CIRC Symposium Series76e56639ac19042a71a836ad1806e08bWegmans 1400false15133554000002017-12-15T11:30:0015133608000002017-12-15T13:00:00Talks2017/12/1215_circ-symposium-series 1217.htmlfalseOnceGoergen Institute for Data Science Distinguished Speaker Series: Jeannette Wing72106b8dac19042a71a836ad04a102c5Jeannette 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. Professor 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. She was or is on the editorial board of twelve journals, including the Journal of the ACM and Communications of the ACM. She is currently Retiring Chair of the AAAS Section on Information, Computing and Communications, and a member of: 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 Technical Advisory Board. She has been 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). Abstract: Every 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. The 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. In this talk, I will present the mission of the Institute, highlights of our educational and research activities, and plans for future initiatives.Wegmans Hall 1400 (auditorium), River Campusfalse15127488000002017-12-08T11:00:0015127524000002017-12-08T12:00:00Talks2017/12/1208_goergen-institute-for-data-science-distinguished-speaker-series-jeannette-wing.htmlfalseOnceCareers in Data Science: Jason Morrissette, Wegmans Food Marketsa7e272b7ac19042a1507b5d7e7673b23Alumnus Jason Morrissette is a Rochester native. He graduated magna cum laude with a double major in Statistics and Mathematics from the University of Rochester in 2011 and continued his education at the University of Rochester School of Medicine and Dentistry with an MA and PhD in Statistics. While going to school he worked part-time in customer service and intern roles for Wegmans Food Markets. Wegmans is a family-owned supermarket chain headquartered in Rochester, NY that has consistently been named one of FORTUNE magazine’s 100 Best Companies to Work For, topping the list at #1 in 2005 and most recently at #4 in 2016. He now has 10 years with the company and is currently an Analyst in the Customer Insights department. In his current role, he uses his knowledge of data mining and predictive analytics to produce actionable insights from large amounts of customer-related data. Join us to hear about his career path, his work projects and his tips for having a career in data science. Light lunch during the talk. RSVP recommended on Handshake to help us determine food count.Wegmans Hall 1400 (auditorium), River Campusfalse15121476000002017-12-01T12:00:0015121512000002017-12-01T13:00:00Talks2017/12/1201_careers-in-data-science-jason-morrissette,-wegmans.htmlfalseOnceDSUG presents MLH Hack Daye0063d9fac19042a1507b5d7c956406fRettner Atrium (1st floor)false15122268000002017-12-02T10:00:0015122700000002017-12-02T22:00:00Other2017/12/1202_dsug-presents-mlh-hack-day.htmlfalseOnceGraduate Student Workshop: Job Search Strategies e03a1a7fac19042a1507b5d754da827bSummary: This will be an interactive workshop geared towards graduate students where participants will learn about tips, tricks, and strategies that can be applied to most internship and job searches. This is the first workshop in a series of professional development events for AS&E graduate students. For more information and to RSVP click here. Career Center Conference Room, 4-200 Dewey Hall, River Campusfalse15121566000002017-12-01T14:30:0015121602000002017-12-01T15:30:00Career Events2017/12/1201_graduate-student-workshop-job-search-strategies-.htmlfalseOnceComputer Science Colloquim Series: Designing and Developing Cyber-Resilient Systems13cb970cac19042a1507b5d78a244dffWegmans Hall 1400 (auditorium), River Campusfalse15124068000002017-12-04T12:00:0015124104000002017-12-04T13:00:00Meetings2017/12/1204_computer-science-colloquim-series-designing-and-developing-cyber-resilient-systems.htmlfalseOnceMechanical Engineering Seminar: Ultrafast Large-scale Neural Network Processor on a Chip19b85db8ac19042a1507b5d776fdf866Hopeman 224false15127578000002017-12-08T13:30:0015127614000002017-12-08T14:30:00Talks2017/12/1208_mechanical-engineering-seminar-ultrafast-large-scale-neural-network-processor-on-a-chip.htmlfalseOnceComputer Science Colloquium Series: Towards Human-like Understanding of Visual Content: Facilitating Search and Decoding Visual Media4601b557ac19042a1507b5d79599a6d3TITLE: Towards Human-like Understanding of Visual Content: Facilitating Search and Decoding Visual Media ABSTRACT: In the first part of this talk, I will describe our work on interactive image search. We introduced a new form of interaction for search, where the user can give rich feedback to the system via semantic visual attributes (e.g., "metallic", "pointy", and "smiling"). The proposed WhittleSearch approach allows users to narrow down the pool of relevant images by comparing individual properties of the results to those of the desired target. Building on this idea, we develop a system-guided version of the method which engages the user in a 20-questions-like game where the answers are visual comparisons. To ensure that the system interprets the user's attribute-based feedback as intended, we further show how to efficiently adapt a generic model for an attribute to more closely align with the individual user's perception. Our work transforms the interaction between the image search system and its user from keywords and clicks to precise and natural language-based communication. We demonstrate the impact of this new search modality for effective retrieval on databases ranging from consumer products to human faces. This is an important step in making the output of vision systems more useful, by allowing users to both express their needs better and better interpret the system's predictions. In the second part of my talk, I will discuss two recent projects on using computer vision to analyze images in the media, which often have persuasive intents that lie beyond the physical content. As a first step in understanding persuasion in the visual media, we released a dataset of 64,832 image ads, and a video dataset of 3,477 ads, containing rich annotations about the subject, sentiment, and rhetoric of the ads. The key task we focus on is the ability of a computer vision system to answer questions about the actions the viewer is prompted to take and the reasoning that the ad presents to persuade the viewer. To help perform this task, we focus on two challenges: decoding the symbolic references that ads make (e.g. a dove symbolizes peace), and recognizing objects in the severely non-photorealistic portrayals that some ads use. In a second media understanding project, we develop a method that captures photographers’ styles and predicts the authorship of artistic photographs. To explore the feasibility of current computer vision techniques to address photographer identification, we create a new dataset of over 180,000 images taken by 41 well-known photographers. We examine the effectiveness of a variety of features and convolutional neural networks for this task. We also use what our method has learned to generate new “pastiche” photographs in the style of an author. BIO: Adriana Kovashka is an Assistant Professor in Computer Science at the University of Pittsburgh. She received her PhD in 2014 from The University of Texas at Austin. Her research interests primarily lie in computer vision, with some overlap in machine learning, information retrieval, natural language processing, and human computation. Her work is funded by two NSF grants and a Google Faculty Research Award. Her research has been published in the top computer vision conferences, such as Computer Vision and Pattern Recognition (CVPR) and the International Conference on Computer Vision (ICCV), as well as the annual conference of the Association for Computational Linguistics (ACL). She has served as Area Chair for CVPR 2018, Tutorial Chair for WACV 2018, and Doctoral Consortium Chair for CVPR 2015-2017.Wegmans Hall 1400 (auditorium), River Campusfalse15130116000002017-12-11T12:00:0015130152000002017-12-11T13:00:00Talks2017/12/1211_computer-science-colloquium-series-towards-human-like-understanding-of-visual-content-facilitating-search-and-decoding-visual-media.htmltrueOnce