Talks and presentations

• Video for an invited talk, KR for KBQA and KBC given at AKBC, June 2020. (This is the whole first day of the conference, my talk starts about 17:42, after the opening remarks.)
• An invited talk given at the The 16th International Conference on Principles of Knowledge Representation on Oct 27th - Nov 2nd 2018, in Tempe, Arizona.
• An invited talk given at the 28th International Conference on Inductive Logic Programming on September 2nd - 4th 2018, in Ferrara, Italy (there's also video for this talk).
• An invited talk given at Third International Workshop on Declarative Learning Based Programming (DeLBP), at AAAI-2018.
• An invited talk given at SNL-2017 (the 1st International Workshop on Symbolic-Neural Learning) in July 2017.
• An invited talk given at WAKBC-2016 in June 2016.
• Tutorial on statistical relational learning given at NAACL 2016 with William Wang (a shorter version of this was also presented at IJCAI 2016):
  • Part 1 - overview on logic, probability, MLNs, and probabilistic DDBs
  • Part 2 - ProPPR and applications
  • Part 3 - TensorLog, and other recent and current work
• Series of three lectures on probabilistic logic programs given at Singapore Management University in Feb 2016:
  • Background on logic and probabilistic models
  • Parameter learning and structure learning in ProPPR
  • Joint learning in ProPPR and comparing to neural approaches
• Can KR Represent Real-World Knowledge?, invited talk given March 2015 at the AAAI Spring Symposium on Knowledge Representation and Reasoning: Integrating Symbolic and Neural Approaches
• Learning to Reason with Extracted Information, keynote talk given March 2014 at Google's Natural Language Understanding Workshop, Zurich, Switzerland.
• Learning to Construct and Reason with a Large KB of Extracted Information, invited talk given August 2013 at the Inductive Logic Programming Conference, in Rio de Janeiro, Brazil.
• Reasoning With Data Extracted from The Biomedical Literature, invited talk at a joint session of the AAAI Fall Symposia on Discovery Informatics, and Information Retrieval and Knowledge Discovery in Biomedical Text.
• Learning Similarity Relations Based on Random Walks in Graphs, invited talk at CIKM 2012, October, 2012.
  • Earlier version of talk:Learning Relationships Defined by Linear Combinations of Constrained Random Walks, invited talk at the 9th Workshop on Machine Learning and Graphs, San Diego, CA, Aug 2011.
• Fast Effective Clustering for Graphs and Documents, given at CMU's LTI Colloquium Feb 10, 2012.
  • Earlier versions given at Virginia Tech in April 2010 and University of Pennsylvania in Feb 2010.
• Learning to Extract a Broad-Coverage Knowledge Base from the Web, invited talk at the Symposium on Data-Intensive Analysis, Analytics, and Informatics, Pittsburgh, PA Apr 2011.
• Open Information Extraction Methods: Computers that Learn to Read, invited talk at National Federation of Advanced Information Services (NFAIS), Philadelpha, PA, Feb 2011.
• Learning Proximity Relations Defined by Linear Combinations of Constrained Random Walks, given at a seminar at the University of Maryland in Sep 2010.
• Modeling Entity-Entity Links and Entity-Annotated Text, given at the ICML 2010 Workshop on Topic Modeling.
• Predictively Modeling Social Media, invited talk given at the 1st International Workshop on Mining Social Media, co-located with 13th Conference of the Spanish Association for Artificial Intelligence (CAEPIA-TTIA 2009).
• Matching and clustering product descriptions using learned similarity metrics, invited talk given at the IJCAI 2009 Workshop on Information Integration on the Web, July 2009. (Powerpoint; 6.7M)
• Open information extraction talks:
  • Graph-Based Methods for Open Information Extraction, talk given at Nov 2009 at MAVIR in Madrid, Spain.
  • Graph-Based Methods for Open Information Extraction, earlier version of talk given at Stanford and Google March 2009.
  • Graph-Based Methods for Open Information Extraction, still earlier version of the same talk given at a 2008 NIPS workshop.
  • A QT video of highlights from the workshop talks, including an incisive technical question addressed to me from my colleague Steve Fienberg.
• Embodied Cognition and Knowledge: Integration of Heterogeneous Databases without Common Domains Using Queries Based on Textual Similarity, talk given for my 10-year "Test of Time" Award at SIGMOD-2008(Powerpoint; 11Mb)
• Using Machine Learning to Discover and Understand Structured Data, invited talk given at LinkedData 2008. (Powerpoint; 6Mb)
• Machine Learning for Personal Information Management, invited talk given at ICMLA-2007. (Powerpoint; 8Mb)
• A Framework for Learning to Query Heterogeneous Data, invited talk given at IQIS 2006. (Powerpoint; 8Mb)
• On Beyond Hypertext: Searching in Graphs Containing Documents, Words, and Actual Data, invited talk given at DB/IR Day 2006. (Powerpoint; 6Mb)
• A Century Of Progress On Information Integration: A Mid-Term Report, an overview of information integration, focusing modestly on my own work, given as invited talk at WebDB-2005. (Powerpoint; 12Mb)
• Tutorials:
  • Information extraction (PowerPoint; 4.8Mb), aimed at folks somewhat familiar with statistical NLP methods. And thanks to Thierry Poibeau, there's also a version en francais (did I get that right, Thierry?) Also, two earlier versions of this are also still around, both given with Andew McCallum at recent conferences, KDD-2003(PowerPoint; 6.8Mb) and NIPS-2002.
  • Text classification (PowerPoint; 3Mb), given at a CALD Summer Course.
  • Collaborative filtering (PowerPoint; 9.1Mb), given at a DIMACS workshop.

• A mini-course on record linkage and matching:
  • Overview of record linkage methods(PowerPoint; 250kb).
  • Overview of distance metrics for strings(PowerPoint; 530kb).
  • Overview of using HMMs for normalizing text in record linkage tasks(PowerPoint; 640kb).
    It's not a presentation, but I have also put together a short annotated bibliography of record linkage and matching papers.
  • William Hayes has a nice summary of an extended discussion of string-matching tools on the BioNLP mailing list (July 2012).

• Other technical talks:
  • A presentation of my IJCAI-2005 results on "stacked sequential learning", presented in Edinburgh in August, 2005.
  • A presentation of my NIPS-2002 results on using bootstrapping techniques to improve web page classification, given at CMU in October 2002. (PowerPoint; 3.2mb).
  • A presentation of my WWW-2002 results on wrapper learning, presented in April 2002. (PDF; 170kb).
  • An overview of experiments with WHIRL. (PDF; 800kb).

Publications

Here's pointers to my DBLP page, my Scholar page, and my Arxiv page.
• A Computer Scientist's Guide To Biology is no longer available from this web page, but is now available from Springer. Here is a the TOC, introduction, index, and a sample chapter, from a late draft of the book; and also all the figures from the book in PowerPoint and all the figures in PDF. (The figures are a little prettier than the ones in the final book, which is black and white, not color).
• ICML 2006 Proceedings are available in print, for the true afficianado of fine learning-related research. It's well worth the money for the cover art alone (of course, all the papers are also available on-line for free.)
• Recent and selected publications. These are some representative publications for which on-line copies can be distributed.
• All publications. Here is an more-or-less complete chronological list of my publications. The bibliography includes pointers to on-line versions when I can provide them, but unfortunately copyright restrictions don't allow me to make all of my publications available on-line. Of course, reprints are always available from me on request.
• Publications by topic:
  • Matching/Data Integration
  • Text categorization
  • Information Extraction
  • Rule Learning
  • Collaborative Filtering
  • Applications
  • Formal Results
  • Inductive Logic Programming
  • Explanation-Based Learning

Students and other colleagues

• Daniel Spokoyny, LTI PhD student, co-supervised with Taylor Berg-Kirkpatrick.

Former students/colleagues:

• Katie Rivard Mazaitis, research programmer/analyst

• Jay Yoon Lee, CSD PhD student, co-advised with Jaime Carbonell, now a postdoc at UMass/Amherst.
• Bhuwan Dhingra, LTI PhD student, co-advised with Ruslan Salakhutdinov, now an Assistant Professor at Duke University.
• Zhilin Yang, former LTI PhD student, co-advised with Ruslan Salakhutdinov, now an Assistant Professor at Tsinghua University.
• Rose Catherine Kanjirathinkal, former LTI PhD student, now at Yahoo.
• Fan Yang (former MLD PhD student)
• William Yang Wang, former LTI PhD student, now an Assistant Professor at UCSB.
• Dana Movshovitz-Attias former CSD PhD student, now at Google.
• Bhavana Dalvi Mishraformer LTI PhD student (co-advised with Jamie Callan, now at AI2.
• Tae Yano, former LTI PhD student, co-advised with Noah Smith.
• Nan Li, former CSD PhD student, co-advised with Ken Koedinger, now at D. E. Shaw.
• Ramnath Balasubramanyan, former LTI PhD student.
• Mahesh Joshi, former LTI PhD student, co-advised with Carolyn Rosé
• Frank Lin, former LTI PhD student
• Ni Lao former LTI PhD student
• Richard C. Wang, former LTI PhD student co-advised with Bob Frederking.
• Andrew Arnold former MLD PhD student, now at Amazon.
• Einat Minkov former LTI PhD student, now at Haifa University.
• Vitor Rocha de Carvalho former LTI PhD student, now at SnapChat.
• Zhenzhen Kou former MLD PhD student, now at Google.

• Yifeng Tao, CMU Comp Bio PhD student, now supervised by Russell Schwartz.
• Edoardo Airoldi former MLD/Stats PhD student, co-advised with Steve Fienberg, now at Harvard.
• Pradeep Ravikumar former MLD PhD student, co-advised with Steve Fienberg, now at CMU.

• Haitian Sun, former MLD MS student, now a PhD student at CMU.
• Fan Yang, MLD MS student.
• Qiao Jin, School of Medicine, Tsinghua University, now supervised by Xinghua Lu.
• Ezra Winston, former MLD Master's student, now a PhD student in MLD.
• Lanxio (Karen) Xu, former MLD Master's student.
• Yuxing Zhang, former MLD Master's student.
• Jakob Bauer, former MLD 5th-year Master's student, now at Google. .
• Kavya Srinet, former MCDS Master's student.
• Bhawna Juneja, former MCDS Master's student.
• Tom Shen, former CMU CSD undergrad.
• Yu-Hsin Allen Kuo, former LTI MLT student, formerly co-advised with Natasa Miskov-Zivanov
• Rahul Goutam, former LTI MLT student, co-advised with Natasa Miskov-Zivanov
• Malcolm Greaves, former CSD master's student.
• Wen Haw Chong, PhD student at Singapore Management University, visted CMU in 2015-2016.
• Tuan Ahn Hoang, PhD student at Singapore Management University, visited CMU for 2012-2013 academic year.
• Freddy Chong Tat Chua PhD student at Singapore Management University, visited CMU for the academic year 2011-2012.

• Gustavo Lacerda former research assistant, co-supervised with Noboru Matsuda and Ken Koedinger.
• Lidong Bing, former postdoc.
• Ramesh Nallapati former postdoc, co-supervised with John Lafferty.
• Noboru Matsuda former postdoc, co-supervised with Ken Koedinger.

• Ja-Hui Chang visiting faculty from National Central University, Taiwan, 2007-2008.

• I have been an external committee member for the PhD theses of
  • John Zelle (degree from U Texas)
  • Misha Bilenko (from U Texas)
  • Daniel Kudenko (Rutgers)
  • Chumki Basu (Rutgers)
  • Ananlada Chotimongkol (CMU)
  • Wei-Hao Lin (CMU)
  • Cenk Gazen (CMU)
  • David Nadeau (U Ottowa)
  • Hanghang Tong (CMU)
  • Ben van Durme (Rochester)
  • Partha Talukdar (U Penn)
  • Andy Carlson (CMU)
  • Yifen Huang (CMU)
  • Swapna Sundaran (U Pitt)
  • Michael Heilman (CMU)
  • Jon Elsas (CMU)
  • Dipanjan Das (CMU)
  • Fan Guo (CMU)
  • Jana Diesner (CMU)
  • Freddy Chong Tat Chua (Singapore Management University).
  • Qirong Ho (CMU)
  • Danai Koutra (CMU)
  • Reyyan Yeniterzi (CMU)
  • YiChi Wang (CMU)
  • Steven Gardiner (CMU)
  • Jay Pujara (Univ Maryland)
  • Derry Wijaya (CMU)
  • Lingjia Deng (Univ of Pittsburgh)
  • Chenyan Xiong (CMU)
  • Tiancheng Zhao (CMU)
  • Pradeep Dasigi (CMU)
  • Shashank Srivastava (CMU)
  • Abulhair Saparov (CMU)
  • Danish Pruthi (CMU)
  I have also been an external committee member for the Master's theses of Mehrbod Sharifi (CMU) and Weam Abu-Zaki (CMU).

  I am currently a PhD committee member for Vidhisha Balachandran, Zhengbo Jiang, Luyu Gao, and Sankey Vaibhav Mehta.

  Other Stuff

  For those many friends whose research I have built on, be warned. My full name, "William Weston Cohen", is an anagram of the phrase "I now cite shallow men". (From Sara Cohen - no relation! - comes this warning: "Women's rights activists would probably request you to use the following anagram instead: 'I shall now cite women'".)

  Through my advisor, Alex Borgida, I can trace my "academic lineage" back to luminaries like Leibniz, Newton and Alfred Whitehead. Update: My former student Andrew Arnold has gone back even further, to Galileo!

  In 2014 I unearthed a strange relic from the past, a sort of game/website I wrote for my son Charlie back in...I'm gonna say, 1994, 1995, something like that, and I sort of made it work again, although JavaScript has changed a bit in the last couple of decades. (The main bugs have to do with sound-file presentation - in 1994 these were played by mime-file configured helper programs, not natively by the browser, so now you need to hit 'back' about 1/2 the time after a sound plays.) Historically interesting? You decide!

  Poetry anyone?

  ---