Mountain View, CA ·
415-742-1185 ·
wcmac@cs·stanford·edu
Overview
Ph.D. in Computer Science from Stanford University, with focus on statistical natural language processing (NLP).
Expertise in artificial intelligence (AI), machine learning, data mining, information retrieval, and computational linguistics.
Extensive business experience: entrepreneurship, finance, technology development, and NLP consulting.
Current activities: Senior Research Scientist at Google; teaching at Stanford University; occasional consulting.
Professional Experience
2010-present:
Senior Research Scientist,
Google,
Mountain View, California
Research and development of algorithms for semantic analysis of user-generated text and user modeling.
2010-present:
Lecturer,
Stanford University,
Stanford, California
Winter 2012: teaching CS224U: Natural Language Understanding, a grad-level course on applied computational linguistics. 50 students.
Winter 2011: taught CS224N: Natural Language Processing, a grad-level course on statistical natural language processing. 60 students.
Winter 2010: taught CS224U: Natural Language Understanding. 40 students.
2009-2010:
Senior Research Scientist,
Aardvark,
San Francisco, California
Research and development of back-end algorithms, with particular emphasis on machine learning models and text analysis.
Designed algorithm used to assign topic labels to questions. Substantial contributions to question routing algorithms.
Developed system for automatic learning of user interests from social media (Facebook and Twitter status updates).
User modeling and preferential matching of askers & answerers with similar behavioral profiles.
Aardvark was acquired by Google in February 2010.
2007-2009:
Independent Consultant,
Palo Alto, California
Served as consultant and advisor to various companies seeking to
apply state-of-the-art NLP and machine learning techniques to
everyday business problems.
Worked on projects involving:
Extracting consumer opinions from online product reviews (sentiment analysis).
Developing a natural-language interface to a travel reservation system.
Applying machine learning methods in an online math tutoring system.
2006:
Intern,
Google Research,
Mountain View, California
Developed algorithms for automated question answering.
Gained experience with web-scale technologies, e.g. MapReduce.
2002-2003:
Researcher,
Knowledge Systems Lab,
Stanford University, Stanford, California
Pursued research in distributed AI: strategies for query-answering over
multiple (or partitioned) knowledge bases.
Participated in developing algorithms for
enabling efficient collaborative reasoning among disparate KBs, and
automatically decomposing large KBs into minimally-connected partitions.
Developed test suite for empirical validation and analysis of our
algorithms, using a variety of real-world KBs.
1999-2000:
Cofounder, VP Production,
SayIt, Inc.,
San Francisco, California
Secured $5.3M in venture funding, with Softbank as lead investor.
Designed, built, and tested initial website in only four months,
including highly-scaleable content-ranking mechanisms, browse and search
caches, and an interactive animation builder.
Website ranked in top 250 within 3 months of launch, with over 2
million unique visitors per month.
Managed web production team. Developed efficient production process,
including project queuing and prioritizing, technical standards, and
project specs.
Directly responsible for information architecture, UI design, and
usability analysis. Developed multidimensional content ontology.
1996-1998:
Quant/Trader,
D. E. Shaw & Co.,
New York, New York
Held primary responsibility for trading a $5 billion portfolio of
Japanese bonds and derivatives: JGB switches, swap spreads, box trades,
basis trades, listed vs. unlisted JGBs, dollar-yen basis swaps,
TIBOR-LIBOR swaps, euroyen futures, Japanese municipal bonds, FX forwards
and options.
Generated and analyzed trade ideas within a relative-value
(expectations arbitrage) framework.
Utilized quantitative valuation techniques and financial modeling,
including multi-factor yield curve models, no-arbitrage derivatives
pricing models, and mean-reverting stochastic processes.
Developed and maintained fixed-income analytics code in C, C++, Perl,
awk, SQL, bash, Tcl.
An extended model of natural logic
[pdf]
Bill MacCartney and Christopher D. Manning The Eighth International Conference on Computational Semantics (IWCS-8),
Tilburg, Netherlands, January 2009
A phrase-based alignment model for natural language inference
[pdf]
Bill MacCartney, Michel Galley, and Christopher D. Manning The Conference on Empirical Methods in Natural Language Processing (EMNLP-08),
Honolulu, HI, October 2008
Modeling semantic containment and exclusion in natural language inference
[pdf]
Bill MacCartney and Christopher D. Manning The 22nd International Conference on Computational Linguistics (Coling-08),
Manchester, UK, August 2008 —received Best Paper Award—
Natural logic for textual inference
[pdf]
Bill MacCartney and Christopher D. Manning ACL Workshop on Textual Entailment and Paraphrasing, Prague, June 2007
Learning Alignments and Leveraging Natural Logic
[pdf]
Nathanael Chambers, Daniel Cer, Trond Grenager, David Hall, Chloe Kiddon,
Bill MacCartney, Marie-Catherine de Marneffe, Daniel Ramage, Eric Yeh and
Christopher D. Manning ACL Workshop on Textual Entailment and Paraphrasing, Prague, June 2007
Aligning semantic graphs for textual inference and machine reading
[pdf]
Marie-Catherine de Marneffe, Trond Grenager, Bill MacCartney, Daniel Cer,
Daniel Ramage, Chloé Kiddon, Christopher D. Manning AAAI Spring Symposium at Stanford, 2007
Learning to recognize features of valid textual entailments
[pdf]
Bill MacCartney, Trond Grenager, Marie-Catherine de Marneffe,
Daniel Cer, Christopher D. Manning
Proceedings of the Human Language Technology Conference of the North
American Chapter of the Association for Computational Linguistics
(HLT-NAACL 2006)
Generating Typed Dependency Parses from Phrase Structure Parses
[pdf]
Marie-Catherine de Marneffe, Bill MacCartney, Christopher D. Manning
5th International Conference on Language Resources and Evaluation (LREC 2006)
Learning to distinguish valid textual entailments
[pdf]
Marie-Catherine de Marneffe, Bill MacCartney, Trond Grenager, Daniel
Cer, Anna Rafferty, and Christopher D. Manning Second Pascal RTE Challenge Workshop, 2006
Robust Textual Inference using Diverse Knowledge Sources
[pdf]
Rajat Raina, Aria Haghighi, Christopher Cox, Jenny Finkel, Jeff
Michels, Kristina Toutanova, Bill MacCartney, Marie-Catherine de
Marneffe, Christopher D. Manning, Andrew Y. Ng Proceedings of the First PASCAL Challenges Workshop, 2005
Solving Logic Puzzles: From Robust Processing to Precise Semantics
[pdf]
Iddo Lev, Bill MacCartney, Christopher D. Manning, Roger Levy Proceedings of the ACL-04 Workshop on Text Meaning and Interpretation,
July 2004
Practical Partition-Based Theorem Proving for Large Knowledge Bases
[pdf,
ps]
Bill MacCartney, Sheila A. McIlraith, Eyal Amir, Tomas Uribe Proceedings of the 18th International Joint Conference on Artificial Intelligence (IJCAI-03), August 2003
The Cycic Friends Network: Getting Cyc agents to reason together
[pdf,
ps]
James Mayfield, Tim Finin, Rajkumar Narayanaswamy, Chetan
Shah, William MacCartney & Keith Goolsbey Proceedings of the ACM CIKM-95 Intelligent Information Agents
Workshop, December 1995
Professional Service
I've served on the program committee or as a reviewer for several NLP conferences:
Reviewer, NAACL-HLT 2007
Reviewer, EMNLP 2008
Reviewer, NAACL-HLT 2009
Program Committee, TextInfer 2009
Program Committee, NASSLLI 2010 Workshop on Inference from Text