Olcay Boz
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  • 1. OBJECTIVE: Research and Development position in Analytics, Data Mining, Machine Learning. SKILLS: • Data Mining, Data Analysis, Knowledge Discovery, Machine Learning, Artificial Intelligence, Neural Networks, Decision Trees, Multilinear Regression, Logistic Regression, Expert Systems, Genetic Algorithms, Natural Language Processing, Feature Subset Selection. • Perl, C++, C, Java, JavaScript, SQL, SAS, Visual Basic, Awk, Clips, Lisp, Prolog, LaTeX, CVS, RCS, SCCS. • WWW based application development using Perl, Java, CGI, DBI, Servlets, HTML, DHTML and XML. • Development and usage of C++, STL libraries, Object Oriented Perl modules and Java libraries. • Unix (Solaris, AIX), Linux and Microsoft Windows environments. • Relational Databases (Oracle, MS SQL Server), Database Design, ERWin, Visio WORK EXPERIENCE: October 2006 – February 2008 Senior Staff Scientist BasePoint Analytics LLC, Carlsbad, CA • Developed credit and debit card fraud models. Models are developed using feed forward neural networks. • Developed a new method for explaining the outputs from Neural Networks for the credit card fraud models. • Developed new Perl scripts for statistical data evaluation and data validation and transformation. • Developed new C++ programs for model evaluation. • Developed real time referral optimization techniques for real time fraud detection for credit card companies to stop the riskiest fraud transactions at the point of sale. With the optimization techniques we developed we maximize the amount of fraud detected with minimum number of referred or declined transactions. • Worked on new product development for detecting credit card fraud for online transactions. • Worked on scoring and evaluation solutions for mortgage fraud and early payment default for Mortgage Lenders and Investment Banks. April 2003 – September 2006 Senior Staff Scientist Fair Isaac Corporation, San Diego, CA • Designed and developed transaction data driven predictive models for credit and debit card fraud detection, credit card risk analysis/prediction, predicting credit card attrition and account profitability using neural networks, machine learning, statistical modeling, pattern recognition, and artificial intelligence. • The main responsibilities included: analyzing and understanding large amounts of historical transactional data to determine suitability for modeling, data clean-up and filtering, pattern identification and feature extraction, feature (variable) selection, experimenting with different types of algorithms and modeling techniques, analyzing performance, preparing model reports for communication with internal and external clients, participating in pre-sales, and providing post implementation support. • Supervised and trained junior analytic modelers. • Developed new software tools and libraries used in model development, data analysis and conversion and model performance analysis. Jan 2002 – March 2003
  • 2. Systems Engineer AT&T Labs, Middletown, NJ • Developed System and Design Requirements for Integrated Order Management (IOM) System. • Designed and maintained the Design of IOM Oracle Database by using ERWin and Visio. • Designed screens for IOM application which is a web based application. • IOM is intended to provide a common user portal to AT&T Business Services’ service-specific ordering infrastructures (Data/IP, Voice, Local Voice) to facilitate customer-concentric ordering of both standalone and bundled services. Jan 2000 – Dec 2001 Senior Software Designer and Software Development Team Leader IBM Global Services, Middletown, NJ • Software development team leader in two WWW based database application projects. • Both applications are Object Oriented Perl CGI applications using DBI to connect to ORACLE database in Unix (Solaris) environment. • Developed Object Oriented Perl Modules for CGI, HTML and Database access. • Developed an easy to use PERL XML parser that can be used for parsing or constructing XML files. • Database access modules enable user to access the tables and fields in the database by using their names directly that makes programming easier and shortens development time. 1998 - 1999 Research Assistant Lehigh University, Bethlehem, PA • Conducted research on development of a large Internet enabled Java based database application. • Supervised 15 undergraduate students working in the project. • Instructed lectures on JDBC and SQL to undergraduate students working in the project. 1995 - 1998 Data Mining Research Scientist AT&T Segmentation Scoring Platform District – Data Mining team, Piscataway, NJ • Conducted research on customer status prediction and knowledge discovery in Segmentation and Scoring Platform Database in collaboration with AT&T Labs researchers. Used neural networks and symbolic machine learning techniques (C4.5 and Ripper). • Created a system which would help marketing managers predict future customer status and extract interesting and usable knowledge from the database. Used customer call usage data, customer status information and demographics data for prediction and data mining. • Developed a new technique for feature subset selection using Neural Networks. • Developed C++ classes for making handling of very large data files easier for Segmentation and Scoring of long distance customer data warehouse in Unix (Solaris) environment. • Developed a multi-threaded sort program for sorting very large data files in Unix (Solaris) environment. 1993 – 1995 Research Assistant Lehigh University, Bethlehem, PA • Conducted research on knowledge based engineering design and modeling. Used several C++ class libraries and CLIPS expert system shell. 1987 - 1991
  • 3. Senior Software Design Engineer Nortel Networks R&D, Istanbul, Turkey • Designed and developed software packages (e.g. 3-Way conference call, wake up service) for DMS exchanges for Nortel Networks. • Supervised five software designers and consulted thirty software designers. • Instructed the course "Introduction to PROTEL and DMS development environment". AWARDS: 1991 - 1993 NATO Science scholarship from TUBITAK (The Scientific and Research Council of Turkey) for Ph.D. in Computer Science. EDUCATION: Lehigh University, Bethlehem, PA. Ph.D. Computer Science, December 1999 Fields of specialization: Artificial Intelligence, Data Mining, Machine Learning, Decision Trees, Neural Networks, Expert Systems, Feature Subset Selection, Discretization. Ph.D. Thesis: "Converting A Trained Neural Network To A Decision Tree - DecText - Decision Tree Extractor." In real life applications (especially in Data Mining applications) understandability of the knowledge acquired by a Machine Learning system is very important. DecText addresses the understandability problem of Neural Networks by converting the knowledge acquired by the Neural Network into a classical C4.5 like Decision Tree. Another contribution of this thesis is a new Feature Subset Selection technique. Choosing a subset of the features will increase accuracy and reduce complexity of the acquired knowledge. Tested the new technique on real world and artificial datasets and compared its results with existing methods. Showed that the new method chooses good subsets by searching fewer states than the existing methods. Developed libraries and programs in C++ and STL in Linux environment for testing the results of the research Istanbul Technical University, Istanbul, Turkey M.S. Control and Computer Engineering, February 1990. Fields of specialization: Global optimization, numerical analysis techniques and optimization in control system design. M.S. Thesis: "A new global optimization technique and application to control system design." Bogazici University, Istanbul, Turkey B.S. Electrical and Electronics Engineering, July 1987. PROFESSIONAL ACTIVITIES: Member, ACM SIGKDD PUBLICATIONS: Boz, Olcay (2002). “Extracting Decision Trees From Trained Neural Networks”, KDD-2002 The Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining , July 23 - 26, 2002
  • 4. Boz, Olcay (2002). “Converting A Trained Neural Network To A Decision Tree DecText - Decision Tree Extractor”, The 2002 International Conference on Machine Learning and Applications (ICMLA'02) June 24 - 27, 2002 Boz, Olcay (2002). “Feature Subset Selection by Using Sorted Feature Relevance”, The 2002 International Conference on Machine Learning and Applications (ICMLA'02) June 24 - 27, 2002 Boz, Olcay (1997). “Customer Status Prediction and Knowledge Discovery in Segmentation Scoring Platform Database” AT&T Technical Report, AT&T September 1997. Boz, Olcay (1995). “Knowledge Integration and Rule Extraction in Neural Networks.” Technical Report, EECS, Lehigh University. October 1995. Decker, R., Lee, D.H., Jin, H., Boz, O. (1995). "Generic Engineering Design Using Design Scripts", 9th Conference with Industry, Information Resources in Manufacturing, Center For Manufacturing Systems Engineering, Lehigh University, Bethlehem, PA, May 23-24, 1995. Tigli, O., Eksin, I., Ertem, S., Boz., O. (1994)."Global Optimization Method in Controlling a Plant", Elsevier Science 1994, Electric Power Systems Research. Tigli, O., Eksin, I., Ertem, S., Boz. O. (1992). "Optimal Control of a Plant Using Global Optimization Method", Modeling and Simulation, Vol 23, Part4, Proceedings of the twenty-third Annual Pittsburgh Conference, April 30 - May 1, 1992, Pittsburgh, PA. Tigli, O., Eksin, I., Ertem, S., Boz., O. (1992). "Global Optimization Method in Controlling a Plant", Third biennial Symposium on Industrial Electric Power Applications, New Orleans, Louisiana, 1992. Boz, Olcay, Eksin, I., Goren, L. (1989). “A New Global Optimization Technique for Multivariable Functions and Application to the Design of Systems”, Third National Conference in Electrical Engineering, Istanbul, Turkey, 1989. PRESENTATIONS: Boz, Olcay (194). “Expert Knowledge Management System. Porting Lupes to X, Express Clips Integration and Tool Domain Knowledge.”, Semiconductor Research Corporation (SRC)/Lehigh Annual Review, Lehigh University, PA. Presented two posters on “Expert Knowledge Management System and Engineering Design” in the annual SRC/Lehigh Annual Review in 1993 and 1994.