William W. Cohen Director, Research Engineering, Google AI News: I have moved to Google! Since June 2018 I have been starting up and leading a new research group in AI/ML based in located in Pittsburgh, in Google's Bakery Square location.

Biography

Dr. Cohen is a past president of the International Machine Learning Society. In the past he has also served as an action editor for the the AI and Machine Learning series of books published by Morgan Claypool, for the journal Machine Learning, the journal Artificial Intelligence, the Journal of Machine Learning Research, and the Journal of Artificial Intelligence Research. He was General Chair for the 2008 International Machine Learning Conference, held July 6-9 at the University of Helsinki, in Finland; Program Co-Chair of the 2006 International Machine Learning Conference; and Co-Chair of the 1994 International Machine Learning Conference. Dr. Cohen was also the co-Chair for the 3rd Int'l AAAI Conference on Weblogs and Social Media, which was held May 17-20, 2009 in San Jose, and was the co-Program Chair for the 4rd Int'l AAAI Conference on Weblogs and Social Media. He is a AAAI Fellow, and was a winner of the 2008 the SIGMOD "Test of Time" Award for the most influential SIGMOD paper of 1998, and the 2014 SIGIR "Test of Time" Award for the most influential SIGIR paper of 2002-2004.

Dr. Cohen's research interests include information integration and machine learning, particularly information extraction, text categorization and learning from large datasets. He has a long-standing interest in statistical relational learning and learning models, or learning from data, that display non-trivial structure. He holds seven patents related to learning, discovery, information retrieval, and data integration, and is the author of more than 200 publications.

Dr. Cohen is currently on leave from his position as a Professor in the Department of Machine Learning, with a joint appointment in the Language Technology Institute.

Announcements and FAQs

• I have moved to Google. I am leading a new research group in AI/ML that is located in Pittsburgh in Google's Bakery Square location. And case you're wondering - yes, we are hiring!

  Matt Gormley is the new Director of the Undergraduate Minor in ML. The new co-Directors of the MS in ML Program will be Nina Balcan and Ruslan Salakhutdinov

• Can I visit CMU and work with you?, or can I apply to CMU and work with you as a grad student? I will continue to advise my current students but I will not be taking any new students or hosting any visitors at CMU.

• What's the difference between 10-601 and ...? If you're having trouble with the MLD's growing menu of intro ML courses here's a draft of a document that explains the differences. If you're not sure if you're qualified, the prereqs for the course are listed on the course home page, and we're fairly strict about enforcing them for undergrads. Grad students should have equivalent experience: good programming skills - the equivalent of a one-semester college course - and some mathematical maturity, including prior exposure to calculus, probability and linear algebra. If you're not sure about your background there is a self-assessment test you can take.

Projects, Publications, Software, Datasets, and Talks

Teaching

• Fall 2018: 10-605/10-805 will be taught by Barnabas Poczos

• Spring 2018: Undergraduate Level Machine Learning with Large Datasets, 10-405, Mon-Wed 3:30-4:20 in GHC 4307
• Fall 2017: Machine Learning with Large Datasets, 10-605 and 10-805, Tues-Thus 1:30-2:50pm, PH 100.
• Fall 2016: Machine Learning with Large Datasets, 10-605 and 10-805, Tues-Thus 1:30-2:50pm, Wean Hall 7500.
• Spring 2016: Machine Learning 10-601, Mon-Wed time 10:30-11:50am, GHC 4401, with Maria-Florina Balcan.
• Fall 2015: Machine Learning with Large Datasets, 10-605 and 10-805, Tu-Thu 4:30-5:50am in Dougherty Hall 2210.
• Spring 2015: Machine Learning with Large Datasets, 10-605 and 10-805, Tu-Thu 10:30-11:50am in BH A51
• Fall 2014: 10-601 Machine Learning, Tu-Thu 1:30-2:50, Wean 7500
• Spring 2014: 10-605 Machine Learning with Large Datasets, Mon-Wed 1:30-2:50, Dougherty Hall 1112
• Fall 2013: 10-601 Machine Learning, Mon-Wed 4:30-5:50, Doherty Hall 2315 (with Eric Xing).
• Spring 2013: Machine Learning with Large Datasets, Mon-Wed 1:30-2:50, 4307 GHC
• Fall 2012: ML 10-802 and LTI 11-772 (Analysis of Social Media), 10:30-11:50pm Tues & Thus, 4303 Gates Building.
• Fall 2012: 10-915, the MLD Journal Club, 12-1:20pm Tue & Thu, 4101 Gates Building (with Roy Maxion).
• Spring 2012: Machine Learning with Large Datasets, Tues-Thurs 1:30-2:50pm, NSH 1305
• Fall 2011: Structured Prediction for Language and Other Discrete Data (SPLODD-2011), ML 10-710 and LTI 11-763, Tues-Thursday 3:00-4:20 in Gates-Hillman 4211. This is co-taught by myself and Noah Smith, and will include some subjects from Information Extraction and some from Language and Stats 2. A machine learning course (10-701 or consent of the instructors) is a prereq; we don't recommend that you take the course if you have already taken Information Extraction or Language and Stats 2.
• Spring 2011: ML 10-802 and LTI 11-772 (Analysis of Social Media), 10:30-11:50pm Tues & Thus, 4303 Gates Building.
• Spring 2011: 10-915, the MLD Journal Club, 3-4pm Mon & Wed, 4101 Gates Building.
• Fall 2010: 10-707 (Information Extraction - cross-listed in LTI as 11-748), 1:30-2:50pm Mon & Wed, Gates 4101. The first class is 9/8, the Wed after Labor Day, to allow incoming students time to attend the IC courses.
• Spring 2010: 10-802 (Analysis of Social Media).
• Fall 2009: 10-707 (Information Extraction), 1:30-2:50pm Mon & Wed, 5222 Gates Building.
• Spring 2008: 10-601 (Machine Learning) with Tom Mitchell, on 3-4:30 Mon & Wed in Wean Hall 5409.
• Fall 2007: Analysis of Social Media, Machine Learning 10-802 and LTI 11-772, with Natalie Glance (of Google Pittsburgh) - a brand-new seminar course. 4:30-6:30 Tuesdays in Wean Hall 4623.
  • Note: This site is the shattered remains of a once-beautiful wiki, created by the students of 10-802, generously hosted for free by ScribbleWiki, tragically lost (due a combination of RAID drive failures and low-bidder backup schemes), and then largely recovered using Warrick from various internel caches and archives.
• Fall 2007: Current Topics in Computational Biology (Journal Club), 02-701. (Announcements). Thursdays from 4:00-5:00 in 411 Mellon Institute (after Cell & Systems Modeling).
• Spring 2007: Information Extraction, Machine Learning 10-707 and LTI 11-748 - back by popular demand for the first time since 2004!
• Fall 2006: Current Topics in Computational Biology (Journal Club), 02-701. (Announcements)
• Spring 2006: Read the Web, CALD 10-709.
• June 21,23,25, 2005: A mini-course on Minorthird. Materials are below.
  • Slides, notes, and sample files from first day's lecture.
  • Slides, notes, and sample files from second day's lecture.
  • Powerpoint slides from third day's lecture.
  • Jar file for minorThird, if you only want to run the code, not compile it or read it. The installation process here is:
    1. Install Java 1.4 or higher (actually, JRE is all you need).
    2. Download the jar for minorThird and stick it in some directory.
    3. Optionally, download the sample data repository and unpack it into the same directory.
    4. Change to that same directory and then run Minorthird with the command
       java -Xmx500M -jar minorthird.jar

       What will pop up will be a small launch pad that can be used to start any of the UI programs. You can also start a particular main by specifying minorthird.jar as your classpath, for instance:
       java -Xmx500M -cp minorthird.jar edu.cmu.minorthird.ui.Help

  • If you want to do a real install here's the home page on Sourceforge, and a document on how to do a CVS install Minorthird.
• Spring 2004: "Learning to Turn Words into Data: Machine Learning Approaches to Information Extraction and Information Integration", CALD 10-707 and LTI 11-748.

Students and other colleagues

• Zhilin Yang, LTI PhD student, co-advised with Ruslan Salakhutdinov.
• Bhuwan Dhingra, LTI PhD student, co-advised with Ruslan Salakhutdinov.
• Fan Yang, MLD PhD student.
• Daniel Spokoyny, LTI PhD student, co-supervised with Taylog Berg-Kirkpatrick.

• Haitian Sun, MLD MS student.
• Qiao Jin, School of Medicine, Tsinghua University

Long-term colleagues

• Katie Rivard Mazaitis, research programmer/analyst, CMU

Former students

• Rose Catherine Kanjirathinkal, LTI PhD student.
• Yifeng Tao, CMU Comp Bio PhD student, co-supervised with Xinghua Lu.
• William Yang Wang (former LTI PhD student, now at UCSB).
• Dana Movshovitz-Attias (former CSD PhD student, now at Google).
• Bhavana Dalvi Mishra (former LTI PhD student (co-advised with Jamie Callan, now at AI2)
• Tae Yano, (former LTI PhD student, co-advised with Noah Smith, now at Microsoft)
• Nan Li, (former CSD PhD student, co-advised with Ken Koedinger, now at D. E. Shaw)
• Ramnath Balasubramanyan, (LTI PhD student, now at Twitter)
• Mahesh Joshi, (former LTI PhD student, co-advised with Carolyn Rosé, now at EBay)
• Frank Lin, (former LTI PhD student, now at AirBnB)
• Ni Lao (former LTI PhD student, now at Google)
• Richard C. Wang, (former LTI PhD student co-advised with Bob Frederking, now at Baidu).
• Andrew Arnold (former MLD PhD student, now at Point 72 Asset Management)
• Einat Minkov (former LTI PhD student, now at Haifa University)
• Vitor Rocha de Carvalho (former LTI PhD student, now at QualComm)
• Zhenzhen Kou (former MLD PhD student, now at Google)

• Ezra Winston, MLD Master's student.
• Lanxio (Karen) Xu, MLD Master's student.
• Yuxing Zhang, MLD Master's student.
• Jakob Bauer, MLD 5th-year Master's student .
• Kavya Srinet, MCDS Master's student.
• Bhawna Juneja, MCDS Master's student.
• Tom Shen, CMU CSD undergrad
• Yu-Hsin Allen Kuo, 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.
• Edoardo Airoldi (former MLD/Stats PhD student, co-advised with Steve Fienberg)
• Ja-Hui Chang (visiting faculty from National Central University, Taiwan, 2007-2008)
• 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 in my group).
• Freddy Chong Tat Chua (PhD student at Singapore Management University, visited CMU for the academic year 2011-2012 in my group.)
• Gustavo Lacerda (former research assistant, co-supervised with Noboru Matsuda and Ken Koedinger, now at UBC)
• Lidong Bing, former postdoc, now at Tencent.
• Ramesh Nallapati (former postdoc, co-supervised with John Lafferty, now at IBM Watson)
• Noboru Matsuda (former postdoc, co-supervised with Ken Koedinger, now System Scientist in CMU's HCII)
• Pradeep Ravikumar (former MLD PhD student, co-advised with Steve Fienberg)

• 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)
  • Pradeep Dasigi (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 an external committee member for Tiancheng Zhao, Shashank Srivastava, and Abulhair Saparov.

  Other important people

  Jo Cohen is an up-and-coming member of the Pittsburgh technical theatre scene. He mainly works as lighting designer or electrician, in primarily in the Pittsburgh area (and occasionally elsewhere). Oh, and I'm their proud father.

  Contact Info

  William W. Cohen
  Professor, Machine Learning Department
  Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213
  8217 Gates Hillman Complex
  (shipping address: 6105 Gates Hillman Complex)
  voice: 412-268-7664 / fax: 412-268-2205
  Assistant: Dorothy Holland-Minkley, GHC 8001, dfh@andrew.cmu.edu
  

  My preferred email address for CMU-related matters is: wcohen AT cs DOT cmu DOT edu