Prof. Jaime Carbonell
Director LTI, Carnegie Mellon University, USA
Jaime is head of the Language Technologies Institute and Allen Newell Professor of Computer Science at Carnegie Mellon University. He is a world-renowned expert in the areas of information retrieval, data mining and machine translation. Jaime co-founded and took public Carnegie Group, a company in the IT services market employing advanced artificial-intelligence techniques.
His recent technology breakthroughs include Maximal Marginal Relevance (for information retrieval and summarization) and techniques for novel intelligence from massive data (in collaboration with DYNAMiX Technologies). Jaime has consulted for several Fortune 100 companies ranging from Caterpillar to Citigroup, in the general area of intelligent business methods and processes.
Professional Organizations and Activities
Member : ACM (elected Chair of SIGART 1983-85), ACL, AAAI (AAAI Fellow 1988-present, AAAI executive committee 1990-92), Cognitive Science Society, Sigma Xi, AMTA.
Government and other Committees : NSF/CISE Scientific Advisory Committee (2010-2014), NIH Human Genome Scientific Advisory Committee, aka “Watson Committee” (1988-1992). DFKI (National German AI Lab) Scientific Advisory Board (1988-2003). National Institute of Standards and Technology (NIST/IAD), Scientific Advisory Committee (1997-2001), DOE Oakridge National Laboratories Scientific Advisory Committee (1985-1987), GMD/IPSI Information Sciences (Germany) Scientific Advisory board (1990-2001), Citigroup Technology Advisory committee (1987-1995).
Book Series co-Editor : Lecture Notes in Artificial Intelligence North American editor, Springer (1996-2008).
Editorial Boards : Machine Learning Journal (1984-2000, editor-in-chief 1988-1993), Machine Translation Journal (1980’s), Artificial Intelligence Journal (1984-2008).
Research : Invented multiple well-known algorithms and methods in statistical machine learning including: Proactive Machine Learning (with Donmez) for multi-source cost-sensitive active learning, Linked Conditional Random Fields (L-SCRF, with Liu) for predicting tertiary and quaternary protein folds, new regularization-based transfer learning methods (with Kshirsagar), Maximal Marginal Relevance (MMR, with Goldstein) for information novelty, retrieval and summarization, topic-conditioned modeling for novelty detection, symmetric optimal phrasal alignment method for trainable example-based and statistical machine translation, series-anomaly modeling for financial fraud detection and syndromic surveillance, knowledge-based interlingual machine translation (and later extended it with colleagues: Tomita, Nirenburg, Nyberg, and Mitamura), transformational analogy for case-based reasoning, derivational analogy for reconstructive justification-based reasoning (with Veloso), robust case-frame parsing (with Hayes), Seeded Version-Space Learning (with polynomial complexity), and developed improvements to several other machine learning algorithms. Current research foci include robust statistical learning and mapping protein sequences to 3D structure and inferring functional properties, automated transfer-rule learning for Machine Translation, , enriched active transfer learning context-based machine translation, and machine translation for very rare languages.
Education : Created the PhD program at CMU on Language Technologies with 100’s of PhD graduates. Designed new courses in Language Technologies, Machine learning, Data Mining and eCommerce. Edited 3 books on Machine Learning. Taught undergraduate and graduate courses in Artificial Intelligence, Machine Learning, Software Engineering, Natural Language Processing, Language Technologies, Data Mining, Information Retrieval, Web-Based Architectures, Machine Translation, Algorithms, and related Computer Science topics. Other initiatives: Created the Center for Machine Translation at CMU in 1986, and the Language Technologies Institute in 1996. Co-creator & co-director of the Universal Library and million-book project (US, China, India). MT Summit chair 1991, Co-designer of interactive pinpointing speech tutor. Co-creator & co-PI of new Computational Biolinguistics Initiative at CMU. Helped create the CMU-Pitt Computational Biology Program.
1. Industrial Consulting : Meaningful Machines (participated in designing the context-based machine translation methods, 2002-2009).
2. Industrial Scientific : (data mining to improve workplace safety, 2008-present).
3. Carnegie Speech Inc : (business and technology strategy for intelligent language tuotoring, 2002-present).
4. Carnegie Group Inc : (expert systems & financial data mining: 1984-1997).
5. Citicorp : (financial data mining, real time transactions, new IT technology insertion: 1990-1998).
6. Lycos Inc : (launching the internet search engine 1998-1999).
7. Vivisimo : (2003-2006, scientific advisory board).
8. Searchline : (launched the new search engine, 2002-2004).
9. Wisdom Technologies : (financial optimization and data mining for corporate treasuries, large banks, etc. 1995-2003).
10. Dynamix Technologies : designed their large-scale data mining engine with applications to Homeland Security, AR/AP financial optimization, transactional optimization in bond trading and in re-insurance, pattern discovery in network-wire-transfer streams, syndromic surveillance, etc. 2000-present.
11. Peak Strategy : (financial analytics, investment, mining, 2005-2007), Boeing (designed their intensive data mining course).
12. Citibank : technology advisory board for 10 years, focusing on text and data mining, fraud detection, optimization methods, etc.
13. 10 other shorter-term engagements in data mining in industry, including financial data mining : Transactional fraud detection, instant-credit bad-dept minimization, collection effectiveness, cash-flow optimization (sweep/invest/float), data mining for risk/cost tradeoff minimization (FX, interest rate, counterparty, debt, etc), and so on. During these engagements process I designed or co-designed three data mining engines, and evaluated and help improve numerous other data mining engines, including the machine learning algorithms at their core.
14. Miscellaneous : Gave over 500 invited or refereed-paper presentations (colloquia, seminars, panels, addresses, conferences, key-notes, etc.). Received the IJCAI Best Paper Award in 1997 for translingual information retrieval. Received the CMU Computer Science Department’s teaching award (1987), the Sperry Fellowship for excellence in AI research (1986), unsolicited gifts from Alcoa and Hughes corporations for research in machine learning, and a “recognition of service” award from the ACM for the SIGART presidency (1983-1985). Provided congressional testimony on machine translation (1990). Leader of the NSF/JTEC study group on Japanese machine translation science and technology (1990-91). Principal investigator or major participant in research grants and contracts totaling over 90 million dollars since 1979 at the CMU School of Computer Science, Center for Machine Translation, and Language Technologies Institute.
15. Expert witness : Provided expert testimony and depositions, expert reports, advice, consulting , etc. in several cases involving intellectual property including: software design and copyrights, patents for data mining, patents for search engine algorithms and methods, speech recognition, integrated software systems, computational and statistical applications in finance, statistical machine learning, text mining, text processing, natural language, etc.
16. Patents : Inventor in several issued patents, provided advice on patentability of new software and methods, helped draft software-related patents, conducted prior art searches, composed responses to patent examiners, evaluated validity of issued patents As expert witness provided opinions and reports on patent infringement, patent validity (anticipation, obviousness), claim constructions, Inter Partes Reviews, etc.