EDUCATION EMPLOYMENT. 2009: Elected to Member of IBM Academy of Technology.

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1 Jan 2018 CHIDANAND (Chid) APTE, Ph. D. Director, AI & Blockchain Solutions Industries Research IBM Research - T J Watson Research Center P. O. Box 218 Yorktown Heights, NY apte@us.ibm.com, EDUCATION Ph.D. in Computer Science, Rutgers University, New Brunswick, NJ, B.Tech. in Electrical Engineering, Indian Institute of Technology, Bombay, India, EMPLOYMENT Highlights of Technical Leadership Accomplishments: 7+ years in executive level management of large diversified technical organizations with responsibility to deliver on critical high visibility initiatives for IBM s strategic clients and product business units. 25+ years of handson technical experience in conducting and leading research projects in the areas of Applied Machine Learning, Data Analytics, and Data Science. Have driven innovations in machine learning for unstructured data analytics, distributed and parallel architectures for highly scalable analytics, petabyte-level industry data curation for performing data science at scale in IOT applications, industry solutions for Insurance, Marketing, Manufacturing, Agriculture, and Enterprise Business Processes. January 2017 Present: Director AI& Blockchain Solutions, Industries Research, IBM T.J. Watson Research Center. In addition to managing a core applied Data Science agenda for the department, have taken on expanded responsibilities to manage a larger organization for launching new initiatives in Blockchain technology and solutions, and AI Solutions for industries that leverage the department s core expertise in Optimization, Applied Math, Graph Algorithms & Databases, and Computational/Statistical Learning : Director, Mathematical Sciences, Industries & Solutions, IBM T. J. Watson Research Center. Lead and manage a 70 person organization. Department's research agenda covers theory and applications of Optimization, Data Science, and Operations Research. In addition to maintaining a basic research agenda in Mathematical Programming & Optimization, Operations Management, Statistical Modeling & Forecasting, Machine Learning & Predictive Modeling, and Data Mining Systems, teams are engaged in several solutions initiatives focused on Workforce Optimization, Predictive Asset Management, Resource & Operations Management, High-Performance (Big Data & HPC) Analytics, and emerging data-rich industries such as Healthcare, Agriculture, Energy & Utilities, and Traffic/Transportation. Responsible for setting and managing division worldwide research agenda in mathematical sciences and analytics. 2009: Elected to Member of IBM Academy of Technology : Senior Manager, Data Analytics Center, Mathematical Sciences Department., IBM T.J. Watson Research Center. Leading department s Statistics, Machine Learning, and Data Mining R&D programs. Line management for 3 first-line managers and 30 research scientists and engineers. Responsibilities include technical oversight of activities to ensure balanced delivery of impact to IBM and the scientific community, coordinating with peers in Research and across IBM, and line budget management Manager, Data Analytics Research Group, Mathematical Sciences Department, IBM T.J. Watson Research Center. Responsible for establishing and growing Math. Science dept s machine learning and data mining activity into a world-class organization. Initiated and led some of the

2 division s earliest client-partnership first-of-a-kind projects in the Business Intelligence / Data Mining area, with major IBM clients in Insurance, Retail, Distribution, Pharmaceutical, and Transportation industries. Founding chair of the Knowledge Discovery & Data Mining (KDD) professional interest community (PIC) in IBM Research : Research Staff Member, IBM Research Division, Yorktown Heights, NY. Conducted research in topics related to Expert Systems, Knowledge-Based Systems, Knowledge Representation, and Machine Learning Methods for Knowledge Acquisition. Conducted some of the earliest known work in applying machine learning to the document categorization problem, resulting in a seminal paper in ACM Transactions on Information Systems Numerous internal IBM Research Division awards for the development and broad deployment of the knowledge-based systems, data mining and business intelligence solutions and tools. Non-IBM Experience : Research Assistant, Department of Computer Science, Rutgers University. Conducted research in expert and knowledge-based systems Member of Technical Staff, RCA Astro-Electronics. Designed and developed flight control software for satellites Teaching Assistant, Department of Computer Science, Rutgers University. Assisted in teaching of undergraduate Computer Science courses in Machine Language and Systems Programming, and graduate level courses in Data Structures Research Associate, Department of Computer Science, IIT Bombay, India. Conducted research and development of one-pass in-core fast compilers for high level programming languages. PROFESSIONAL ACTIVITIES General Chair, ACM SIGKDD Conference on Knowledge Discovery and Data Mining, San Diego, CA, August Invited Plenary Keynote Speaker, SIAM Conference on Data Mining (SDM), 2011 General Program Chair, SIAM International Conference on Data Mining, 2008 General Program Chair, SIAM International Conference on Data Mining, 2007 Member of Editorial Board, Journal of Statistical Analysis and Data Mining, present Associate Program Committee Chair for SIAM Data Mining Co-Program Chair for IAPR Member of the Program Committee, ACM SIGKDD 1998, 2001, 2003, 2004, 2005, 2006, 2007, 2008 Member of the Program Committee, SIAM Intl. Conference on Data Mining, 2001, 2002, 2003, 2004, 2005 Member of the Program Committee, IEEE International Conference on Data Mining, Member of the Program Committee, International Conference on Machine Learning, ICML Member of the editorial board, International Journal of Intelligent Systems in Accounting, Finance, and Management, present. Associate Editor-in-Chief, IEEE EXPERT, Member of the Program Committee, IEEE Conference on AI Applications, 1990, 1991, 1992, 1993, 1994, Member of the Program Committee, International Conference on AI Applications on Wall Street, 1991, 1993, 1995.

3 Member of the Program Committee, International Workshop on AI in Economics and Management, 1993, Member of the editorial board, IEEE EXPERT, Co-Guest Editor, IEEE EXPERT Fall 1987 Special Issue on Financial Applications. Invited speaker at various industrial and university seminar and symposia series, at domestic as well as international locations. Participated in numerous Business Intelligence, Data Mining, and AI related technical conferences, and presented papers at many of these. Refereed and reviewed papers for Data Mining and Knowledge Discovery (DMKD) Journal, IEEE Transactions on Knowledge and Data Engineering (TKDE), IEEE COMPUTER, IEEE EXPERT, ACM SIGKDD, SIAM Intl. Conf. on Data Mining, NASA Intelligent Systems Program, IEEE conferences on AI applications (CAIA), ACM Computing Reviews, National conferences on Artificial Intelligence (AAAI), IBM Journal of Research and Development, IBM Systems Journal, and various other AI related technical publications and workshops. Senior Member of IEEE, Member of AAAI and ACM. SELECTED REFEREED PUBLICATIONS AND PATENTS With I. Mullins, B. Robson, S. Weiss et al., Data Mining and Clinical Data Repositories: Insights from a 667,000 Patient Data Set, Computers in Biology and Medicine, R. Natarajan, R. Sion, C. Apte, et al., A Grid-base Approach to Enterprise-scale Data Mining, Future Generation Computer Systems, N. Abe, N. Verma, C. Apte, R. Schroko, Cross-Channel Optimized Marketing, in Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Seattle, WA, P. Perner and C. Apte, Empirical Evaluation of Feature Subset Selection Methods, Engineering Applications of AI, N. Abe, C. Apte, et al., Sampling Approach to Resource Light Data Mining, SIAM Data Mining Conference, May R. Natarajan, R. Sion, C. Apte, I. Narang, A Grid-Based Approach for Enterprise-scale Data Mining, IEEE ICDM (International Conference on Data Mining), Nov C. Apte, Data Mining - The Big Dig, in ORMS Today, January C. Apte et al., Data Intensive Analytics for Predictive Modeling, in IBM Journal of Research and Development, January C. Apte et al., A Probabilistic Estimation Framework for Predictive Modeling Analytics, in IBM Systems Journal, August C. Apte et al., Business Applications of Data Mining, in Communications of the ACM, August 2002 C. Apte et al., Segmentation-Based Modeling for Advanced Targeted Marketing, in Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), San Francisco, August C. Apte et al., AI at IBM Research, in IEEE Intelligent Systems, Nov./Dec R. Vilalta, C. Apte, and S.M. Weiss, Operational Data Analysis: Improved Predictions Using Multi-Computer Pattern Detection, in Proceedings of the 11th IFIP/IEEE International Workshop on Distributed Systems: Operations & Management (DSOM 2000). Austin, Texas, USA. V. Iyengar, C. Apte, and T. Zhang, Active Learning using Adaptive Resampling, in Proceedings of ACM SIGKDD 2000.

4 S.M. Weiss, B.F. White, and C. Apte, Lightweight Document Clustering, in Proceedings of PKDD S.M. Weiss, B.F. White, C. Apte, and F. Damerau, Lightweight Document Matching, in IJCAI- 99 Workshop on Text Mining: Foundations, Applications, and Techniques, Also in IEEE Intelligent Systems, Volume 15, Number 2, March/April C. Apte et al., Probabilistic Estimation Based Data Mining for Discovering Insurance Risks, IBM Research Report RC-21483, in IEEE Intelligent Systems, Volume 14, Number 6, November/December S.M. Weiss, C. Apte, F. Damerau et al., Maximizing Text-Mining Performance, in IEEE Intelligent Systems, Volume 14, Number 4, July/August C. Apte et al., Insurance Risk Modeling Using Data Mining Technology, in Proceedings of The Third International Conference on The Practical Applications of Knowledge Discovery and Data Mining, April C. Apte, E. Pednault, S. Weiss, Data Mining with Extended Symbolic Models, in Proceedings of Joint Statistical Meeting (JSM 98), Statistical Computing Section, C. Apte, S. Weiss, F. Damerau, Text Mining with Decision Trees and Decision Rules, in Conference on Automated Learning and Discovery, Carnegie-Mellon University, June C. Apte et al., Decomposition of Heterogeneous Classification Problems, in Intelligent Data Analysis, Expanded version of paper with same title in proceedings of IDA 97, August C. Apte and S. Weiss, Data Mining with Decision Trees and Decision Rules, in Future Generation Computer Systems, November C. Apte, Data Mining - An Industrial Research Perspective, in IEEE Computational Science and Engineering, April-June C. Apte et al., RAMP: Rules Abstraction for Modeling and Prediction, IBM Research Division Technical Report RC C. Apte and S.J. Hong, Predicting Equity Returns from Securities Data with Minimal Rule Generation, In Advances in Knowledge Discovery, AAAI Press, C. Apte et al., Case Studies in High-Dimensional Classification, In Applied Intelligence, Vol. 4 No. 3, C. Apte et al., Automated Learning of Decision Rules for Text Categorization, In ACM Transactions on Information Systems, Vol. 12 No. 3, C. Apte et al., Towards Language Independent Automated Learning of Text Categorization Methods, In ACM SIGIR 94, July Y. Jang and C. Apte, Modeling Procedural Knowledge to Enhance Explanation Adequacy, In Proceedings of the 6th International Symposium on Artificial Intelligence Technology Transfer Conference, Sept C. Apte et al., Predicting Defects in Disk Drive Manufacturing: A Case Study in High Dimensional Classification, In Proceedings of the Ninth IEEE Conference on AI Applications, March S. Weiss, C. Apte et al., The Integration of Machine Learning and Knowledge Acquisition, In Proceedings of the 2nd Japanese Workshop on Knowledge Acquisition, November C. Apte et al., An Experiment in Constructing an Open Expert System Using a Knowledge Substrate, In IBM Journal of Research and Development, Vol 36, May C. Apte and J. Kastner, An object centered representation for financial analysis, In Expert Systems with Applications - An International Journal, Vol 3, Y. Jang and C. Apte, Rapid prototyping based on common substrate of knowledge, In Proceedings of the Seventh IEEE Conference on AI Applications, February 1991.

5 C. Apte et al., Utilizing knowledge intensive techniques in an automated consultant for financial marketing, In Proceedings of the Second International Conference on AI in Economics and Management, January C. Apte and R. Dionne, Building Numerical Sensitivity Analysis Systems Using a Knowledge Based Approach, In Proceedings of the Fourth IEEE Conference on Artificial Intelligence Applications, , March E. Mays, C. Apte et al., Experience with K-Rep: An Object Centered Knowledge Representation Language, In Proceedings of the Fourth IEEE Conference on Artificial Intelligence Applications, 62-67, March C. Apte and S. Weiss, An Expert Systems Methodology for Control and Interpretation of Applications Software, In International Journal of Expert Systems, 1(1):17-37, E. Mays, C. Apte et al., Organizing knowledge in a complex financial domain, In IEEE EXPERT, 2(3):61-70, Fall J. Kastner, C. Apte et al., A Knowledge Based Consultant for Financial Marketing, In AI Magazine, VII(5):71-79, Winter 1986/87. C. Apte and S.J. Hong, Using Qualitative Reasoning to Understand Financial Arithmetic, In Proceedings of the Fifth National Conference on Artificial Intelligence, , August C. Apte and S. Weiss, An approach to expert control of interactive software systems, IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-7(5): , Sept S. Weiss, C. Kulikowski, C. Apte, et al. Building Expert Systems for Controlling Complex Programs In Proceedings of the Second Annual National Conference on Artificial Intelligence, , August PATENTS 5 US Patents granted, additional under review.

M.S., Quantitative Finance, May 2009 Rutgers Business School - Newark and New Brunswick Rutgers, The State University of New Jersey, USA

M.S., Quantitative Finance, May 2009 Rutgers Business School - Newark and New Brunswick Rutgers, The State University of New Jersey, USA Keli Xiao, Ph.D. Contact Information Research Interests Harriman Hall 346 Tel: (631) 762-4760 College of Business Fax: (631) 632-9412 Stony Brook University E-mail: Keli.Xiao@stonybrook.edu Stony Brook,