia\, New York City\, and beyond.
URL:https://entrepreneurship.columbia.edu/event/data-for-good-2/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20180216T120000
DTEND;TZID=UTC:20180216T133000
DTSTAMP:20260414T225931
CREATED:20180215T170318Z
LAST-MODIFIED:20180219T170546Z
UID:12601-1518782400-1518787800@entrepreneurship.columbia.edu
SUMMARY:Data for Good
DESCRIPTION:OPEN TO ALL\n\nFriday\, February 16\, 2018\n12:00PM-1:30PM\nCEPSR 750\n\n\nIn this talk\, we discuss a systematic evaluation of the impact of financial regulations concerning the collateralization of derivative trades on systemic risk – a topic that has been vigorously discussed since the financial crisis in 2007/08. Experts often disagree on the efficacy of these regulations. Compounding this problem banks regard their trade data required for a full analysis as proprietary. We adapt a simulation technology combining advances in graph theory to randomly generate entire financial systems sampled from realistic distributions with a novel open source risk engine to compute risks in financial systems under different regulations. This allows us to consistently evaluate\, predict and optimize the impact of financial regulations on all levels – from a single trade to systemic risk – before it is implemented. The resulting data set is accessible to contemporary data science techniques like data mining\, anomaly detection and visualization. We find that collateralization reduces the costs of resolving a financial system in crisis\, yet it does not change the distribution of those costs and can have adverse effects on individual participants in extreme situations. \nRemote participants can register for online streaming in advance at: \nhttps://columbiauniversity.zoom.us/meeting/register/4e9e74be7f16abb08c34be5db4a05ad8 \nJointly sponsored by the Data Science Institute and the Institute for Social and Economic Research and Policy
URL:https://entrepreneurship.columbia.edu/event/data-for-good/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20171010T080000
DTEND;TZID=UTC:20171010T170000
DTSTAMP:20260414T225931
CREATED:20170728T174259Z
LAST-MODIFIED:20170829T201347Z
UID:9140-1507622400-1507654800@entrepreneurship.columbia.edu
SUMMARY:Biopharmaceutical Product Development & Data Science Symposium (Event)
DESCRIPTION:OPEN TO ALL \nSAVE THE DATE\nTuesday\, October 10\, 2017\, 8am–5pm\nNew Jersey Institute of Technology\, NJIT Campus Center Atrium\n150 Bleeker Street\, Newark\, NJ 07103 \nKEYNOTE SPEAKERS: \nDr. Jacqueline Law\nGlobal Head & VP\, Real World Data Science\nRoche/Genentech \nDr. Shahram Ebadollahi\nChief Technology Officer\nIBM Watson Health \nThe symposium will highlight two areas. Morning sessions will address the application of data analytics and big data in drug discovery\, preclinical and clinical development. The afternoon session will examine how data analytics and big data can impact process development and manufacturing of biopharmaceutical products. \nREGISTER HERE.
URL:https://entrepreneurship.columbia.edu/event/biopharmaceutical-product-development-data-science-symposium/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20170922T100000
DTEND;TZID=UTC:20170922T110000
DTSTAMP:20260414T225931
CREATED:20170915T152924Z
LAST-MODIFIED:20170915T152924Z
UID:10412-1506074400-1506078000@entrepreneurship.columbia.edu
SUMMARY:Data Science Institute Colloquium Series Event: What Can Deep Learning Learn from Linear Regression
DESCRIPTION:OPEN TO ALL \nABSTRACT \nWhen training large-scale deep neural networks for pattern recognition\, hundreds of hours on clusters of GPUs are required to achieve state-of-the-art performance. Improved optimization algorithms could potentially enable faster industrial prototyping and make training contemporary models more accessible. \nIn this talk\, I will attempt to distill the key difficulties in optimizing large\, deep neural networks for pattern recognition. In particular\, I will emphasize that many of the popularized notions of what make these problems “hard” are not true impediments at all. I will show that it is not only easy to globally optimize neural networks\, but that such global optimization remains easy when fitting completely random data. \nI will argue instead that the source of difficulty in deep learning is a lack of understanding of generalization—namely understanding behavior on new and unseen data. By appealing to standard concepts from linear regression\, I will describe why certain popular theories of generalization fail to explain the success of large neural nets. I will close with some possible approaches to patching this theory and guiding the engineering of deep learning models with enormous capacity. \n 
URL:https://entrepreneurship.columbia.edu/event/data-science-institute-colloquium-series-event-can-deep-learning-learn-linear-regression/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20170920T163000
DTEND;TZID=UTC:20170920T180000
DTSTAMP:20260414T225931
CREATED:20170915T152633Z
LAST-MODIFIED:20170915T152633Z
UID:10409-1505925000-1505930400@entrepreneurship.columbia.edu
SUMMARY:Data\, Ethics and Decision-Making Lecture Series: Dr. Jeanette M. Wing\, Avanessians Director of the Data Science Institute
DESCRIPTION:OPEN TO ALL \nABSTRACT: \nThe Data\, Ethics\, and Decision-making Speaker Series hosted by the Institute for Social and Economic Research and Policy (ISERP) presents Dr. Jeannette M. Wing\, Avanessians Director of the Data Science Institute and Professor of Computer Science in at Columbia University\, on “Using Data for Good: What does it mean?“. Professor Wing will be laying out her vision for the Institute\, which will focus on her desire to think seriously about the definition and practice of using data for good.
URL:https://entrepreneurship.columbia.edu/event/data-ethics-decision-making-lecture-series-dr-jeanette-m-wing-avanessians-director-data-science-institute/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20170905T110000
DTEND;TZID=UTC:20170905T120000
DTSTAMP:20260414T225931
CREATED:20170905T134650Z
LAST-MODIFIED:20170905T135252Z
UID:10202-1504609200-1504612800@entrepreneurship.columbia.edu
SUMMARY:Data Science Institute Colloquium: Kevin Murphy | Research Scientist\, Google (Keynote)
DESCRIPTION:OPEN TO ALL – NO REGISTRATION REQUIRED \n\n\nTowards Machines that Perceive and Communicate \nABSTRACT: I will summarize some recent work related to visual scene understanding and “grounded” language understanding. In particular\, I will discuss a connected group of results from my group at Google: \n– Our DeepLab system for semantic segmentation (PAMI’17) [1].\n– Our object detection system (CVPR ‘17 and 1st place in COCO’16) [2].\n– Our instance segmentation system (2nd place in COCO’16)\n– Our person detection/pose estimation system [3] (CVPR’17 and 2nd place in COCO’16)\n– Visually grounded referring expressions (CVPR’16) [4].\n– Discriminative image captioning (CVPR’17) [5].\n– Optimizing semantic metrics for image captioning using RL (ICCV’17) [6]\n– Generative models of visual imagination (submitted to NIPS’17). \nI will explain how each of these pieces can be combined to develop systems that can better understand images and words. \nBIO: Bio: Kevin Murphy is a research scientist at Google in Mountain View\, California\, where he works on AI\, machine learning\, and computer vision. Before joining Google in 2011\, he was an associate professor (with tenure) of computer science and statistics at the University of British Columbia in Vancouver\, Canada. Before starting at UBC in 2004\, he was a postdoc at MIT. Kevin got his BA from U. Cambridge\, his MEng from U. Pennsylvania\, and his PhD from UC Berkeley. He has published over 80 papers in refereed conferences and journals\, as well as an 1100-page textbook called “Machine Learning: a Probabilistic Perspective” (MIT Press\, 2012)\, which was awarded the 2013 DeGroot Prize for best book in the field of Statistical Science. Kevin is also the (co) Editor-in-Chief of JMLR (the Journal of Machine Learning Research). \n\n\nEvent Contact Information: \nData Science Institute\n212-854-5660\ndatascience@columbia.edu
URL:https://entrepreneurship.columbia.edu/event/data-science-institute-colloquium-kevin-murphy-research-scientist-google/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20170511T180000
DTEND;TZID=UTC:20170511T190000
DTSTAMP:20260414T225931
CREATED:20170426T194538Z
LAST-MODIFIED:20170426T194538Z
UID:8124-1494525600-1494529200@entrepreneurship.columbia.edu
SUMMARY:Improving Health-Care: Challenges and Opportunities for Reinforcement Learning
DESCRIPTION:Reinforcement learning offers a powerful paradigm for automatically discovering and optimizing sequential treatments for chronic and life-threatening diseases. In particular\, we will focus on how data collected in multi-stage sequential trials can be used to automatically generate treatment strategies that are tailored to patient characteristics and time-dependent outcomes. We will also examine promising methods to improve the efficiency of clinical trials through adaptation. Examples will be drawn from several ongoing research projects on developing new treatment strategies for epilepsy\, mental illness\, diabetes\, and cancer. \nREGISTER HERE \nThis event is part of the NYC Data Science Seminar Series\, organized by MSR NYC\, Facebook\, NYU Center for Data Science\, Columbia University\, and Cornell Tech\, with the Jacobs Technion-Cornell Institute.\nMore information can be found here.
URL:https://entrepreneurship.columbia.edu/event/improving-health-care-challenges-opportunities-reinforcement-learning/
LOCATION:Davis Auditorium\, Schapiro\, New York City\, 10027\, United States
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20170511T160000
DTEND;TZID=UTC:20170511T173000
DTSTAMP:20260414T225931
CREATED:20170509T204122Z
LAST-MODIFIED:20170509T204122Z
UID:8248-1494518400-1494523800@entrepreneurship.columbia.edu
SUMMARY:Data Science Institute-Industry-Innovation Seminar: Peter Marx\, General Electric
DESCRIPTION:Peter Marx\, Vice President\, Advanced Projects\, GE Digital Adjunct Professor\, USC \nTITLE: How the New Availability of Urban and Industrial Data are Impacting Our World from Public Safety to Jet Engines \nThis talk discusses how newly available data from cities and industry\, from sensing and activities\, and from transactions and services are driving change across our world. Cities are increasingly using data to drive new efficiencies and insights in the urban world. For example\, policing and public safety services are ever-more data-driven and transparent with data being more widely distributed than at any point in the past. Similarly\, industry is changing from being traditionally physical into becoming more digital through the distribution of data. New availability of sensing data through the emerging Industrial Internet of Things (IIoT)\, for example\, is allowing for increasing levels of predictive maintenance and qualities of service. Highly personalized healthcare is now possible because of data being made available digitally from everywhere from our worn devices to imaging of our bodies to our genetics themselves. \nThis discussion will draw on General Electric?s activities driving the Industrial Internet of Things (IIoT) and Predix\, as well as from leading cities like Los Angeles\, Singapore\, and Dubai. We will touch upon technologies such as machine learning (AI) and other types of analytics\, as well as computer vision (CV)\, connectivity (5G and private LTE)\, and mixed reality. \nCLICK HERE FOR MORE INFORMATION.
URL:https://entrepreneurship.columbia.edu/event/data-science-institute-industry-innovation-seminar-peter-marx-general-electric/
LOCATION:Schapiro Building Room 750\, 530 West 120th Street\, New York City\, 10027\, United States
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20170511T160000
DTEND;TZID=UTC:20170511T173000
DTSTAMP:20260414T225931
CREATED:20170503T183217Z
LAST-MODIFIED:20170503T183217Z
UID:8192-1494518400-1494523800@entrepreneurship.columbia.edu
SUMMARY:Data Science Institute-Industry-Innovation Seminar: Surveillance and Social Situational Awareness
DESCRIPTION:This talk will describe a variety of methods that have been developed for the purposes of understanding group level social behaviors using stand-off video surveillance methods. Three main topics are considered: 1) the GE Sherlock System: a comprehensive approach to capturing and analyzing non-verbal cues of persons in crowd/group level interactions\, 2) One Shot Learning: a new approach to crowd level behavior recognition based on the concept that a new behavior can be recognized with as little as a single example and 3) Agent Based Inference: a novel approach to the analysis of individual cognitive states of person?s interacting in a group or crowd level social interactions. The talk starts with a description of the GE Sherlock system which encompasses methods such as person tracking in crowds\, dynamic PTZ camera control\, facial analytics from a distance such as gaze estimation and expression recognition\, upper body affective pose analysis and the inference of social states such as rapport and hostility. The talk then discusses how cues derived from the Sherlock system can be used to construct semantically meaningful behavior descriptors or affects allowing for signature matching between behaviors which can be viewed as a form of one shot learning. Going beyond affects based on direct observation\, we argue that more meaningful affects can be constructed via the inference of the cognitive states of each individual. To this end we introduce the Agent Based Inference framework. The talk concludes with a discussion of how such methods are making their way into commercial use via efforts such as the intelligent city\, the intelligent airport and the intelligent hospital. \nGET MORE INFORMATION HERE.
URL:https://entrepreneurship.columbia.edu/event/data-science-institute-industry-innovation-seminar-surveillance-social-situational-awareness/
LOCATION:CEPSR 750\, New York City\, 10027
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20170426T163000
DTEND;TZID=UTC:20170426T173000
DTSTAMP:20260414T225931
CREATED:20170426T193440Z
LAST-MODIFIED:20170426T193440Z
UID:8122-1493224200-1493227800@entrepreneurship.columbia.edu
SUMMARY:Recent Advances in Post-Selection Statistical Inference
DESCRIPTION:The Joint Colloquium Series\, hosted by the Data Science Institute and the Department of Statistics\, presents Recent Advances in Post-Selection Statistical Inference” with Professor Robert Tibshirani of Stanford University. \nIn this era of big data and complex statistical modeling\, scientists use sophisticated computational tools to search through a large number of models\, looking for meaningful patterns. The challenge is then to judge the strength of a large number of apparent associations that have been found. This statistical problem has become known as ?Post-selection inference\,? the assessment of significance and effect sizes from a data-set after mining the same data to find these associations. In this talk I will discuss new methods for computing p-values and confidence intervals in regression\, that correctly account for the adaptive selection of the model. This is joint work with Jonathan Taylor\, Ryan Tibshirani\, Will Fithian and Richard Lockhart. \nRegistration not required; more data available here.
URL:https://entrepreneurship.columbia.edu/event/recent-advances-post-selection-statistical-inference/
LOCATION:Davis Auditorium\, Schapiro\, New York City\, 10027\, United States
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20170405T080000
DTEND;TZID=UTC:20170405T170000
DTSTAMP:20260414T225931
CREATED:20160914T191558Z
LAST-MODIFIED:20170328T011548Z
UID:4819-1491379200-1491411600@entrepreneurship.columbia.edu
SUMMARY:Third Annual Data Science Day
DESCRIPTION:AGENDA\nKeynote Speaker: Alfred Spector\nChief Technology Officer and Head of Engineering at Two Sigma \n“Opportunities and Perils in Data Science”\nLightning Talk Sessions:\nOur Connected World\n\nSuman Jana\, Assistant Professor of Computer Science\nSusan McGregor\, Assistant Professor of Journalism;\nAssistant Director\, Tow Center for Digital Journalism\nHollie Russon-Gilman\, Lecturer in International and Public Affairs \nApplications of Data Science\nStefano Fusi\, Associate Professor of Neuroscience\nAndrew Gelman\, Professor of Statistics and Political Science\nAndreas Christian Mueller\, Lecturer in the Discipline of Data Science\nMingoo Seok\, Assistant Professor of Electrical Engineering \nPatient Driven Health Care\nKenrick Dwain Cato\, Assistant Professor of Nursing\nYing Kuen K. Cheung\, Professor of Biostatistics\nNoemie Elhadad\, Associate Professor of Biomedical Informatics \nSharing Economy\nXuan Sharon Di\, Assistant Professor of Civil Engineering and Engineering Mechanics\nConstantinos Maglaras\, David and Lyn Silfen Professor of Business\nEric L. Talley\, Isidor and Seville Sulzbacher Professor of Law \n\n\nLAST YEAR’S DATA SCIENCE DAY \nColumbia’s Data Science Institute held its second annual all-day conference devoted to big data on April 6\, and it was information overload in the best sense. \nKeynote speaker Dan Doctoroff talked about the revolutionary impact data science will have on people and our urban environment.\n—Photo by Timothy Lee Photographers \nAttendees got a chance to learn all about key research underway by Columbia faculty and researchers who are leading the charge in this burgeoning field. Disciplines as diverse as engineering\, economics\, astrophysics\, and history were represented throughout the day on data science challenges as varied as gang violence prevention\, measurements of urban pollution\, kidney disease prediction\, encrypted search\, and much more. \nSpeaking to a packed audience in Roone Arledge Auditorium\, Columbia Engineering Dean Mary C. Boyce underscored the Institute’s crucial role since its inception four years ago in pushing the innovation\, discussion\, and education of data science\, across multiple fields. “The Institute has really acted to catalyze data science across the University\,” she said\, stressing that the initiative has ignited faculty and student collaboration. “We’re also transforming the way we do research and the way we teach across campus\,” she added\, pointing to new programs in data science\, including the MS program\, a certificate program for professionals\, and several new courses in data science. [Rest of Story] \nIn his keynote address\, Sidewalk Labs CEO Dan Doctoroff gave a riveting talk about “the coming technological revolution in cities.” Doctoroff\, former CEO of Bloomberg L.P. and a former deputy mayor of New York City under Michael Bloomberg\, started Sidewalk Labs to bridge the gap between technology and cities. He said harnessing data science—computing power\, sensing\, the power of social networks—will have a revolutionary impact on people and our urban environment\, essentially developing the smartest of all cities that will lead humanity into the future.
URL:https://entrepreneurship.columbia.edu/event/third-annual-data-science-day/
CATEGORIES:Columbia Data Science Institute
ATTACH;FMTTYPE=image/jpeg:https://entrepreneurship.columbia.edu/wp-content/uploads/2016/09/DSI.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20170302T170000
DTEND;TZID=UTC:20170302T183000
DTSTAMP:20260414T225931
CREATED:20170111T171456Z
LAST-MODIFIED:20170222T220803Z
UID:6530-1488474000-1488479400@entrepreneurship.columbia.edu
SUMMARY:YES\, You Really Can Use This! -- Applying Data Science to Real-World Problems
DESCRIPTION:ABSTRACT:\nBooz Allen Hamilton’s Dan Liebermann and Ben Arancibia will cover what it takes to get data science done in the real world.  They will be sharing stories from the trenches – covering experiences and lessons learned from turning data science theory into reality when the problem (and the solution) are far from known.  The talk will heavily engage the audience to hear their perspective\, and cover the approach Booz Allen took to solve its clients’ problems.  The goal is to get the audience thinking about what they would do in these situations and how they would apply their classroom experience. \nBIOGRAPHY\nDan Liebermann\, a Lead Associate at Booz Allen Hamilton\, has a track-record of leading successful analytical and technical engagements while drawing on his project management skills. Dan has ten years of experience conducting data analysis and managing data science projects where he has used his combination of consulting and data science skills to help his clients derive the most value from their data.  His work has included applications in statistics\, machine learning\, data mining\, and population modeling\, in addition to supporting the organizational and people sides of developing a data science capability.  Dan has used tools such as R\, Bayesialab\, and Excel to perform statistical and analytical techniques.  Dan holds a M.P.A. with a specialization in Management from Columbia University’s School of International and Public Affairs\, and a B.A. from Carnegie Mellon University. \nBen Arancibia\, a Lead Data Scientist in Booz Allen Hamilton’s Strategic Innovation Group has significant experience in statistical analysis\, Big Data analytical processes\, database development\, as well as\, the R\, and Python programming languages. Ben’s work includes applied data science\, building Big Data systems\, and web application development. Prior to working for Booz Allen\, Ben worked extensively in international development managing software development projects and as a GIS developer. Ben holds a MS in Data Science from the City University of New York where his graduate research focused on fraud detection in financial foreign assistance transactions. He holds an undergraduate degree from William and Mary in quantitative economics.
URL:https://entrepreneurship.columbia.edu/event/yes-really-can-use-applying-data-science-real-world-problems/
LOCATION:Davis Auditorium\, Schapiro\, New York City\, 10027\, United States
CATEGORIES:Columbia Data Science Institute
ATTACH;FMTTYPE=image/jpeg:https://entrepreneurship.columbia.edu/wp-content/uploads/2016/11/Collaboratory.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20170301T230000
DTEND;TZID=UTC:20170301T230500
DTSTAMP:20260414T225931
CREATED:20170113T192058Z
LAST-MODIFIED:20170113T192058Z
UID:6567-1488409200-1488409500@entrepreneurship.columbia.edu
SUMMARY:DEADLINE: Data Science Day Demo and Poster Submissions
DESCRIPTION:The Data Science Institute is excited to begin soliciting demos and posters from CU faculty and their students to be shown at our upcoming Data Science Day @ Columbia University: \nWHEN:                 Wednesday\, April 5\, 2017\nWHERE:               Roone Arledge Auditorium\, Lerner Hall\nTIME:                    [TENTATIVE] Invited Speakers: 9AM-2PM | Demos + Posters: 2PM-5PM \nSUBMISSION DEADLINE: Wednesday\, March 1st\, 2017\nNOTIFICATION DATE: Week of March 13th\, 2017 \nThe audience will be mainly people from industry and government interested in learning more about research going on at the Institute.  We are excited to showcase our research through demos and posters to generate industry enthusiasm prompting further engagement with the Institute. \nSubmissions selected for presentation will receive free admission to the event.  \nInformation about last year’s Data Science Day may be found via here.
URL:https://entrepreneurship.columbia.edu/event/deadline-data-science-day-demo-poster-submissions/
CATEGORIES:Columbia Data Science Institute
ATTACH;FMTTYPE=image/jpeg:https://entrepreneurship.columbia.edu/wp-content/uploads/2017/01/Data-Science-Day-2017-4K-Network.jpg
END:VEVENT
END:VCALENDAR