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X-WR-CALDESC:Events for Columbia Entrepreneurship
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BEGIN:VEVENT
DTSTART;TZID=UTC:20191025T140000
DTEND;TZID=UTC:20191025T153000
DTSTAMP:20260414T211301
CREATED:20190930T143738Z
LAST-MODIFIED:20190930T143738Z
UID:18674-1572012000-1572017400@entrepreneurship.columbia.edu
SUMMARY:FinTech Lecture Series - Where on Earth is AI Headed?
DESCRIPTION:Free\, open to the public\, and does not require registration.\n\n\n\nWhere on Earth is AI Headed?\n\n\nFriday\, October 25\, 2019\n\n2:00 PM – Lecture\n\n3:00 PM – Reception\n\n \nSchapiro CEPSR – Davis Auditorium\n\n530 West 120th Street\, 4th Floor\nNew York\, NY 10027\n\n \nSpeaker: Tom M. Mitchell – Founders University Professor\, School of Computer Science\n\n \nSpeaker Biography: Tom M. Mitchell is the Founders University Professor in the School of Computer Science at Carnegie Mellon University\, where he created the world’s first academic Machine Learning Department. Mitchell’s research explores machine learning theory\, algorithms and applications\, as well as the impact of AI on society. He has testified to the U.S. Congress several times on AI impacts on society\, and he co-chaired the 2017 U.S. National Academy study on “Information Technology\, Automation\, and the U.S. Workforce.” Mitchell advises a variety of young and old companies internationally on their AI product and business strategies\, and his research has been featured in popular press from the New York Times\, to CCTV (China’s national television network)\, to CBS’s 60 Minutes. He is a member of the U.S. National Academy of Engineering\, a member of the American Academy of Arts and Sciences\, and a Fellow and Past President of the Association for the Advancement of Artificial Intelligence (AAAI).
URL:https://entrepreneurship.columbia.edu/event/fintech-lecture-series-where-on-earth-is-ai-headed/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20191009T173000
DTEND;TZID=UTC:20191009T183000
DTSTAMP:20260414T211301
CREATED:20190930T143616Z
LAST-MODIFIED:20190930T143616Z
UID:18672-1570642200-1570645800@entrepreneurship.columbia.edu
SUMMARY:NYC DS3 Seminar - How Can Machine-Learning Methods Help to Make Scientific Inferences?
DESCRIPTION:Free\, open to the public\, and does not require registration. \n\n\nWednesday\, October 9\, 2019\n\n5:00 PM – 5:30 PM: Welcome\n5:30 PM – 6:30 PM: Talk\n\n \nSchapiro CEPSR – Davis Auditorium\n\n530 West 120th Street\, 4th Floor\nNew York\, NY 10027\n\n \nTalk Abstract: Machine learning in the form of standard supervised classification algorithms is not all that useful or productive in the natural sciences\, because the (effective) goals of these algorithms aren’t very similar to the goals of scientific inquiry. However\, the ML community has delivered great ideas and methods for building\, fitting\, and validating extremely flexible models. I argue that if we want to exploit the good things about ML but achieve truly scientific goals\, we need to do two things: We need to augment or modify the (currently trivial) causal structure of the ML methods to represent our very strong domain-specific beliefs about how the data are generated. And we need to be careful to use ML methods only in the parts of our problems for which we don’t care about the latent structure or parameters (that is\, use them to model nuisances\, not use them to do everything). I give examples from stellar astrophysics where adding ML components into larger causal models has created new scientific capabilities.\n \nSpeaker: Professor David W. Hogg\, NYU|MPIA|Flatiron\n \nSpeaker Biography: After a Ph.D. in Physics from Caltech and a few years at the Institute for Advanced Study\, Hogg came to New York University in 2001 and was granted tenure there in 2007. His work at NYU has ranged from fundamental cosmological measurements to stellar dynamics to planet search and characterization. His work includes a significant engineering component. He spends a part of each year at the Max Planck Institute for Astronomy in Heidelberg\, Germany\, where he is a visiting member of the research staff\, and a part of each week at the Flatiron Institute of the Simons Foundation\, where he is a group leader.
URL:https://entrepreneurship.columbia.edu/event/nyc-ds3-seminar-how-can-machine-learning-methods-help-to-make-scientific-inferences/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20191001T110000
DTEND;TZID=UTC:20191001T123000
DTSTAMP:20260414T211301
CREATED:20190930T143447Z
LAST-MODIFIED:20190930T143447Z
UID:18670-1569927600-1569933000@entrepreneurship.columbia.edu
SUMMARY:Data Science Institute-Industry-Innovation Seminar: Goldman Sachs
DESCRIPTION:Free\, open to the public\, and does not require registration.\n\n\n\n\n\nTuesday\, October 1\, 2019\n\n11:00 AM – 12:30 PM\n\n \nSchapiro CEPSR – Davis Auditorium\n\n530 West 120th Street\, 4th Floor\nNew York\, NY 10027\n\n \nSpeaker #1: Mayur Thakur\, Head of the Data Analytics Group\, Global Compliance Division \nBiography: Mayur Thakur is head of the Data Analytics Group in the Global Compliance Division. He joined Goldman Sachs as a managing director in 2014. Prior to joining the firm\, Mayur worked at Google\, where he designed search algorithms for more than seven years. Previously\, he was an assistant professor of computer science at the University of Missouri. Mayur earned a PhD in Computer Science from the University of Rochester in 2004 and a BTech in Computer Science and Engineering from the Indian Institute of Technology\, Delhi\, in 1999.\n \nSpeaker #2: Suruchi Deodhar\, Vice President\, Goldman Sachs \nBiography: Suruchi is a Vice President at Goldman Sachs\, leading the Communication Risk Engineering team in the Global Compliance Division. She joined the firm in 2015 after completing her PhD in Computer Science from Virginia Tech. Her PhD research focused on developing large scale data integration techniques and big-data systems for evaluation and forecasting of epidemics.
URL:https://entrepreneurship.columbia.edu/event/data-science-institute-industry-innovation-seminar-goldman-sachs/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20190827T160000
DTEND;TZID=UTC:20190827T173000
DTSTAMP:20260414T211301
CREATED:20190827T155421Z
LAST-MODIFIED:20190827T155421Z
UID:18214-1566921600-1566927000@entrepreneurship.columbia.edu
SUMMARY:Deep Learning to Solve Challenging Problems with the SVP of Google AI
DESCRIPTION:OPEN TO ALL \n\nDEEP LEARNING TO SOLVE CHALLENGING PROBLEMS\nSpeaker: Jeff Dean\, SVP Google AI / Lead\, Google Brain Project\nDate: Tuesday\, August 27\, 2019\nTime: 4:00pm – 5:30pm\nLocation: Mudd 451 – Computer Science Building\nLight refreshments will be served \nFor the past eight years\, Google Research teams have conducted research on difficult problems in artificial intelligence\, on building large-scale computer systems for machine learning research\, and\, in collaboration with many teams at Google\, on applying our research and systems to many Google products. As part of our work in this space\, we have built and open-sourced the TensorFlow system (tensorflow.org)\, a widely popular system designed to easily express machine learning ideas and to quickly train\, evaluate\, and deploy machine learning systems. \nWe have also collaborated closely with Google’s platforms team to design and deploy new computational hardware called Tensor Processing Units\, specialized for accelerating machine learning computations. In this talk\, I’ll highlight some of our recent research accomplishments\, and will relate them to the National Academy of Engineering’s Grand Engineering Challenges for the 21st Century\, including the use of machine learning for healthcare\, robotics\, language understanding and engineering the tools of scientific discovery. I’ll also cover how machine learning is transforming many aspects of our computing hardware and software systems. \nThis talk describes joint work with many people at Google.
URL:https://entrepreneurship.columbia.edu/event/deep-learning-to-solve-challenging-problems-with-the-svp-of-google-ai/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20190517T081500
DTEND;TZID=UTC:20190517T180000
DTSTAMP:20260414T211301
CREATED:20190415T200237Z
LAST-MODIFIED:20190415T200237Z
UID:16109-1558080900-1558116000@entrepreneurship.columbia.edu
SUMMARY:Machine Learning in Finance Workshop
DESCRIPTION:OPEN TO ALL\n\nPurchase Tickets Here\n\n\n\n\n\nFriday\, May 17\, 2019 \n8:15 AM – 6:00 PM \nColumbia University – Lerner Hall\n2920 Broadway\, New York\, NY 10027 \nThe Data Science Institute (DSI) at Columbia University and Bloomberg are pleased to announce a workshop on “Machine Learning in Finance”. The workshop will be held at Columbia University under the auspices of the Financial and Business Analytics Center\, one of the constituent centers in the DSI\, and the Center for Financial Engineering. \nBoxed lunches will be provided. There will also be regular coffee breaks throughout the day and a wine and cheese reception after the event.\n \nThe Center for Financial Engineering and the Financial Analytics Center at Columbia University\n\nOrganizer of Machine Learning in Finance Workshop 2019\n\nThe Center for Financial Engineering is an interdisciplinary research center established in 2007 to encourage research on financial engineering and mathematical modeling in finance. It aims at fostering research collaboration among Columbia faculty\, graduate students and affiliates\, facilitating their contacts with financial institutions and corporations and enhancing the visibility of Columbia as a center for research and innovation in financial engineering. \nThe Center’s research activities deal with the pricing and hedging of derivative securities\, the statistical modeling of financial markets\, computational methods in finance\, risk management\, asset allocation\, and portfolio optimization. \nThe Financial Analytics Center is one of the key centers at the Data Science Institute at Columbia University. It brings together expertise in finance theory\, machine learning\, statistics\, signal processing\, operations\, and natural language processing\, and supports collaborations with an appropriately trained student body as well as with the financial industry.
URL:https://entrepreneurship.columbia.edu/event/machine-learning-finance-workshop/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20190509T160000
DTEND;TZID=UTC:20190509T180000
DTSTAMP:20260414T211301
CREATED:20190430T145817Z
LAST-MODIFIED:20190430T145817Z
UID:16214-1557417600-1557424800@entrepreneurship.columbia.edu
SUMMARY:Molecular Innovations for Live Cell Imaging (Presentation)
DESCRIPTION:Thursday\, May 9\, 2019 \n4:00PM – 6:00PM\n\nBuell Hall\n\n515 West 116th Street\n\nNew York\, NY 10027\n\n\nThe fluorescent proteins revolutionized our ability to study protein function directly in the cell by enabling individual proteins to be selectively labeled through genetic encoding of a fluorescent tag. As researchers seek to make increasingly sophisticated dynamic measurements of protein function in the cell to unravel molecular mechanism\, we designed a chemical tag to combine the advantages of genetic encoding with a modular organic fluorophore. With TMP-tag\, the protein of interest is tagged with E. coli dihydrofolate reductase\, which can subsequently be labeled with a cell permeable trimethoprim-fluorophore conjugate. Here we demonstrate that TMP-tag is a robust cellular reagent. We present recent results exploiting the modular nature of the chemical tag to generate TMP-tags for specific applications in single-molecule\, super-resolution\, and multi-color imaging. We look forward to innovations at the interface of chemical tag technology and spectroscopy for biological imaging. \nVirginia W. Cornish graduated summa cum laude from Columbia University with a B.A. in Biochemistry in 1991\, where she did undergraduate research with Professor Ronald Breslow. She earned her Ph.D. in Chemistry with Professor Peter Schultz at the University of California at Berkeley and then was a Postdoctoral Fellow in the Biology Department at M.I.T. under the guidance of Professor Robert Sauer. Virginia joined the faculty of the Chemistry Department at Columbia in 1999\, where she carries out research at the interface of chemistry and biology\, and was promoted to Associate Professor with tenure in 2004 and then Professor in 2007. Her laboratory brings together modern methods in synthetic chemistry and DNA technology to expand the synthetic capabilities of living cells. Her research has resulted in 59 research publications and several patents and currently is supported by multiple grants from the NIH and NSF. Virginia has been recognized for her research by awards including an NSF Career Award (2000)\, a Sloan Foundation Fellowship (2003)\, the Protein Society Irving Sigal Young Investigator Award (2009)\, and the American Chemical Society Pfizer Award in Enzyme Chemistry (2009). In addition to her research and teaching\, Virginia enjoys spending time with her husband and their three children.\n \nPlease contact marley.bauce@columbia.edu with any event related questions.
URL:https://entrepreneurship.columbia.edu/event/molecular-innovations-live-cell-imaging-presentation/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20190403
DTEND;VALUE=DATE:20190404
DTSTAMP:20260414T211301
CREATED:20181114T162350Z
LAST-MODIFIED:20181114T184952Z
UID:15027-1554249600-1554335999@entrepreneurship.columbia.edu
SUMMARY:Data Science Day
DESCRIPTION:OPEN TO ALL \nREGISTER HERE \nWednesday\, April 3\, 2019\n9AM–5PM \nAnnouncing the Keynote Speaker:\nBrad Smith\nPresident of Microsoft \nJoin the Columbia Data Science Institute 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-2/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20190306T180000
DTEND;TZID=UTC:20190306T193000
DTSTAMP:20260414T211301
CREATED:20190114T213101Z
LAST-MODIFIED:20190114T213101Z
UID:15477-1551895200-1551900600@entrepreneurship.columbia.edu
SUMMARY:Data Science Institute-Industry-Innovation Seminar: Amazon
DESCRIPTION:OPEN TO COLUMBIANS\n\nByron Cook\, Professor of Computer Science at University College London (UCL) and Director of Automated Reasoning at Amazon Web Services\n\n \nWednesday\, March 6\, 20108\n6:00PM – 7:30PM\nSchapiro CEPSR\, Davis Auditorium (412)  \n\nAbstract: This talk will discuss the development and use of formal verification tools within Amazon Web Services (AWS) to increase the security assurance of its cloud infrastructure and to help customers secure themselves. I’ll also discuss some remaining challenges that could inspire future research in the community.\n\nBio: Byron Cook is Professor of Computer Science at University College London (UCL) and Director of Automated Reasoning at Amazon Web Services. Byron’s interests include computer/network security\, program analysis/verification\, programming languages\, theorem proving\, logic\, hardware design\, operating systems\, and biological systems. Byron is the founder and leader of Amazon’s Automated Reasoning Group (ARG).e at University College London (UCL) and Director of Automated Reasoning at Amazon Web Services
URL:https://entrepreneurship.columbia.edu/event/data-science-institute-industry-innovation-seminar-amazon/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20190208T153000
DTEND;TZID=UTC:20190208T170000
DTSTAMP:20260414T211301
CREATED:20190114T214834Z
LAST-MODIFIED:20190114T214834Z
UID:15481-1549639800-1549645200@entrepreneurship.columbia.edu
SUMMARY:FDT Center for Intelligent Asset Management - FinTech Lecture Series
DESCRIPTION:OPEN TO ALL COLUMBIANS\n\nFDT Center for Intelligent Asset Management – FinTech Lecture Series\n \n“Fair Algorithms for Machine Learning”\n \nMichael Kearns\n \nFriday\, February 8\, 2019\n\nDavis Auditorium\n3:30 pm lecture followed by 4:30 pm reception\n\nMichael Kearns is a professor in the Computer and Information Science Department at the University of Pennsylvania\, where he holds the National Center Chair. He is also Head of Research in Morgan Stanley’s AI Center of Excellence. At Penn\, Kearns has secondary appointments in the Department of Economics\, and in the departments of Statistics and Operations\, Information\, and Decisions in the Wharton School. He is the founding director of the Warren Center for Network and Data Sciences and the founder and former director of Penn Engineering’s Networked and Social Systems Engineering Program. His research interests includes topics in machine learning\, artificial intelligence\, algorithmic game theory and quantitative trading and finance. Kearns is an elected Fellow of the American Academy of Arts and Science\, the Association for Computing Machinery\, and the Association for the Advancement of Artificial Intelligence. He has consulted widely in the technology and finance industries\, and on a variety of related regulatory and legal matters.
URL:https://entrepreneurship.columbia.edu/event/fdt-center-intelligent-asset-management-fintech-lecture-series/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20190206T180000
DTEND;TZID=UTC:20190206T200000
DTSTAMP:20260414T211301
CREATED:20190114T220652Z
LAST-MODIFIED:20190114T220652Z
UID:15489-1549476000-1549483200@entrepreneurship.columbia.edu
SUMMARY:Computational Social Science Poster Session
DESCRIPTION:The 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\nWednesday\, February 6\, 2019 \n6:00 PM – 8:00 PM\n\nMudd Hall\, 500 W. 120 St.\, New York\, NY 10027\nRoom/Area: 407 (Data Science Institute)\n\n\nEvent Contact Information: \nData Science Institute\n212-854-5660\ndatascience@columbia.edu
URL:https://entrepreneurship.columbia.edu/event/computational-social-science-poster-session/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20190201T153000
DTEND;TZID=UTC:20190201T173000
DTSTAMP:20260414T211301
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:20260414T211301
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:20260414T211301
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:20260414T211302
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:20260414T211302
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:20260414T211302
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:20260414T211302
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:20260414T211302
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:20260414T211302
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:20260414T211302
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:20260414T211302
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:20260414T211302
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:20260414T211302
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:20260414T211302
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:20260414T211302
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:20260414T211302
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:20260414T211302
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:20260414T211302
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:20260414T211302
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:20260414T211302
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
END:VCALENDAR