D. Randall Wilson

E-mail: randy@axon.cs.byu.edu
WWW: http://axon.cs.byu.edu/~randy

INTERESTS

• Genealogy.
• Machine learning & neural networks. (See my publications).
• Speech Recognition.
• Computer graphics. (See examples of my graphics creations).

8/97	Ph.D. in Computer Science at Brigham Young University, Provo, UT. Dissertation: Advances in Instance-Based Learning
8/94	M.S. in Computer Science at Brigham Young University, Provo, UT.
4/92	B.S. in Computer Science at Brigham Young University, Provo, UT. Minors in Math and Korean. GPA: 3.9 / 4.0.

6/2003-present	Principal Engineer, Information Architect, FamilySearch.org, Salt Lake City, UT. Spearheaded the Record Linkage team in creating tools, gathering data and developing algorithms to accurately identify matching records in a billion-person database with 80% recall and 99.5% precision. Helped develop new industry standards for modeling genealogical data.
5/97-6/2003	Research Scientist, fonix Corporation, Draper, UT. Did research in continuous speech recognition. Developed new, efficient speech decoder; created visualization tools to help analyze recognition results, and improved accuracy of neural networks and speech recognition engines.
1/2003-5/2003	Research Consultant, iArchives, Lehi, UT. Did part-time research in neural networks and language modeling for use in optical character recognition of printed materials scanned from microfilms.
5/92-4/97	Research Assistant, under Dr. Tony Martinez, BYU CS Department. Did research on Neural Networks and Machine Learning for use in a Ph.D. dissertation and other publications. Emphasis on instance-based learning algorithms.
1/96-3/96	University Instructor for C++ programming class (CS 290), BYU CS Department. Prepared & taught lectures on C, C++, and UNIX; created & maintained class WWW pages, wrote tests, supervised teaching assistants.
1/95-4/95	University Instructor for computer architecture class (CS 380), BYU CS Department. Taught lectures, maintained lecture notes on WWW, administered tests, etc.
9/92-4/93	Teaching Assistant for compiler class (CS 431), under Dr. Bill Hays, BYU CS Department. Helped students write a `C' compiler, answered questions on compiler theory, graded tests, and occasionally taught class.

8/86-8/88	Missionary, in the Korea Taejon Mission, for The Church of Jesus Christ of Latter-Day Saints.

• Ph.D. Assistantship, Fall 1994-Winter 1996.
  
• Graduated Magna Cum Laude.
  
• Academic Scholarships during nine semesters and three terms at BYU.
  
• Member of Phi Kappa Phi and National Honor Society.
  
• Appeared on Dean's List, Winter 1989, Winter 1990, Fall 1990, and Spring 1991.
  
• Eagle Scout.

• Wilson, D. Randall, and Tony R. Martinez, The Inefficiency of Batch Training for Large Training Sets, In Proceedings of the International Joint Conference on Neural Networks (IJCNN2000), Vol. II, pp. 113-117, July 2000.

• Wilson, D. Randall, and Tony R. Martinez, Reduction Techniques for Exemplar-Based Learning Algorithms, Machine Learning, vol. 38, no. 3, pp. 257-286, March 2000.

• Wilson, D. Randall, and Tony R. Martinez, An Integrated Instance-Based Learning Algorithm, Computational Intelligence, vol. 16, no. 1, pp. 1-28, 2000.

• Wilson, D. Randall, and Tony R. Martinez, Improved Heterogeneous Distance Functions, Journal of Artificial Intelligence Research (JAIR), Vol. 6, No. 1, pp. 1-34, 1997.

• Wilson, D. Randall, and Tony R. Martinez, Combining Cross-Validation and Confidence to Measure Fitness, In Proceedings of the International Joint Conference on Neural Networks (IJCNN'99), paper 163, 1999.

• Ventura, Dan, D. Randall Wilson, Brian Moncur and Tony Martinez, A Neural Model of Centered Tri-gram Speech Recognition, In Proceedings of the International Joint Conference on Neural Networks (IJCNN'99), paper 2188, 1999.

• Wilson, D. Randall, Dan Ventura, Brian Moncur and Tony R. Martinez, The Robustness of Relaxation Rates in Constraint Satisfaction Networks, In Proceedings of the International Joint Conference on Neural Networks (IJCNN'99), paper 162, 1999.

• Wilson, D. Randall, Advances in Instance-Based Learning Algorithms, Ph.D. Dissertation, Computer Science Department, Brigham Young University, August 1997.

• Wilson, D. Randall, and Tony R. Martinez, Instance Pruning Techniques, In Fisher, D., ed., Machine Learning: Proceedings of the Fourteenth International Conference (ICML'97), Morgan Kaufmann Publishers, San Francisco, CA, pp. 403-411, 1997.

• Wilson, D. Randall, and Tony R. Martinez, Improved Center Point Selection for Probabilistic Neural Networks, In Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms (ICANNGA'97), pp. 514-517, 1997.

• Wilson, D. Randall, and Tony R. Martinez, Real-Valued Schemata Search Using Statistical Confidence, In Proceedings of the 1997 Sian Ka'an International Workshop on Neural Networks and Neurocontrol, 1997.

• Wilson, D. Randall, and Tony R. Martinez, Bias and the Probability of Generalization, In Proceedings of the 1997 International Conference on Intelligent Information Systems (IIS'97), pp. 108-114, 1997.

• Wilson, D. Randall, and Tony R. Martinez, Heterogeneous Radial Basis Function Networks, Proceedings of the International Conference on Neural Networks (ICNN'96), Vol. 2, pp. 1263-1267, June 1996.

• Wilson, D. Randall, and Tony R. Martinez, Value Difference Metrics for Continuously Valued Attributes, Proceedings of the International Conference on Artificial Intelligence, Expert Systems, and Neural Networks (AIE'96), pp. 74-78, August 1996.

• Wilson, D. Randall, and Tony R. Martinez, Instance-Based Learning with Genetically Derived Attribute Weights, Proceedings of the International Conference on Artificial Intelligence, Expert Systems, and Neural Networks (AIE'96), pp. 11-14, August 1996.

• Wilson, D. Randall, Prototype Styles of Generalization, Master's Thesis, Computer Science Department, Brigham Young University, August 1994.

• Wilson, D. Randall, and Tony R. Martinez, The Importance of Using Multiple Styles of Generalization, Proceedings of the First New Zealand International Conference on Artificial Neural Networks and Expert Systems (ANNES), pp. 54-57, November 1993.

• Wilson, D. Randall, and Tony R. Martinez, The Potential of Prototype Styles of Generalization, The Sixth Australian Joint Conference on Artificial Intelligence (AI '93), pp. 356-361, November 1993.