www.CustomChamberMusic.com/calistri-yeh

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Actively seeking a new position in the NJ or NYC area. Looking for a senior technical leadership role where my contributions can directly affect the direction and future success of a company, and when that direction can make a positive difference in people's lives.

15+ years experience designing and building pragmatic intelligent systems in academic, corporate research, and commercial settings.
10+ years experience managing multi-site software teams and subcontractors, ranging from 2-25 scientists, engineers, and analysts.
Ph.D. in artificial intelligence.

Proven track record of transforming innovative research into commercial products. Excellent abilities in design, management, strategic analysis, innovation, and communication at all levels.

Research and application interests include:

• Data Mining: classification, clustering, knowledge extraction, statistical & probabilistic reasoning, text mining
• Heuristics: intelligent architectures & interfaces, personalization, plan recognition & planning, user modeling
• Search Engines: information retrieval, multilingual / cross-lingual search, natural language, text analysis

Senior Director of Search Technology (2009-present)

Senior Director of Context Mining and Content Management (2008-2009)
Director of Context Mining (2006-2008)
Responsibilities include search heuristics for billions of webpages and images, personalization for millions of users, content classification and quality analysis, vertical search optimization, and tools for user productivity and back-end analysis. Directed up to 25 people on 3 continents. Mentored other managers, worked closely with other business units and partner companies. Many projects are proprietary/confidential. Live products from my teams can be seen on:

• www.ask.com (Zoom related search with path-based personalization, spell checker, web results with geo-biased personalization, triggering & content for specialized vertical search, major components of ranking)
• www.dictionary.com (Related search, crossword solver)
• www.rushmoredrive.com (customized search for black community)

Director of Research (2000-2006)
Responsible for all science/research decisions and overall science direction of the company. Provide technical management and leadership for a geographically distributed team of up to 11 scientists, linguists, and analysts. Involved in all aspects of project planning, proposal writing, and customer presentations. Major projects include:

• Semantic Signatures contextual advertising product places highly relevant ads on any webpage in real time. Principal inventor of the underlying Trainable Semantic Vector technology.
• CINDOR (Conceptual Interlingua for Document Retrieval) cross-language search.
• ContentTailor / ShrinkText summarization and readable text compression for wireless devices.

Head of Advanced Technology (1998-2000)
Responsible for developing new technology to support the next generation of company products and services. Managed a distributed team of 4 scientists and made direct contributions to projects. Our core research result was a new method for domain-trainable semantic indexing of text. This research resulted in several short-term commercial spin-offs including subject-based document retrieval, real-time clustering and classification, auto-generated trainable custom thesaurus, and an automatic query expander for a natural-language search engine.

Computer Scientist (1996-1998)
Principal architect and implementer of the processing system of MAPIT and PatentMiner, the first commercial natural-language data mining systems that search and analyze the full text of millions of patents in real time. Designed and implemented the indexing module, query processing module, visualization tools, and overall system architecture. Built working prototype with live data in 5 days; first paying customer in 6 months. Personally processed over 100GB of patent text (subsequent updates were handled by a team of three full-time people). Designed and implemented distributed hardware configuration for fault-tolerant real-time search (50% cheaper and 300% faster than original).

Manager, Artificial Intelligence Group (1993-1996)
Project manager and principal investigator of a three-year government contract with Cornell University and the University of Iowa to build an intelligent planning architecture using techniques from planning, scheduling, machine learning, and distributed computing. Successfully delivered both innovative research breakthroughs and practical solutions to a specific customer problem in large-scale transportation scheduling.

Computer Scientist (1990-1993)
Created blackboard architecture design for a passive radar system. Designed and implemented new method of archiving security audit messages for secure distributed operating system. Designed and implemented network monitoring system to simulate Navy communications traffic. Implemented Bayesian belief network to diagnose radio faults.

PhD in Computer Science, Brown University, 1990 (advisor: Eugene Charniak).

MS in Computer Science, SUNY Albany, 1987.

BS summa cum laude in Computer Science and Mathematics, SUNY Albany, 1986.
Minors: German, Russian, Music, Statistics.

Member of AAAI, ACL, ACM, IEEE Computer Society, Phi Beta Kappa, Sigma Xi.

Classical cellist, composer, and arranger. Principal cellist of Livingston Symphony Orchestra and Synergismus Duo. Founder and CEO of Custom Chamber Music.

Author of numerous published papers and patents. Selected titles:

N. Habash, C. Mah, S. Imran, R. Calistri-Yeh, and P. Sheridan, "Design, Construction and Validation of an Arabic-English Conceptual Interlingua for Cross-language Information Retrieval." In Proc. 5th International Conference on Language Resources and Evaluation (LREC-2006), 107-112, 2006.

R.J. Calistri-Yeh and A.M. Segre, "ALPS: An Adaptive Learning and Planning System." Rome Laboratory Technical Report RL-TR-96-225, 1997.

R.J. Calistri-Yeh, A.M. Segre, and D. Sturgill, "The Peaks and Valleys of ALPS: An Adaptive Learning and Planning System for Transportation Scheduling." In Advanced Planning Technology: Technological Achievements of the ARPA/Rome Laboratory Planning Initiative (ARPI-96), 89-96, AAAI Press, May 1996.

Y. Zhu and R.J. Calistri-Yeh, "Iterative Plan Repair in ALPS." Technical Report TM-95-0067, ORA, Ithaca NY, September 1995.

R.J. Calistri-Yeh and A.M. Segre, "ALPS: An adaptive learning and planning system." In Proc. TECOM Artificial Intelligence Technology Symposium, 309-326, September 1994.

R.J. Calistri-Yeh, "Applying Blackboard Techniques to Real-Time Signal Processing and Multimedia Network Management." In Proc. 7th Int'l Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE-94), 593-599, Austin, TX, June 1994.

R.J. Calistri-Yeh and A.M. Segre, "The Design of ALPS: An Adaptive Learning and Planning System." In Proc. 2nd Int'l Conference on Artificial Intelligence Planning Systems (AIPS-94), 207-212, Chicago, IL, June 1994.

R.J. Calistri-Yeh, "Iterative Strengthening: An Algorithm for Generating Anytime Optimal Plans." In Proc. 6th Int'l Conference on Tools with Artificial Intelligence (TAI-94), 728-731, New Orleans, LA, November 1994. Also appears in Proc. ARPA / Rome Laboratory Knowledge Based Planning and Scheduling Initiative Workshop (ARPI-94), 3-13, Tucson, AZ, February 1994.

R.J. Calistri-Yeh, "An A* Approach to Robust Plan Recognition for Intelligent Interfaces." In N.G. Bourbakis, ed., Applications of Learning and Planning Methods, vol. 26 of World Scientific Series in Computer Science, 227-251, Teaneck, NJ, 1991.

R.J. Calistri-Yeh, "Utilizing User Models to Handle Ambiguity in Robust Plan Recognition." In User Modeling and User-Adapted Interaction: An International Journal, 1(4):289-322, 1991.

R.J. Calistri, "Classifying and Detecting Plan-Based Misconceptions for Robust Plan Recognition." In AI Magazine, 12(3), 34-35, AAAI Press, Fall 1991.

R.J. Calistri, "Classifying and Detecting Plan-Based Misconceptions for Robust Plan Recognition." Ph.D. dissertation, Department of Computer Science, Brown University, Providence, RI, May 1990.

D.L. Snyder and R.J. Calistri-Yeh, "Management and Analysis of Document Information Text." US Patent #6,038,561, issued 2000.

R.J. Calistri-Yeh, B. Yuan, G.B. Osborne, and D.L. Snyder, "Construction of Trainable Semantic Vectors and Clustering, Classification, and Searching using Trainable Semantic Vectors." US Patent #6,751,621, issued 2004.

R.J. Calistri-Yeh, B. Yuan, G.B. Osborne, and D.L. Snyder, "Construction of Trainable Semantic Vectors and Clustering, Classification, and Searching using Trainable Semantic Vectors." US Patent #7,299,247, issued 2007.

R.J. Calistri-Yeh, B. Yuan, G.B. Osborne, and D.L. Snyder, "Construction of Trainable Semantic Vectors and Clustering, Classification, and Searching using Trainable Semantic Vectors." US Patent #7,406,456, issued 2008.

R.J. Calistri-Yeh, B. Yuan, G.B. Osborne, and D.L. Snyder, "Construction of Trainable Semantic Vectors and Clustering, Classification, and Searching using Trainable Semantic Vectors." US Patent #7,444,356, issued 2008.

R.J. Calistri-Yeh, B. Yuan, G.B. Osborne, and D.L. Snyder, "Construction of Trainable Semantic Vectors and Clustering, Classification, and Searching using Trainable Semantic Vectors." US Patent Application #2004/0193414, published 2004.

R.J. Calistri-Yeh, B. Yuan, G.B. Osborne, and D.L. Snyder, "Construction of Trainable Semantic Vectors and Clustering, Classification, and Searching using Trainable Semantic Vectors." US Patent Application #2004/0199505, published 2004.

R.J. Calistri-Yeh, B. Yuan, G.B. Osborne, and D.L. Snyder, "Construction of Trainable Semantic Vectors and Clustering, Classification, and Searching using Trainable Semantic Vectors." US Patent Application #2004/0199546, published 2004.

R.J. Calistri-Yeh, W. Ruan, C.P. Mah, M.L. Howatt, M.E. McKenna, and M.J. Forrester, "Advertisement Placement Method and System Using Semantic Analysis." US Patent Application #2005/0216516, published 2005.

R.J. Calistri-Yeh, B. Yuan, G.B. Osborne, and D.L. Snyder, "Construction of Trainable Semantic Vectors and Clustering, Classification, and Searching using Trainable Semantic Vectors." US Patent Application #2008/0281814, published 2008.