Some other info about me here. February 2019. blei_cv.pdf David Blei is a professor of statistics and computer science at Columbia University, and a member of the Columbia Data Science Institute. Selected Abstracts Bayesian Nonparametric Customer Base Analysis with Model-based Visualizations Ryan Dew and Asim Ansari The assumption is that each document mix with various topics and every topic mix with various words. Fellow, Society for Industrial and Applied Mathematics (SIAM), 2012. David Blei. Ryan Dew The Wharton School — 3730 Walnut Street, JMHH 755 — Philadelphia, PA 19104 ryandew@wharton.upenn.edu — www.rtdew.com Academic Appointments David Blei's main research interest lies in the fields of machine learning and Bayesian statistics. Hosted by Prof. David M. Blei 2015 – 2016 (Competitive) Ph.D. Microsoft Research, New York City, NY. Tel (212) 854-2993, Civil Engineering and Engineering Mechanics, Industrial Engineering and Operations Research, Postdoctoral Fellow, Department of Machine Learning, Carnegie Mellon University, 2004–2006  Advisor: John Lafferty, Professor, Departments of Statistics and Computer Science, Columbia University, 2014, Associate Professor, Department of Computer Science, Princeton University, 2011–2014, Assistant Professor, Department of Computer Science, Princeton University, 2006–2011, Fellow of the Institute for Mathematical Statistics, 2017, ICML Test of Time Award (for “Dynamic Topic Models”), 2016, Presidential Award for Outstanding Teaching, Honorable Mention, 2016, Fellow of the Association of Computing Machinery, 2015, SIGIR Test of Time Award Honorable Mention (for “Modeling Annotated Data”), 2015, Blavatnik Award for Young Scientists: Faculty Winner, 2013 P, Presidential Early Career Award for Scientists and Engineers (PECASE), 2011, Office of Naval Research Young Investigator Award, 2011, D. Blei, A. Kucukelbir, and J. McAuliffe. 112(26):E3341 – 50, 2015. Mail Code 4690. David Mimno 2 How Social Media Non-use Influences the Likelihood of Reversion: Self Control, Being Surveilled, Feeling Freedom, and Socially Connecting. Every pixel counts++: Joint learning of geometry and motion with 3d holistic un- Forsyth ``Probabilistic methods for finding people,'' International Journal of Computer Vision , Volume 43, Issue 1, pp45-68, June 2001 Blei has received several awards for his research, including a Sloan Fellowship (2010), Office of Naval Research Young Investigator Award (2011), Presidential Early Career Award for Scientists and Engineers (2011), Blavatnik Faculty Award (2013), ACM-Infosys Foundation Award (2013) and a Guggenheim fellowship. David M. Zoltowski, Jonathan W. Pillow, and Scott W. Linderman. Andrew C. Miller, Ziad Obermeyer, David M. Blei, John P. Cunningham, and Sendhil Mullainathan Machine Learning for Health (NeurIPS Workshop), 2018 An electrocardiogram (EKG) is a common, non-invasive test that measures the electrical activity of a patient's heart. T.H.Chan School of Public Health August 2016 - May 2018 M.S. Columbia University (USA) 2015 – 2016 • Working with Prof. David M. Blei process”, by David Blei, Thomas L. Griffiths (student advisee), and Michael I. Jordan. Honorable mention, Marr Prize for Best Student Paper, Twenty-Sixth Annual Conference of the Cognitive Science Society, 2004, for “Using physical theories to infer hidden causal … in Computational Biology and Quantitative Genetics (CBQG) GPA: 3.79/4.0 Advisor: Giovanni Parmigiani CBQG Program Student Committee Co-chair. I am a Computer Science Ph.D. student at Columbia University, where I am advised by David Blei. We will be developing new methods and implementing them in probabilistic programming systems. Verified email at columbia.edu - Homepage. CV / Google Scholar / LinkedIn / Github / Twitter / Email: abd2141 at columbia dot edu I am a Ph.D candidate in the department of Statistics at Columbia University where I am jointly being advised by David Blei and John Paisley. Distinguished invited lectures 2019 J. James Woods Lecture Series, Butler University. Search this site: Humanities. 1255 Amsterdam Avenue Journal of Machine Learning Research, 3:993-1022, 2003. Honorable mention, Marr Prize for Best Student Paper, Twenty-Sixth Annual Conference of the Cognitive Science Society, 2004, for “Using physical theories to infer hidden causal … Journal of Machine Learning Research, 14:1303-1347, 2013. New York, NY 10027  David B. Dunson Arts and Sciences Distinguished Professor of Statistical Science My research focuses on developing new tools for probabilistic learning from complex data - methods development is directly motivated by challenging applications in ecology/biodiversity, neuroscience, environmental health, criminal justice/fairness, and more. For operational updates and health guidance from the University, please visit the COVID-19 Resource Guide. Previously, I recieved a BA in Mathematics at Princeton University, where I was fortunate enough to do research with Sanjeev Arora and David Blei (who taught at Princeton at the time). Advisors: David Blei, John Paisley Master in Applied Statistics, Cornell University Jan 2012 – May 2013 Advisors: David Lifka, Martin Wells Diplome d’Ingenieur, Telecom ParisTech Sep 2009 – May 2013 France’s “Grandes Ecoles ” Lycee Henri IV (France’s “Classes Preparatoires aux Grandes Ecoles”) Sep 2006 – June 2009 Employment Sort by citations Sort by year Sort by title. 2018. Estimating Heterogeneous Consumer Preferences for Restaurants and Travel Time Using Mobile Location Data: David Blei, Robert Donnelly, Francisco Ruiz, Tobias Schmidt Tensor Variable Elimination for Plated Factor Graphs.ICML 2019 DEPARTMENT OF STATISTICS Columbia University Room 1005 SSW, MC 4690 1255 Amsterdam Avenue New York, NY 10027 Phone: 212.851.2132 Fax: 212.851.2164 AZIMUT, Italy's leading independent asset manager Specialised in asset management, the Group offers financial advisory services for investors, primarily through its advisor networks. [PDF], M. Hoffman, D. Blei, J. Paisley, and C. Wang. Gabriele Blei is Co-CEO at Azimut Holding Spa. Advisor: Hanna Wallach. Francisco Ruiz, David Blei: Annals of Applied Statistics (forthcoming), 2019. My CV … I completed my Ph.D. in the Electrical Engineering Department at Columbia University, as part of the LabROSA, working with Professor Dan Ellis and Professor David Blei. Sort. Thus, each train-test partition includes different data for testing. Deep exponential families. David Blei, Andrew Y. Ng and Michael I. Jordan. Professor, Computer Science and Statistics. Selected Abstracts Bayesian Nonparametric Customer Base Analysis with Model-based Visualizations Ryan Dew and Asim Ansari Based on dissertation essay process”, by David Blei, Thomas L. Griffiths (student advisee), and Michael I. Jordan. His work is primarily in machine learning. Title. (This algorithm is used by the New York Times to form recommendations for its readers.) Michael Kearns, Yishay Mansour and Andrew Y. Ng. David Blei. Scholarship by the Spanish Ministry of Education 2012 – 2015 • FPU Grant No. Supervisor: David Blei and Simon Tavar e Research Intern, Google Brain, Mountain View, CA May 2019{August 2019 Supervisor: George Tucker and Chelsea Finn Research Intern, Quantlab Financial LLC, Houston, TX June 2017{August 2017 Supervisor: Joe Masters Data Science Intern, HP Lab, Austin, TX June 2016{August 2016 Supervisor: Lakshminarayan Choudur David M. Blei is a professor in the Statistics and Computer Science departments at Columbia University. Scaling probabilistic, models of genetic variation to millions of humans. david.blei@columbia.edu Olivier Toubia (Committee member) Glaubinger Professor of Business Columbia University ot2107@gsb.columbia.edu (212) 854-8243 Page 4 of 6. CV / Google Scholar / LinkedIn / Github / Twitter / Email: abd2141 at columbia dot edu I am a Ph.D candidate in the department of Statistics at Columbia University where I am jointly being advised by David Blei and John Paisley. Probabilistic topic models. [PDF] [Code]. Posterior predictive checks to quantify lack-of-fit in admixture models of latent population struc-ture. Honorable mention, Marr Prize for Best Student Paper, Twenty-Sixth Annual Conference of the Cognitive Science Society, 2004, for “Using physical theories to infer hidden causal … 37, pp. In Submission. The thrusts are (a) scalable inference and (b) model checking. Mingyuan Zhou and Lawrence Carin, \Negative binomial process count and mixture modeling," Supervisor: David Blei and Simon Tavar e Research Intern, Google Brain, Mountain View, CA May 2019{August 2019 Supervisor: George Tucker and Chelsea Finn Research Intern, Quantlab Financial LLC, Houston, TX June 2017{August 2017 Supervisor: Joe Masters Data Science Intern, HP Lab, Austin, TX June 2016{August 2016 Supervisor: Lakshminarayan Choudur Stop words on bi-gram or 4-gram drastically reduces number of features. David Blei, Michael Jordan, and Joshua Tenenbaum. process”, by David Blei, Thomas L. Griffiths (student advisee), and Michael I. Jordan. David M Blei, and Chris H Wiggins. Title. One recent example is collaborative topic models, which connect textual content to user behavior (such as clicks), and which can be used to interpret patterns of readership, recommend documents, characterize readers, and organize collections according to both content and consumption. Here is my CV. Efficient and flexible variational inference algorithms Postdoctoral Researcher. He is a fellow of the ACM and the IMS. He works on a variety of applications, such as text, images, music, social networks, user behavior and scientific data. Since then, Blei and his group has significantly expanded the scope of topic modeling. \Scalable Probabilistic Causal Structure Discovery." The embedding models we develop lie at the intersection of Bayesian machine learning and deep learning. College of Information and Computer Sciences, University of Massachusetts Amherst. Risk prediction for chronic kidney disease progression using heterogeneous electronic health record data and time series analysis. Dose-response modeling in high-throughput cancer drug screenings: An end-to-end approach. You can read my CV for more information, and you can also contact me directly. [18] Adji B. Dieng, Yoon Kim, Alexander M. Rush, David M. Blei. Today, their algorithm—latent Dirichlet allocation (LDA)—is a standard method for topic discovery, and is used in many downstream tasks. Il libro dei Salmi (1-50). [PNAS], D. Blei. International Joint Conference of Arti cial Intelligence (IJCAI). S.Athey,D.Blei,R.Donnelly,F.Ruiz,andT.Schmidt.Estimatingheterogeneousconsumer preferencesforrestaurantsandtraveltimeusingmobilelocationdata. LDA is introduced by David Blei, Andrew Ng and Michael O. Jordan in 2003. 37, pp. cv = CountVectorizer (ngram_range = (1, 2)). ICML Test of Time award (with F. Bach and G. Lanckriet), for \Multiple kernel learning, conic duality, and the SMO algorithm" in ICML 2004), 2014. Random 5-folds CV: a random partition in 5 folds was performed, and then they were joined in 5 different train-test partitions, where in each case 4 folds are used for training and the remaining one for testing. Machine Learning Statistics Probabilistic topic models Bayesian nonparametrics Approximate posterior inference. Supervisor: Hanna Wallach. david.blei@columbia.edu Olivier Toubia (Committee member) Glaubinger Professor of Business Columbia University ot2107@gsb.columbia.edu (212) 854-8243 Page 4 of 6. Before joining Columbia, he was an Associate Professor of Computer Science at Princeton University (2006-2014). David Blei's main research interest lies in the fields of machine learning and Bayesian statistics. Biostatistics (in press), 2020. Verified email at columbia.edu - Homepage. Find David Blei's phone number, address, and email on Spokeo, the leading online directory for contact information. Modeling User Exposure in Recommendation, Dawen Liang, Laurent Charlin, James McInerney, David M. Blei, in Proceedings of the 25th International Conference on World Wide Web (WWW), 2016. in Computational Biology and Quantitative Genetics (CBQG) GPA: 3.79/4.0 Advisor: Giovanni Parmigiani CBQG Program Student Committee Co-chair. Proceedings of the National Academy of Sciences. It is unsupervised learning and topic model is the typical example. 2003 S. Ioffe and D.A. Prof. Blei and his group have set new paths in the fields of machine learning and artificial intelligence. 2018 Roger N. Shepard Visiting Scholar, University of Arizona. To applicants interested in many kinds of applications and from any field user behavior and scientific data ) 2014... To learn more About our spring term, please visit the updates for Students page on inference... 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