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X-WR-CALDESC:Events for Columbia Entrepreneurship
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DTSTART:20150101T000000
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BEGIN:VEVENT
DTSTART;TZID=UTC:20171010T080000
DTEND;TZID=UTC:20171010T170000
DTSTAMP:20260415T021402
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:20260415T021402
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:20260415T021402
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:20260415T021402
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:20260415T021402
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:20260415T021402
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:20260415T021402
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:20260415T021402
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:20260415T021402
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
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20170302T170000
DTEND;TZID=UTC:20170302T183000
DTSTAMP:20260415T021402
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:20260415T021402
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
BEGIN:VEVENT
DTSTART;TZID=UTC:20161129T160000
DTEND;TZID=UTC:20161129T170000
DTSTAMP:20260415T021402
CREATED:20160914T192649Z
LAST-MODIFIED:20160914T193907Z
UID:4821-1480435200-1480438800@entrepreneurship.columbia.edu
SUMMARY:DEADLINE: Applications for Urban-X Accelerator
DESCRIPTION:Application\nFocusing on the convergence of Smart Cities\, Connected Real Estate\, Resilient Energy Systems\, and the Future of Mobility\, Big Data\, and Digitalization of Urban Infrastructure\, Urban-X is looking for pre-seed startups\, founders\, and hungry risk-takers working on technology for intelligent cities\, urban hyper-growth\, and society-scale challenges. \nApplications are now open for Urban-X’s cohort 02\, which will kick off in October in NYC. Operated by MINI and SOSV HAX\, Urban-X invests in and accelerates startups through a 4 month program\, with hands-on mentorship\, customer development\, hardware engineering\, design\, partnerships\, and fundraising help. Our network of over 100 mentors\, prospective partners\, customers\, and policymakers is incredibly deep.  Applications are competitive. Chosen startups will receive $60\,000 USD in seed capital investment plus significant in-kind software\, hosting\, and legal services\, as well as the opportunity to hone your solution at HAX’s facilities in Shenzhen and BMW / MINI’s global operations in Munich.  Applications are due NOVEMBER 29 and can be found here: https://urban-x.com/apply/ \n \n  \n  \n 
URL:https://entrepreneurship.columbia.edu/event/deadline-applications-urban-x-accelerator/
CATEGORIES:Columbia Data Science Institute
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20161004T143000
DTEND;TZID=UTC:20161004T160000
DTSTAMP:20260415T021402
CREATED:20160930T143214Z
LAST-MODIFIED:20160930T143214Z
UID:5098-1475591400-1475596800@entrepreneurship.columbia.edu
SUMMARY:Gen. Ellen M. Pawlikowski\, U.S. Airforce at Data Science Institute Colloquium Series
DESCRIPTION:Join the Columbia University Data Science Institute\nNo Registration Required\nPotential adversaries have carefully studied the American way of war and U.S. reliance on aerospace power. They are investing heavily in technologies to deny the air superiority advantage we have enjoyed for more than a generation. Our dominance is no longer assured. This presentation will explore how the Air Force is planning to “out innovate” near-peer competitors and deliver multi-domain air\, space and cyber capabilities in support of a new Third Offset Strategy. It will highlight new operating concepts and technologies like autonomy\, hypersonics\, directed energy and additive manufacturing to fly\, fight and win in 2030 and beyond. \nGeneral Pawlikowski employs some 80\,000 people and managing $60 billion annually. The Air Force Research Lab is in her portfolio and she has led efforts to tackle “big data” in the lifecycle of Air Force designs\, processes and parts. \nGeneral Ellen M. Pawlikowski\nGen. Ellen M. Pawlikowski serves as Commander\, Air Force Materiel Command\, Wright-Patterson Air Force Base\, Ohio. The command employs some 80\,000 people and manages $60 billion annually\, executing the critical mission of warfighter support through leading-edge science and technology\, cradle-to-grave life cycle weapon systems management\, world-class developmental test and evaluation\, and world-class depot maintenance and supply chain management. \nGeneral Pawlikowski entered the Air Force in 1978 through the ROTC program at the New Jersey Institute of Technology. She then attended the University of California at Berkeley and received a Doctorate in chemical engineering in December 1981\, entering active duty at McClellan AFB\, California\, in April 1982. \nGeneral Pawlikowski’s career has spanned a wide variety of technical management\, leadership and staff positions including command at the wing and center levels. She has served as Director of the Acquisition Management Office for the Assistant to the Secretary of Defense for Atomic Energy and as Deputy Assistant to the Secretary of Defense for Counterproliferation\, Office of the Secretary of Defense.  Her leadership assignments included Program Director of the Airborne Laser Program; Commander of the Military Satellite Communications Systems Wing; Deputy Director of the National Reconnaissance Office; Commander of the Air Force Research Laboratory; and most recently Commander of the Space and Missile Systems Center. \nGeneral Pawlikowski is nationally recognized for her leadership in the US science and technology community.  She is a Fellow of the American Institute of Aeronautics and Astronautics and a member of the National Academy of Engineers. \nPrior to her current assignment\, General Pawlikowski was the Military Deputy\, Office of the Assistant Secretary of the Air Force for Acquisition\, the Pentagon\, Washington\, D.C. \nEDUCATION\n1978 Bachelor of Science degree in chemical engineering\, New Jersey Institute of Technology\, Newark\n1981 Doctorate of Philosophy in chemical engineering\, University of California\, Berkeley\n1984 Squadron Officer School\, Maxwell AFB\, Ala.\n1990 Air Command and Staff College\, Maxwell AFB\, Ala.\n1991 Program Managers Course\, Defense Systems Management College\, Fort Belvoir\, Va.\n1994 Industrial College of the Armed Forces\, Fort Lesley J. McNair\, Washington\, D.C. \nASSIGNMENTS\n1. April 1982 – December 1984\, Director\, Gas Research and Development\, Technical Operations Division\, McClellan AFB\, Calif.\n2. December 1984 – March 1986\, Chief\, Mass Spectrometry and Micro-beam Instruments Branch\, Technical Operations Division\, McClellan AFB\, Calif.\n3. March 1986 – December 1987\, Command Systems Plans Manager\, Air Force Technical Applications Center\, Patrick AFB\, Fla.\n4. December 1987 – July 1989\, Chief\, Plans and Programs Division\, Air Force Technical Applications Center\, Patrick AFB\, Fla.\n5. July 1989 – July 1990\, student\, Air Command and Staff College\, Maxwell AFB\, Ala.\n6. June 1990 – December 1991\, Deputy Chief\, Special Projects Division\, Rome Laboratory\, Griffiss AFB\, N.Y.\n7. December 1991 – July 1993\, Senior Executive Officer\, Rome Laboratory\, Griffiss AFB\, N.Y.\n8. July 1993 – June 1994\, student\, Industrial College of the Armed Forces\, Fort Lesley J. McNair\, Washington\, D.C.\n9. June 1994 – March 1996\, Director\, Acquisition Management Office\, Assistant to the Secretary of Defense for Atomic Energy\, Office of the Secretary of Defense\, the Pentagon\, Washington\, D.C.\n10. March 1996 – June 1997\, Deputy Assistant to the Secretary of Defense for Counterproliferation\, Office of the Secretary of Defense\, the Pentagon\, Washington\, D.C.\n11. June 1997 – June 1999\, Chief\, Revolutionizing Training Division\, Training Systems Product Group\, Aeronautical Systems Center\, Wright-Patterson AFB\, Ohio\n12. June 1999 – March 2000\, Deputy Director\, Global Power Programs\, Assistant Secretary of the Air Force for Acquisition\, Headquarters U.S. Air Force\, Washington\, D.C.\n13. April 2000 – March 2005\, Director\, Airborne Laser System Program Office\, Aeronautical Systems Center\, Kirtland AFB\, N.M.\n14. March 2005 – July 2007\, Commander\, Military Satellite Communications Systems Wing\, Space and Missile Systems Center\, Los Angeles AFB\, Calif.\n15. July 2007 – May 2008\, Vice Commander\, Space and Missile Systems Center\, Los Angeles AFB\, Calif.\n16. June 2008 – February 2010\, Deputy Director\, National Reconnaissance Office\, Chantilly\, Va.\n17. February 2010 – May 2011\, Commander\, Air Force Research Laboratory\, Wright-Patterson AFB\, Ohio\n18. June 2011 – June 2014\, Commander\, Space and Missile Systems Center and Program Executive Officer for Space\, Los Angeles AFB\, Calif.\n19.  June 2014 – June 2015\, Military Deputy\, Office of the Assistant Secretary of the Air Force for Acquisition\, the Pentagon\, Washington\, D.C.\n20. June 2015 – present\, Commander\, Air Force Materiel Command\, Wright-Patterson AFB\, Ohio \nSUMMARY OF JOINT ASSIGNMENTS \n1. June 1994 – March 1996\, Director\, Acquisition Management Office\, Assistant to the Secretary of Defense for Atomic Energy\, Office of the Secretary of Defense\, the Pentagon\, Washington\, D.C.\, as a lieutenant colonel\n2. March 1996 – June 1997\, Deputy Assistant to the Secretary of Defense for Counterproliferation\, Office of the Secretary of Defense\, the Pentagon\, Washington\, D.C.\, as a colonel\n3. March 2005 – July 2007\, Commander\, Military Satellite Communications Systems Wing\, Space and Missile Systems Center\, Los Angeles AFB\, Calif.\, as a brigadier general\n4. June 2008 – February 2010\, Deputy Director\, National Reconnaissance Office\, Chantilly\, Va.\, as a major general \nMAJOR AWARDS AND DECORATIONS\nDistinguished Service Medal\nDefense Superior Service Medal with two oak leaf clusters\nLegion of Merit\nDefense Meritorious Service Medal\nMeritorious Service Medal with two oak leaf clusters\nAir Force Commendation Medal with oak leaf cluster\nAir Force Achievement Medal\nAir Force Individual Recognition Ribbon \nOTHER ACHIEVEMENTS\n1984  Commandant Trophy\, Squadron Officers School\n1999  Air Force Association Management Award – Executive\n2012  Women in Aerospace\, Lifetime Achievement Awards\n2012  Thomas D. White Space Award\n2012  Fellow\, American Institute of Aeronautics and Astronautics\n2014  Member\, National Academy of Engineering \nEFFECTIVE DATES OF PROMOTION\nSecond Lieutenant May 25\, 1978\nFirst Lieutenant May 25\, 1981\nCaptain May 25\, 1983\nMajor March 1\, 1988\nLieutenant Colonel April 1\, 1992\nColonel Oct. 1\, 1996\nBrigadier General June 1\, 2005\nMajor General  July 22\, 2008\nLieutenant General June 3\, 2011\nGeneral June 8\, 2015 \n(Current as of June 2015)
URL:https://entrepreneurship.columbia.edu/event/gen-ellen-m-pawlikowski-u-s-airforce-data-science-institute-colloquium-series/
LOCATION:Davis Auditorium\, Schapiro\, New York City\, 10027\, United States
CATEGORIES:Columbia Data Science Institute
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