Probabilistic topic models. By bringing together ideas in computer science, statistics, and optimization, more than a decade ago, Blei and collaborators developed a method to discover the abstract “topics” that pervade a collection of documents. 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 The MachineLearning at Columbia mailing list is a good source of informationabout talks and other events on campus. I am a postdoctoral fellow in the Data Science Institute at Columbia working with David Blei and Donald Green to study voter turnout in US elections. Francisco Ruiz, David Blei: Annals of Applied Statistics (forthcoming), 2019. International Joint Conference of Arti cial Intelligence (IJCAI). LDA is introduced by David Blei, Andrew Ng and Michael O. Jordan in 2003. Dose-response modeling in high-throughput cancer drug screenings: An end-to-end approach. 2016 Mind Lecture, University of Kansas. Find books New York, NY 10027  Proceedings of the National Academy of Sciences. Thus, each train-test partition includes different data for testing. In David Blei and Francis Bach, editors, ICML, pages 97–105. david.blei@columbia.edu Olivier Toubia(Committee member) Glaubinger Professor of Business Columbia University ot2107@gsb.columbia.edu (212) 854-8243 Page 4of6. Latent Dirichlet allocation. Ryan Dew The Wharton School — 3730 Walnut Street, JMHH 755 — Philadelphia, PA 19104 ryandew@wharton.upenn.edu — www.rtdew.com Academic Appointments David Blei writes: I have two postdoc openings for basic research in probabilistic modeling. Advisors: George Hripcsak and David Blei Harvard. Their work is widely used in science, scholarship, and industry to solve interdisciplinary, real-world problems. Find David Blei's phone number, address, and email on Spokeo, the leading online directory for contact information. Tensor Variable Elimination for Plated Factor Graphs.ICML 2019 [PDF], M. Hoffman, D. Blei, J. Paisley, and C. Wang. Mingyuan Zhou and Lawrence Carin, \Negative binomial process count and mixture modeling," 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. Communications of the ACM, 55(4):77–84, 2012. [A shorter version appeared in NIPS 2002]. Research group My research interest is in the general area of statistical machine learning, including: Probabilistic models and inference techniques, Proceedings of the National Academy of Sciences, 110 (36) 14534-14539, 2013. He is a fellow of the ACM and the IMS. Articles Cited by Co-authors. David Blei's main research interest lies in the fields of machine learning and Bayesian statistics. David E. Rumelhart Prize, 2015. Sort by citations Sort by year Sort by title. Title. Michael Kearns, Yishay Mansour and Andrew Y. Ng. Machine Learning Statistics Probabilistic topic models Bayesian nonparametrics Approximate posterior inference. [arXiv], P. Gopalan, W. Hao, D. Blei, and J. Storey. S.Athey,D.Blei,R.Donnelly,F.Ruiz,andT.Schmidt.Estimatingheterogeneousconsumer preferencesforrestaurantsandtraveltimeusingmobilelocationdata. T.H.Chan School of Public Health August 2016 - May 2018 M.S. Journal of the American Statistical Association, to appear. Before joining Columbia, he was an Associate Professor of Computer Science at Princeton University (2006-2014). To learn more about our spring term, please visit the Updates for Students page. A general recurrent state space framework for … Every pixel counts++: Joint learning of geometry and motion with 3d holistic un- Most recently, I have been focusing on deep methods and causal inference. Proceedings of the National Academy of Sciences. Microsoft Research, New York City, NY. 346-358, Feb. 2015. See Gabriele Blei's compensation, career history, education, & memberships. Their work on variational inference has changed the scale at which we can apply sophisticated methods for data science and machine learning. David M. Zoltowski, Jonathan W. Pillow, and Scott W. Linderman. Yixin Wang, Dhanya Sridhar, David Blei. Professor, Computer Science and Statistics. Posterior predictive checks to quantify lack-of-fit in admixture models of latent population struc-ture. I am a Computer Science Ph.D. student at Columbia University, where I am advised by David Blei. [PDF], D. Blei, A. Ng, and M. Jordan. Since then, Blei and his group has significantly expanded the scope of topic modeling. Deep exponential families. [PNAS], D. Blei. Supervisor: David Blei. Tensor Variable Elimination for Plated Factor Graphs.ICML 2019 2018 Roger N. Shepard Visiting Scholar, University of Arizona. Today, their algorithm—latent Dirichlet allocation (LDA)—is a standard method for topic discovery, and is used in many downstream tasks. Some other info about me here. Fellow, International Society for Bayesian Analysis (ISBA), 2014. Risk prediction for chronic kidney disease progression using heterogeneous electronic health record data and time series analysis. 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 … AZIMUT, Italy's leading independent asset manager Specialised in asset management, the Group offers financial advisory services for investors, primarily through its advisor networks. David M. Blei 3 8. 37, pp. David Mimno, David M Blei, Barbara E Engelhardt. T.H.Chan School of Public Health August 2016 - May 2018 M.S. For operational updates and health guidance from the University, please visit the COVID-19 Resource Guide. 37, pp. Search this site: Humanities. 2003 S. Ioffe and D.A. Variational inference: A review for statisticians. \Scalable Probabilistic Causal Structure Discovery." 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. 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). Professor of Statistics and Computer Science, Columbia University. Journal of Machine Learning Research, 3:993-1022, 2003. (To subscribe, send email tomachine-learning-columbia+subscribe@googlegroups.com.) Stochastic variational inference. AZIMUT, Italy's leading independent asset manager Specialised in asset management, the Group offers financial advisory services for investors, primarily through its advisor networks. AP2010-5333 Columbia has a thrivingmachine learning community, with many faculty and researchersacross departments. We will be developing new methods and implementing them in probabilistic programming systems. Accepted to Machine Learning. 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. Distinguished invited lectures 2019 J. James Woods Lecture Series, Butler University. [nature] [biorXiv], R. Ranganath, L. Tang, L. Charlin, and D. Blei. David M Blei, and Chris H Wiggins. process”, by David Blei, Thomas L. Griffiths (student advisee), and Michael I. Jordan. process”, by David Blei, Thomas L. Griffiths (student advisee), and Michael I. Jordan. Artificial Intelligence and Statistics, 2015. The assumption is that each document mix with various topics and every topic mix with various words. I am open to applicants interested in many kinds of applications and from any field. Avoiding Latent Variable Collapse With Generative Skip Models.AISTATS 2019 [19] Fritz Obermeyer, Eli Bingham, Martin Jankowiak, Justin Chiu, Neeraj Pradhan, Alexander Rush, Noah Goodman. David Blei's main research interest lies in the fields of machine learning and Bayesian statistics. Annual Review of Statistics and Its Applicaton 1:203-232, 2014. Verified email at columbia.edu - Homepage. process”, by David Blei, Thomas L. Griffiths (student advisee), and Michael I. Jordan. Commento e attualizzazione | Gianfranco Ravasi | download | Z-Library. I am an associate professor in the University of Maryland Computer Science Department (tenure home), Institute of Advanced Computer Studies, iSchool, and Language Science Center.Previously, I was an assistant professor at Colorado's Department of Computer Science (tenure granted in 2017).I was a graduate student at Princeton with David Blei. His work is primarily in machine learning. Scholarship by the Spanish Ministry of Education 2012 – 2015 • FPU Grant No. Download books for free. [PDF], D. Blei. Fellow, Society for Industrial and Applied Mathematics (SIAM), 2012. “Text-based Ideal Points” (with David Blei and Keyon Vafa) OTHER ACADEMIC PUBLICATIONS: “Labor Market Institutions in the Gilded Age of American Economic History” (with Noam Yuchtman) -In Oxford Handbook of American Economic History, edited by Lou Cain, … Efficient and flexible variational inference algorithms Postdoctoral Researcher. David M. Blei is a professor in the Statistics and Computer Science departments at Columbia University. David Mimno 2 How Social Media Non-use Influences the Likelihood of Reversion: Self Control, Being Surveilled, Feeling Freedom, and Socially Connecting. I’m a Ph.D. student in the Department of Biomedical Informatics at Columbia University, advised by Professor George Hripcsak and David Blei.My research focuses on developing machine learning methods for causal inference with electronic health records. [11] A sparse sampling algorithm for near-optimal planning in large Markov decision processes. • Working with Prof. David M. Blei and Prof. Zoubin Ghahramani • Research topics: Probabilistic models for econometrics (shopping and location data) and electronic health records. Michael Kearns, Yishay Mansour and Andrew Y. Ng. 346-358, Feb. 2015. David Blei. Columbia University | Columbia University Irving Medical Center© 2019 Columbia University Irving Medical Center, Columbia University Department of Systems BiologyIrving Cancer Research Center1130 St. Nicholas Avenue, New York, NY 10032(212) 851-4673, Columbia University Department of Systems Biology, Center for Computational Biology & Bioinformatics (C2B2), Center for Cancer Systems Therapeutics (CaST), Center for Topology of Cancer Evolution and Heterogeneity, Cancer Target Discovery & Development Center (CTD2), International Serious Adverse Event Consortium (iSAEC), Columbia University Irving Medical Center, Center for Computational Biology and Bioinformatics (C2B2), The Program for Mathematical Genomics (PMG), Department of Systems Biology Information Technology (DSBIT). David Mimno, David M Blei, Barbara E Engelhardt. Estimating Heterogeneous Consumer Preferences for Restaurants and Travel Time Using Mobile Location Data: David Blei, Robert Donnelly, Francisco Ruiz, Tobias Schmidt [PDF], P. Gopalan and D. Blei. February 2019. fit (word) Note: if you choose really high n-grams, the feature space dimension can explode ! Il libro dei Salmi (1-50). Liang, Jaan Altosaar, Laurent Charlin, David M. Blei, in Proceedings of the 10th ACM Conference on Recommender Systems (RecSys), 2016. David Blei. Sort. 19.Gungor Polatkan, Mingyuan Zhou, Lawrence Carin, David Blei, and Ingrid Daubechies, \A Bayesian nonparametric approach to image super-resolution," IEEE Trans. Professor of Statistics and Computer Science, Columbia University. 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. I am open to applicants interested in many kinds of applications and from any field. 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 … My CV … You can read my CV for more information, and you can also contact me directly. Title. David M. Blei 3 10. 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. A. Perotte, R. Ranganath, J. Hirsch, D. Blei, and N. Elhadad. SIGIR Test of Time honorable mention (with D. Blei, for \Modeling annotated data" in SIGIR 2003), 2015. 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. Prior to fall 2014 he was an associate professor in the Department of Computer Science at Princeton University. Advisor: Prof. Dan Ellis and Prof. David Blei Thesis: Understanding music semantics and user behavior with probabilistic latent variable models Carnegie Mellon University, Pittsburgh, PA 2010.9 { 2012.5 M.S. Verified email at columbia.edu - Homepage. About. 2015 Teuber Lecture, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology. David Blei, Andrew Y. Ng and Michael I. Jordan. [Accepted for Oral Presenta-tion] Kobus Barnard, Pinar Duygulu, Nando de Freitas, David Forsyth, David Blei, and Michael I. Jordan, "Matching Words and Pictures", Journal of Machine Learning Research, Vol 3, pp 1107-1135. Efficient discovery of overlapping communities in massive networks. His research is in statistical machine learning, involving probabilistic topic models, Bayesian nonparametric methods and … 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. His research is in statistical machine learning, involving probabilistic topic models, Bayesian nonparametric methods and approximate posterior inference with massive data. I am interested in applying machine learning methods to uncover patterns in large data sets. 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. I was then a post-doc in the Computer Science departments at Princeton University with David Blei and UC Berkeley with Michael Jordan. Nature Genetics, 48:1587-1590. Articles Cited by Co-authors. Here is my CV. Ryan Dew The Wharton School — 3730 Walnut Street, JMHH 755 — Philadelphia, PA 19104 ryandew@wharton.upenn.edu — www.rtdew.com Academic Appointments cv = CountVectorizer (ngram_range = (1, 2)). David M. Zoltowski, Jonathan W. Pillow, and Scott W. Linderman. 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 … Avoiding Latent Variable Collapse With Generative Skip Models.AISTATS 2019 [19] Fritz Obermeyer, Eli Bingham, Martin Jankowiak, Justin Chiu, Neeraj Pradhan, Alexander Rush, Noah Goodman. ferable features with deep adaptation networks. Advisor: Hanna Wallach. Prof. Blei and his group develop novel models and methods for exploring, understanding, and making predictions from the massive data sets that pervade many fields. The thrusts are (a) scalable inference and (b) model checking. Prof. Blei and his group develop novel models and methods for exploring, understanding, and making predictions from the massive data sets that pervade many fields. 10 records for David Blei. 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 2018. David M Blei, and Chris H Wiggins. Prof. Blei and his group develop novel models and methods for exploring, understanding, and making predictions from the massive data sets that pervade many fields. David Sontag's Home Page E-mail: dsontag {@ | at} mit.edu Clinical machine learning group website. Research Intern, Summer 2015 and Summer 2014. Selected Abstracts Bayesian Nonparametric Customer Base Analysis with Model-based Visualizations Ryan Dew and Asim Ansari Pattern Analysis and Machine Intelligence, vol. Yonatan Halpern, David Mimno, Ankur Moitra, David Sontag, Yichen Wu, Michael Zhu. David Blei's main research interest lies in the fields of machine learning and Bayesian statistics. Faculty Award, 2008 National Science Foundation CAREER Award, 2008 (This algorithm is used by the New York Times to form recommendations for its readers.) Machine Learning Statistics Probabilistic topic models Bayesian nonparametrics Approximate posterior inference. It is unsupervised learning and topic model is the typical example. I am an associate professor in the University of Maryland Computer Science Department (tenure home), Institute of Advanced Computer Studies, iSchool, and Language Science Center.Previously, I was an assistant professor at Colorado's Department of Computer Science (tenure granted in 2017).I was a graduate student at Princeton with David Blei. David Blei writes: I have two postdoc openings for basic research in probabilistic modeling. A Computational Approach to Style in American Poetry (with David M. Blei) ICDM 2007 Java code for PacTag, pages 776–807 in Sites Web Dynamiques (ISBN 9782744009846) 1999 Drafts (*student) (ˆsubmitted) ˆInference on Consensus Ranking of Distributions 2020 ˆsivqr: Smoothed IV quantile regression (Stata command/article) 2020 2 [30]Chenxu Luo, Zhenheng Yang, Peng Wang, Yang Wang, Wei Xu, Ram Nevatia, and Alan Yuille. Columbia University (USA) 2015 – 2016 • Working with Prof. David M. Blei David Blei, Andrew Y. Ng and Michael I. Jordan. 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. \Equal Opportunties and A rmative Action via Coun-terfactual Predictions." ... SIGIR Test of Time honorable mention (with D. Blei, for \Modeling annotated data" in SIGIR 2003), 2015. Journal of Machine Learning Research, 3:993-1022, 2003. in Computational Biology and Quantitative Genetics (CBQG) GPA: 3.79/4.0 Advisor: Giovanni Parmigiani CBQG Program Student Committee Co-chair. [18] Adji B. Dieng, Yoon Kim, Alexander M. Rush, David M. Blei. Stop words on bi-gram or 4-gram drastically reduces number of features. Journal of Machine Learning Research, 14:1303-1347, 2013. Prof. Blei and his group develop novel models and methods for exploring, understanding, and making predictions from the massive data sets that pervade many fields. 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 … Experienced Segregation: Billy Ferguson, Matthew Gentzkow, Tobias Schmidt: Working Paper. Sort by citations Sort by year Sort by title. The embedding models we develop lie at the intersection of Bayesian machine learning and deep learning. 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 2 Alfred P. Sloan Fellowship, 2010 E.L. Keyes Jr. Emerson Electric Co. 1255 Amsterdam Avenue 2017. 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 In particular, they focus on a variety of applications, including language, recommendation systems, neuroscience, and the computational social sciences. Accepted to Machine Learning. Pattern Analysis and Machine Intelligence, vol. in Computational Biology and Quantitative Genetics (CBQG) GPA: 3.79/4.0 Advisor: Giovanni Parmigiani CBQG Program Student Committee Co-chair. Dose-response modeling in high-throughput cancer drug screenings: An end-to-end approach. Mail Code 4690. 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. [PDF] [Code]. We will be developing new methods and implementing them in probabilistic programming systems. Graduate Research Assistant, September 2012{2018. College of Information and Computer Sciences, University of Massachusetts Amherst. Advisor: Prof. David Blei My research is focused on embeddings – methods for learning interpretable representations from data. Forsyth ``Probabilistic methods for finding people,'' International Journal of Computer Vision , Volume 43, Issue 1, pp45-68, June 2001 20. david blei thesis When david blei thesis you use our service, you are placing your confidence in us which is why we would like to inform you that all our benefits are free of charge! The thrusts are (a) scalable inference and (b) model checking. Commu-nications of the ACM. Their work is widely used in science, scholarship, and industry to solve interdisciplinary, real-world problems. Selected Abstracts Bayesian Nonparametric Customer Base Analysis with Model-based Visualizations Ryan Dew and Asim Ansari Based on dissertation essay Sort. Best Student Paper Award (with P. Wang, K. Laskey and C. Domeniconi), SIAM Scaling probabilistic, models of genetic variation to millions of humans. [18] Adji B. Dieng, Yoon Kim, Alexander M. Rush, David M. Blei. 20. Biostatistics (in press), 2020. Build, compute, critique, repeat: Data analysis with latent variable models. In Submission. Architecture and Environmental Design; Art History 112(26):E3341 – 50, 2015. David Blei, Michael Jordan, and Joshua Tenenbaum. 112(26):E3341 – 50, 2015. Software Engineering Intern, Summer 2013. He works on a variety of applications, such as text, images, music, social networks, user behavior and scientific data. Dhanya Sridhar, Jay Pujara, Lise Getoor. Biostatistics (in press), 2020. [11] A sparse sampling algorithm for near-optimal planning in large Markov decision processes. About me. JMLR Workshop and Conference Proceedings, 2015. Bayesian modeling helps communicate modeling choices and to reason about uncertainty I generally do research on Bayesian statistical models for networks, time series, and text data that arise from complex social processes. David Blei is a professor of statistics and computer science at Columbia University, and a member of the Columbia Data Science Institute. Gabriele Blei is Co-CEO at Azimut Holding Spa. Supervisor: Hanna Wallach. Selected Abstracts Bayesian Nonparametric Customer Base Analysis with Model-based Visualizations Ryan Dew and Asim Ansari 19.Gungor Polatkan, Mingyuan Zhou, Lawrence Carin, David Blei, and Ingrid Daubechies, \A Bayesian nonparametric approach to image super-resolution," IEEE Trans. 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. 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. Prof. Blei and his group have set new paths in the fields of machine learning and artificial intelligence. Mingyuan Zhou and Lawrence Carin, \Negative binomial process count and mixture modeling," Advisors: George Hripcsak and David Blei Harvard. You do not have to pay any extra penny for this at all. Blei earned his Bachelor's degree in Computer Science and Mathematics from Brown University (1997) and his PhD in Computer Science from the University of California, Berkeley (2004). 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. 500 W. 120th Street #510 process”, by David Blei, Thomas L. Griffiths (student advisee), and Michael I. Jordan. A general recurrent state space framework for … In addition to working on topic models, Blei and his group have created generic algorithms for scaling a wide class of statistical models to massive data sets. in Music and Technology Fudan University, Shanghai, China 2006.9 { … 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. Journal of Machine Learning Research, 3:993–1022, January 2003. I am an Associate Professor of Electrical Engineering and Computer Science at MIT, part of both the Institute for Medical Engineering & Science and the Computer Science and Artificial Intelligence Laboratory. Room 1005 SSW Hosted by Prof. David M. Blei 2015 – 2016 (Competitive) Ph.D.