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  • 2013 Presentations

Decision CAMP 2013 Speakers & Talks

Aziz Boxwala, MD, PhD, FACMI  
Meliorix - Principal

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Aziz is a Principal with Meliorix Inc. 

His expertise is in clinical decision support and medical knowledge management.  He currently is one of the Subject Matter Experts in the Health eDecisions initiative established by
the Office of the National Coordinator for Health Information Technology.

Dr. Boxwala has a blend of experience, having worked in the Health IT industry at startups and large enterprises, and in academia in Informatics programs at Harvard Medical School and most recently at the University of California San Diego.

Heath eDecisions: Knowledge Interoperability for Healthcare

The  Health eDecisions project has developed specifications for interoperable knowledge artifacts for use in healthcare. These artifacts specify, for different clinical scenarios, the logic and applicable patient care actions in a computable form. The artifacts can be implemented within healthcare applications, such as clinical decision support systems, either as-is or translated into the native format of the application. The presentation will provide the motivation for the Health eDecisions project, the specification,  and its applications.

Talk on Wednesday in the Healthcare track


Dr. Benjamin Grosof
Benjamin Grosof & Associates - President
Coherent Knowledge Systems - Co-Founder
RuleML - Co-Founder

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Benjamin is an industry leader in knowledge representation, reasoning, and acquisition. He has pioneered semantic technology and industry standards for rules, the combination of rules with ontologies, the applications of rules in e-commerce and policies, the acquisition of rules and ontologies from natural language, courteous defeasibility, and restraint bounded rationality.  He co-founded RuleML and has had driving roles in W3C RIF and OWL-RL.  He has experience in a wide variety of application areas as well as in machine learning and probabilistic reasoning. 

Previously, he led a large research program in rule-based AI at Vulcan Inc. for Paul G. Allen (2007-2013), was an IT professor at MIT Sloan (2000-2007), and was a senior software scientist at IBM Research (1988-2000). His background includes 4 major industry software releases, a Stanford PhD in computer science, a Harvard BA, and over 50 refereed publications.

Making Very Expressive Rules Practical in Logic and Text

Motivated by requirements from many domains, including policy-based decision-making,  we present two case studies in: 
  • Financial risk management, specifically banking regulatory compliance; and also
  • Biomedical
that utilize:
  • A new method of reasoning with highly expressive, yet scalable, semantic rules.  The rules employ a new logic, Rulelog, that extends the logic of databases to include
    defeasible higher-order logic formulas, bounded rationality, and other meta power.  The rules extend, and work well together with, ontologies as well.  RIF-Rulelog is in draft as a standards submission from RuleML to W3C.   
  • A new approach to natural language processing (NLP) that does logic-based mapping between English text and Rulelog knowledge.  Called Textual Logic, it includes new methods for fully explaining decisions / conclusions in English, and for rapid authoring of rich semantic rules starting from nearly unrestricted English.  The meaning of an English sentence is captured deeply and precisely. 
  • Defeasibility handles the logical (inconsistency) conflict and exceptions that are practically inevitable in NLP, empirical knowledge, and large knowledge bases acquired from and maintained by distributed users.
* Work supported in part by Vulcan, Inc., Seattle, WA, USA

Talk on Tuesday


Brian Stucky
Allegiance Advisory Group - Managing Director of Business Decision Management

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A recognized thought leader in the area of business rules, Brian brings well over two decades of experience designing and implementing business rule and process management systems for both commercial and Federal clients.  

He has implemented and managed business rule development efforts in a variety of financial services domains including the secondary mortgage market, credit card marketing and processing, mutual fund portfolio analysis, and insurance underwriting and risk management.
 
At Freddie Mac, Brian served as the Enterprise Rule Steward where he set the business and technology strategy for business rule development across the corporation.  These efforts  resulted in Freddie Mac winning a 2005 ADT Magazine Innovator Award in the category of Component-Based Development (”Freddie Mac redesigns its processes to satisfy new customer needs”) and being named a finalist for a 2005 Mortgage Technology Magazine “10X” Award.  

Brian works closely with a number of business rule vendors and
speaks internationally at conferences and professional events.  He has given presentations at the Business Rules Forum, European Business Rules Conference, Mortgage Bankers Association Technology & Annual Conference, the Brainstorm Business Process Management Conference Series, and was an invited panelist at a Gartner Group Financial Services Summit.  He was also a contributing author to “The Business Rules Revolution” and to “The Decision Model”.

Decision Management and Financial Services: A Brave New World

The Financial Services industry was one of the earliest adopters
of Business Rule and Process approaches across a variety of applications.  Process-centric enterprises where business rules were prevalent found these techniques to be a perfect fit for their day-to-day operations. As the platforms enabling rule and process solutions evolved, the Financial Services industry went through dramatic changes culminating in the crisis of 2008. Now Decision Management – both as a methodology and a technology – has been viewed as both a culprit and a necessity moving forward in a new era of financial regulation and scrutiny. The presentation will discuss the current state of Decision Management and its role in the new world of Financial Services.

Talk on Wednesday at 8:30am in the Financial Services track


Carlos Serrano-Morales
Sparkling Logic - Co-Founder & CTO

Carlos Serrano-Morales
Carlos started his career working for major European technology projects as well as at the European Space Agency, focusing on distributed real-time systems and real-time diagnosis software. He later co-founded a startup providing front-office trading systems for the European derivatives financial market.

He joined AI pioneer Neuron Data in its early days, worked on Nexpert Object, expert system leader, and then was at the origin of Blaze Advisor, which helped bring about the BRMS revolution to business applications. He was later responsible for all Decision Management technologies at FICO, including business rules, predictive analytics, optimization and decision analysis, as well as the company’s Enterprise Architecture group.

Carlos is now co-founder and CTO for Sparkling Logic, where he has helped create the next generation award-winning Decision Management platform with SMARTS™.

Carlos holds a number of patents in real-time and decision management systems, and is a frequent speaker at trade conferences.

@casmrv

Adaptive Decision Management

Automated Decision Management, relying mostly on the concrete application of business rules, predictive modeling and optimization technologies, has established itself as a core component of large business applications. While these applications are largely configured and managed based on the knowledge elicited from experts and data, they also need to take into account the fact that a lot is not known in advance in terms of the outcome of the decisions they make.

This talk will focus on approaches to achieve adaptive decision management, and in particular the corresponding technology and architecture implications.

Adaptive Decision Management complements and extends rules, analytics and optimization approaches with the capability to include feedback from the outcome of decisions into online and offline processes that evolve the configuration of the decisions to account from the lessons learned from the analysis of these outcomes.

Talk on Tuesday

Decision Management Champion

Talk on Monday

CTO Panel

Carlos will participate in the CTO Panel representing Sparkling Logic

Talk on Tuesday


Carole-Ann Matignon
Sparkling Logic - Co-Founder & CEO

Carole-Ann Matignon
Carole-Ann is co-founder and CEO of Sparkling Logic, a leader in Decision Management technology.  

Over her 15+ years in Decision Management, she has consistently brought
innovation in the business rules and decision management space, which has been recognized by leading industry analysts Gartner and Forrester.  She holds several patents in decision management and adaptive modeling.

Carole-Ann started her career building Expert Systems and Business
Intelligence dashboards, then specialized in Business Rules / Optimization at ILOG and finally led the vision and direction for Blaze Advisor & Decision Management tools at FICO.  She is a passionate & renowned blogger and speaker.

@cmatignon

Big Data versus Big Knowledge

How do you extract your business rules?  Do they reside in the head of your experts?  Do they hide in your data?  
  
There are 2 camps leveraging different technologies: analytics and business rules.  In this talk, we will talk about the strengths and weaknesses of these approaches, and when and how you should use them.
 
With the explosion of data, there is a fantastic opportunity to improve decision making.  While accessibility has been addresses, the velocity and variety of data is becoming a new challenge.  The data scientist shortage will force us to look at analytics in a different way.  Are analytics applicable to all and any problems?  Those are some of the considerations we will ponder while looking at practical usage of analytics and business rules.

Talk on Monday


Dr. Charles Forgy
Production Systems Technologies - CTO
Sparkling Logic - Strategic Advisor

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Charles is the CTO of Production Systems Technologies and a Strategic Advisor to Sparkling Logic. Charles has been involved with rule engines for decades.  In the mid
1970’s he developed the Rete algorithm while a Ph. D. candidate at Carnegie-Mellon University.  After graduating in 1979, he remained at Carnegie-Mellon on the research faculty, where he was co-principal investigator of a DARPA-funded project to develop special hardware for rule engines.  In 1983, he co-founded Production Systems Technologies (PST) to continue research and development of rule engine technology. The primary business of PST is to customize and license rule engines for embedding in large systems.  At PST he developed the more efficient Rete-II and Rete-NT versions of the Rete algorithm, as well as a parallel rule engine for handling high volume and high velocity data.

Charles met his future wife, Diana, while at Carnegie-Mellon. 
Charles and Diana still live in Pittsburgh, PA.  They have three children and two grandchildren.

Writing Concise Rules

Recent years have seen major advances in the expressiveness of rule languages.  By taking advantage of these new capabilities, developers can write rules that are both easier to understand and easier for the rule engines to process.  

In this talk, I will show examples of rules written in the older style
alongside equivalent rules written in the new style.  Measurements made of a typical rule engine running these rules will be presented.  The results will show that the new features can sometimes make huge differences in the efficiency of programs. While the examples will be in a specific language (OPSJ) these capabilities are in fact available in many languages today, so the techniques shown are quite general.

Talk on Tuesday


Chris Adzima
eBay - Senior  Engineering Manager

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Chris is a Trust and Safety Rules Analyst at eBay.com. Chris has been an analyst at eBay for over 7 years and has been writing business rules for over 2. 

He focuses on projects that ensure quality communication between eBay customers. 

Aside from that main focus, he also creates and manages rules for Half.com focusing on the prevention of fraud and loss due to stolen financial instruments.

More about Chris

Using business rules to increase eCommerce sales by managing customer-to-customer relationships

Talk on Tuesday

eBay has over 105 million active members.  These customers communicate with each other using our platform by sending  over 2 million messages a day. In some cases this communication is used to drive business away from eBay and to other platforms and companies. We call this activity Grey Market member to member communications. Not only does this grey market activity hurt eBay's revenue, it leaves buyers without the protection that transacting through eBay provides.

With so many messages sent through the eBay message system each day, we needed quick analysis and turnaround to ensure we had a product in production as soon as possible. Using an agile business rules approach, I created rules  that would detect and prevent
these grey market transactions from being  initiated. This agility significantly reduced our cost to implement and has  provided an amazing ROI. My rule set has increased site Gross Merchandise  Sold (GMS) by $200 million a year. With the success of this initial phase, I  am now creating more rules to increase detection and provide more revenue for  the company.

Key take-away
• Greater ROI by utilizing a small team to manage and create
business rules
• Using Business rules to prevent customer to customer
communications that harm company revenue
Building business rules based on keyword data mined from customer to  customer communications

Christian Middleton
Jawbone - Senior  Engineering Manager

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Christian is a Sr. Engineer Manager of the UP Platform at Jawbone, leading the
architecture and development of backend services, as well as the integration of
Jawbone’s APIs with external partners and developers. Previously, he led the Games team at hi5. He was a PhD student in Computer Science at the Universitat Pompeu Fabra, under the supervision of Ricardo Baeza-Yates. In 2004 he earned an MSc degree, as well as a Computer Science Engineer, at the Universidad de Chile. His main interests are Web mining, search engines, and building high performance systems.

Facts, Rules, and Constraints for Uncovering Health and Wellness Insights

Keeping  consumers engaged in their efforts to acquire and maintain a healthy lifestyle is a continuing challenge. In this talk, we describe a rule-based “eco system” in which information from a wearable sensor is synchronized with a smartphone that, in turn, synchronizes with the cloud. 

Specifically,  movement and sleep data is retrieved from the sensor
device via the phone;  this data is then integrated with dietary and geolocation data stored on the phone, and then aggregated with other user’s data on the cloud.  This talk describes how Jawbone implemented a cloud based RBS in order to notify users with insights that inform them of their progress towards a healthy lifestyle.  The social aspect of the application allows building rules that  incorporate data from friends and people with similar characteristics, providing more interesting insights.

Talk on Wednesday in the Healthcare track


Colleen McClintock
Sparkling Logic - VP Products

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Colleen has been involved in business rules and decision management for over 20 years.

Early in her career she co-founded a consulting company focused on automating complex business policies using rule-based technologies.  

She later joined ILOG where she led the product management and marketing team and evolved JRules from a simple java rule engine component to the market-leading BRMS, acquired by IBM in 2009.  At IBM she worked with IBM research on next-generation decision management projects and introduced decision discovery and documentation in IBM's cloud offering, Blueworks Live.


Decision Management Primer with SMARTS

Learn the basic concepts and benefits of decision management and get hands-on experience using SMARTS  to develop a small decision
service!

Please bring a laptop for hands-on exercises
Wifi connection will be provided

Talk on Monday in the Decision (boot) CAMP series

SMARTS Decision Management Front-End for DROOLS

Learn how to use SMARTS decision management environment
for decision services deployed to DROOLS.

Talk on Wednesday in the Decision (boot) CAMP series


Claude Nanjo
Cognitive Medical Systems - Senior  Software Architect

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Claude is a Senior Software Architect at Cognitive Medical Systems.

Prior to joining Cognitive Medical Systems, Claude was Senior Software Architect at Zynx Health where he focused on the modeling of Evidence-Based Clinical Decision Support (CDS) concepts to support dynamic content generation and clinical decision support services.

Claude is also an active participant in the Health eDecision initiative and in an ongoing HL7 initiative to harmonize e-Clinical Quality Measure and CDS models.

Moving From Content to Knowledge - The Semantic Annotation of Clinical Content for Clinical Decision Support

Today, Evidence-Based Clinical Decision Support knowledge exists primarily in document form and is generally population-based. However, there has been a recognition in the field that CDS knowledge needs to be patient-centric, dynamic, and computable in order to be more impactful at the point-of-care and within clinical workflows. To achieve this aim, CDS knowledge must be captured and structured on sound semantic models which are commonly understood and accepted.

Though no one model entirely meets this need today, this presentation will describe efforts in this direction thanks to encouraging trends in Industry.

Talk on Wednesday in the Healthcare track


Dr. Davide Sottara, PhD
Department of Biomedical Informatics at Arizona State University - Assistant Professor

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Davide got his M.Sc. Degree (2006) and his Ph.D (2010) in Computer
Science, Electronics and Telecommunications from the University of Bologna.

His research and development interests include artificial intelligence in general and decision support systems in particular, focusing on hybrid systems combining predictive models and rule-based systems. 

Since 2006, he has been working on the development of intelligent DSSs in the environmental (in cooperation with the Italian National Agency for the Energy, Environment and New Technologies) and clinical field. He is a member of the Drools Community, contributing to the core engine research and development, as well as leading an experimental sub-project on the support of various forms of non boolean reasoning (uncertain, fuzzy, semantic and subsymbolic). 

After working as an independent private consultant and as a post-doc researcher at the University of Bologna, he is currently an Assistant Professor at the Department of Biomedical Informatics at Arizona State University in Scottsdale (AZ), where he works on knowledge representation and reasoning techniques for clinical decision support.

Soft Decision Making for Healthcare Problems

Medicine is not an exact science and clinical practice is mostly based on evidence, which necessarily includes some degree of uncertainty. Clinical Decision Support (CDS), however, is traditionally based on (clinical) guidelines and rules, and implemented with a combination of (business) rules, workflow-based processes and event processing techniques.

None of these frameworks are suitable to model and process the uncertainty required by clinical decision making, while more suitable probabilistic and fuzzy techniques have not yet become mainstream technologies in the field.

In this talk, we will discuss possible methodologies to integrate "hard" and "soft" decision making, ranging from loosely coupled systems to tightly coupled reasoners.

Talk on Wednesday in the Healthcare track


Dr. Emory Fry, MD
Cognitive Medical Systems - Founder & Chief Medical Informatics Officer

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Dr. Fry, a neonatal intensive care specialist by training, has over 15 years of experience in the design and development of enterprise clinical information systems for the Department of Defense. 

With a particular interest in cognitive science and workflow optimization, Dr. Fry was the Principle Investigator for numerous research initiatives in Clinical Decision Support (CDS), the original architect for the Military Health System’s Nationwide Health Information Network program during 2008-2009, and the Technical Director for the Department of Defense Virtual Lifetime Electronic Record demonstrations in San Diego, 2010.

Dr. Fry retired from active service in 2012, and is a founder and the Chief Medical Informatics Officer at Cognitive Medical Systems in San Diego, CA.

Architecting Cognitive Environments for HealthCare

Dr. Fry will discuss the role of information technology in enabling
organizations to create cognitive environments conducive to the delivery of quality healthcare, highlighting synergies that can arise when workflow, decision-making, and resources are optimally aligned.

He will introduce Socratic Grid, an emerging open source Clinical Decision Support (CDS) platform providing a living laboratory for exploring the knowledge management, business intelligence and predictive analytic technologies required for advanced cognitive and workflow support.

Dr. Fry will argue that open-source, standards-based knowledge management architectures that can be integrated with diverse health information systems are essential to improving care and delivering quality healthcare at scale.

Talk on Wednesday in the Healthcare track


Dr.  Evgeny Selensky
Trimble UK - Scheduling/Optimization Specialist

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Evgeny has been doing research and development in Scheduling and Combinatorial Optimization since 2000. His projects involved collaboration with ILOG (France) and Bausch & Lomb (Ireland). Since 2005 to date, he has held a position Scheduling / Optimization Expert in Advanced Technology Team of Trimble Field Service Management. 
 
Prior to joining Trimble FSM, Evgeny did research on scheduling and optimization for Glasgow University and University College Cork as well as on mechanics of solids for Keldysh Institute of Applied Mathematics, Russian Academy of Sciences. He also worked as an analyst and technical author in information security (Jet Infosystems, Moscow).

 He has served as a reviewer of various conferences in AI. Currently, he is a member of the Editorial Board of Applied Intelligence Journal (The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies, Springer Journal no.
10489).

Evgeny holds a PhD degree from Moscow State University (1999) for research in robot motion simulation and control. Evgeny also serves in Cambridge, UK as a Russian Orthodox priest, Patriarchate of Moscow. 

Rules-based Mobile Resource Learner for Field Scheduling Applications

Businesses today face increasing challenges in trying to efficiently use available resources in order to maximize return on investment and minimize environmental impact.  In the field scheduling and mobile resource allocation market, there are plenty of sophisticated scheduling products available.  However, to start using these products business users have to feed them with such key characteristics of their mobile workforce as service locations where technicians can operate as well as their expertise (skills) in performing particular jobs such as equipment repair, testing,  installation and maintenance.  While an initial configuration of the field scheduling product is time-consuming, the real-world challenge is to maintain and adjust this information on a daily  basis.  So, to use these products efficiently, it is critical to automate these processes and to teach the  scheduling system how to learn this information based on the actual field service assignments.
   
In this presentation we describe a rules-based mobile resource learner that  addresses these problems in conjunction with a highly popular field scheduling tool.  The learner enables the system to learn and adjust information about multi-level technical skills  and geographic areas of the customer field service workforce. It allows a new  customer to start using the scheduler with zero-configuration by just  analyzing an actual history of technician work assignments.  The learner uses a relatively small set of  easily configurable rules that encode how workforce skills and locations are  learned dynamically. The learned information is then fed into the  scheduler/optimizer tool to improve schedule quality.  

The usage of the learner is demonstrated on a few simple
examples.

Talk on Tuesday


Gil Segal
Sapiens - Head of Practice for DECISION

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Gil is the Head of Practice for DECISION at Sapiens, where he plays an instrumental role in the vision and
development of the company’s decision management technology.  

Gil is recognized as an industry expert and consultant in decision management with more than 25 years’ experience architecting, developing, and implementing rules and decision-based systems in large-scale organizations across the globe.

Gil’s experience with decision and process management enabled him to play a leading role in the creation of Sapiens DECISION, the first enterprise-grade business decision management system, built upon KPI’s The Decision Model (TDM) framework.  

Gil received his MBA in Information Systems and Operations Research
from Tel Aviv University, and his undergraduate degree in Computer Studies and Applied Mathematics from Northwestern University.

Decision Management Champion - Freedom for IT: Write Once, Run Anywhere

Today’s rules management systems and processes are chained to the
execution environment and lack the ability to rapidly adapt and evolve along with the ever-changing demands of the business.  Sophisticated business logic management is critical to the organization’s success, yet few organizations have the ability to run the same business logic organization-wide, with consistency and accuracy.  That is where decision management (DM) comes in.

In this session, Gil Segal of Sapiens will share insights about the future of decision management and how decision management systems empower the business while freeing IT to do what IT does best. We will demonstrate how enterprise-scale decision management systems provide the ability to deploy the same business logic to multiple technological environments, and will discuss the benefits to IT of using a BDMS as part of an overall decision management
architecture.

Talk on Monday


Dr. Harold Boley
RuleML - Chairman

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Harold is adjunct professor at the Faculty of Computer Science, University of New Brunswick, and chair of RuleML Inc.

His specification of Web rules through RuleML, currently developed beyond Version 1.0, has found broad uptake. It has been combined with OWL to SWRL, has become the main input to the W3C Recommendation RIF, and is now used for OASIS LegalRuleML. Harold’s recent innovations in data-plus-knowledge representation include PSOA RuleML and Grailog. 

His work on Rule Responder has enabled deployed distributed applications for the Social Semantic Web.

Keynote - From Data to Knowledge through Grailog Visualization

Directed labeled graphs (DLGs) provide a good starting point for
visual data & knowledge representation but cannot straightforwardly
represent nested structures, non-binary relationships, and relation
descriptions. These advanced features require encoded constructs with auxiliary nodes and relationships, which also need to be kept separate from straightforward constructs. Therefore, various extensions of DLGs have been proposed for data & knowledge representation, including graph partitionings (possibly interfaced as complex nodes), n-ary relationships as directed labeled hyperarcs, and (hyper)arc labels used as nodes of other (hyper)arcs.

Meanwhile, a lot of AI / Semantic Web research and development on ontologies & rules has gone into extended logics for knowledge representation such as object (frame) logics, description logics, general modal logics, and higher-order logics. The talk demonstrates how data & knowledge representation with graphs and logics can be reconciled. It proceeds from simple to extended graphs for logics needed in AI and the Semantic Web. Along with its visual introduction, each graph construct is mapped to its corresponding symbolic logic construct. These graph-logic extensions constitute a systematics defined by orthogonal axes, which has led to the Grailog 1.0 language as part of the Web-rule industry standard RuleML 1.0.

Grailog has been used for teaching Logical Foundations of Cognitive Science and Semantic Web Techniques, and is being explored for PSOA RuleML querying of relational data in Clinical Intelligence.

Talk on Wednesday in the Healthcare track


Hidetoshi Sako
Blaze Consulting Japan, inc. - CEO

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Hidetoshi is a pioneer of the BRMS industry in the Japanese market.  For over 17 years, he has been working with major System Integrators, mainly in Financial Services, to help them automate operational decisions.

He has delivered Business Rules-based solutions such as Online Banking CRM to Insurance Underwriting, and Risk Management.

His career started at Neuron Data in 1992 where he started developing approaches for rules implementation and managed rules-based development.  He is passionate about educating Japanese system engineers in Decision Modeling and how to build more competitive business system, focusing on the Asian market.

Hidetoshi holds a MD of economics at Waseda Univ.

Recently, Nikkei BP has selected Hidetoshi as one of 100 IT leaders in
Japan
.


Using Business Rules to Address Insurance Fraud and Claims Leakage in Asia

Insurance fraud is a growing problem in Asia and the majority of fraud detection systems have relied on statistics and analytics which require a sufficient quantity of fraud data to be effective.  Small and medium-sized insurance companies, and many large insurance companies in Asia lack this data, and some attempts and deploying these systems have met with resistance from the business-side since they could not understand the output from these systems. 

InsuPector is a next-generation insurance fraud detection system design to address these issues.  Rather than relying solely on analytics and the availability of sufficient fraud data,  InsuPector, built on Sparkling Logic SMARTS Decision Management System, combines analytics with over 500 fraud  patterns that can be extended to meet the company's specific needs and refined and improved through a built-in performance monitoring feedback loop. InsuPector was designed to allow claims experts to customize and extend the business rules so that new products and fraud cases can be easily added.

In this session you will learn:
  • Why previous generation fraud detection systems failed to meet the needs of many Asian insurance companies
  • How InsuPector was designed to address the short-comings of these systems
  • How InsuPector offers greater ROI than previous insurance fraud detection systems 

Talk on Wednesday in the Financial Services track


Jacob Feldman
OpenRules - CTO

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Dr. Jacob Feldman is a founder and CTO of OpenRules, Inc., a NJ corporation that created and maintains the popular Open Source Business Decision Management System commonly known as "OpenRules".  He has extensive experience in
development of decision support software using Business Rules, Optimization, and
Machine Learning technologies for real-world mission-critical applications.  He has 5 granted patents in the area of Business Rules and Constraint Programming.
 
Jacob is a frequent presenter at the major decision management
events. He is also a specification lead for the JSR-331 standard.

@Jacob_OpenRules

How to Build Smarter Decision Models Capable Of Making Optimal Decisions

Decision modeling practitioners frequently face situations when a decision model has to analyze multiple alternative decisions to come up with an optimal one. Traditional decision modeling approaches mainly rely on business rules and/or scorecards to determine one “good” decision and in most cases do not backtrack to consider potentially better decisions. The reason is simple:  even for relatively small decision models with 20-40 decision variables it is physically impossible to manually create rules that cover all (!) possible combinations of decision variables and to find a decision that minimizes a total cost or maximizes resource utilization.

In this presentation we describe how “Decision Optimization” utilizes off-the-shelf optimization tools to help a business user to create smarter decision models that are capable to find decisions that minimize/maximize certain optimization objectives. Instead of trying to specify all possible rules, a decision model creator uses decision tables to represent only major business constraints and relationships between different decision variables. An optimization objective may be represented as a special decision variable defined on other key variables.  A decision optimization component does the rest of work by automatically considering multiple alternatives and selecting the best one within a time limit defined by a user.  Contrary to traditional rule engines, the optimization component is specifically designed to solve constraint satisfaction and optimization problems using proven optimization techniques such as constraint and/or linear programming.  We will demonstrate decision optimization at work using two real-world use cases.

Talk on Tuesday

Decision Management Champion

Talk on Monday


James Owen
KBSC

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James has been involved in rulebased systems on a professional basis beginning in 1997 with Neuron Data Nexpert at FedEx LEC&C VEA project and later with ND Advisor version 2.0.  In 1998-99 he worked with Dr. Charles Forgy on the Ericsson Geobility project using OPSJ.  Later, he ventured out into JRules 3.0 at Bell South with Dr. Forgy and Dr. Hafedh Mili on the PARIS project.  James has worked for InfoWorld as a featured editor writing many BRMS articles since 2004.  He has consulted with Lloyds TSB in London, O2 in Müchen, ILOG in Paris and most of the Fortune 100 companies in the USA. 

James has a BS in Electrical Engineering from Louisiana Tech and an MBA from LSUS.  

Presently he resides in Fort Worth, Texas, near DFW where he attends his son's Blues/Jazz gigs nearby whenever he is in town and his wife's art festivals.  They have a Rhodesian Ridgeback and a Golden Retriever for company. 

Successful Rule Projects: Why Some Are And Some Are Not

Talk on Tuesday

Most initial BRMS (Business Rule Maintenance System) – or Rulebased – projects are often approached in the same manner:  Someone hears of a successful project that has been done by another company, usually at a trade show or seminar, and they hear of the outrageous claims of savings in time and money and, being human, they want these same kind of savings for  their company as well.  So they contact a rule vendor or two or three and have them come to their company and do a presentation of what they can do for them.  The vendor’s sales staff will, naturally, promise almost anything to get the order.  

The customer, if they don’t have someone on staff who has been on such a project in the past, will be at the mercy of the vendor’s sales staff for the truth.  Having been on upwards of 30 or more rule  projects in many different industries over the past twenty years, mostly successful, some not, I have become somewhat experienced on what makes up a successful project. 

In this talk James will present some of the factors that make up a successful project and some of the pitfalls that a good manager should look out for to prevent a failure.

Talk on Tuesday


James Taylor
Decision Management Solutions - CEO & Principal Consultant

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James is a leading expert in how to use business rules and analytic technology to build Decision Management Systems. James is passionate about using Decision Management Systems to help companies improve decision making and develop an agile, analytic and adaptive business. He provides strategic consulting to companies of all sizes, working with clients in all sectors to adopt decision making technology. James has spent the last 20 years developing approaches, tools, and platforms that others can use to build more effective information systems. He has led Decision Management efforts for leading companies in insurance, banking, health management, manufacturing, travel and telecommunications. In addition to strategy and implementation consulting, James delivers webinars, workshops and training. He is also a regular keynote speaker at conferences around the world.

James is the author of “Decision Management Systems: A practical guide to using business rules and predictive analytics” (IBM Press, 2011). He previously wrote Smart (Enough) Systems: How to Deliver Competitive Advantage by Automating Hidden Decisions (Prentice Hall) with Neil Raden, and has contributed chapters on Decision
Management to multiple books as well as many articles to magazines. He also authors the definitive Decision Management Systems Platform Technologies Report, now in its third release.

The Decision Management Journey

Decision Management is both an approach and a technology stack.

In this opening day workshop, Decision Management consultant and author James Taylor will introduce both.

We'll begin with the discovery and modeling of suitable decisions, move into the construction of decision services and wrap up with the importance of decision analysis for continuous improvement. The critical technology capabilities - managing decision logic, embedding analytics, monitoring decision performance, and optimizing results - will all be introduced and presented in a coherent architecture for building Decision Management Systems.

Different adoption paths and some best practices will conclude the session, putting you on a path to Decision Management success.

Talk on Power Monday at 3pm in the Getting Started track


Kenny Shi
PayPal - Senior Manager of Decision Engine Platform

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Kenny has been building business rules platforms to serve fraud, risk and compliance use cases in the past decade. He has successfully led both technology and business rules analyst teams to have established end-to-end decision management solutions in
large scale. Kenny is passionate about enabling business to be in control and to be agile.

Kenny currently works on Decision Engine Platform at PayPal. Prior to PayPal, Kenny had spent over 9 years at eBay, responsible for “Elvis”, the eBay rules solution. During his tenure at eBay, he had built a home-grown Business Rules Management System, codenamed “eRules”, and had successfully evangelized business rules methodology and helped deploy rules solutions for various products in the company. At eBay, Kenny had also worked on predictive analytics platform, numerous fraud detection capabilities, Complex Event Processing, and behavior profiling using Big Data.

To B(uild) or Not To B(uild)

Engineers like to build. Should we build a Business Rules Management System from scratch? What do you get from a vendor solution? What are the pain points at getting started on a vendor BRMS? What are the longer term needs adopting a vendor BRMS? What are the advantages of a home-grown BRMS? What are the biggest challenges building one in-house?

Having been there and done that, Kenny would like to share with audience the learning from building a BRMS, pros and cons from both sides. This talk will set the right expectations for those teams who want to build, and probably will give hints to vendors what capabilities are asked for by customers.

Talk on Tuesday


Diego Naya
Plugtree - Founder

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Diego is founder of Plugtree, specialized in consultancy, support and training for Drools, jBPM and related technologies He has several years of experience in BPMS and BRMS implementations in different industries. Diego wrote the book “OSWorkflow: A guide for implementing Business Processes” and several related articles. He is actively involved in the Drools / BRMS community as a community contributor.

Complex Event Processing at the largest healthcare company in Argentina

The healthcare company has the largest coverage in Argentina, with over one and a half million affiliates. It is also the leader in healthcare technology usage of the region.

Over the last couple of years they have implemented a complex
event processing system that takes advantage of all the cross references of different types of events. Along that time, they’ve compiled a series of best practices, design patterns and overall experience of its impact over operational aspects of the company. It is of their most interest to share this experience with other companies.

This talk explains how to integrate a CEP server with enterprise level middleware, such as ESBs, legacy applications, different communication protocols such as SOAP, REST and JMS, and being able to process all events in a way that makes sense in a global way from the standing point of the company. This integration goes on to cover integrating outgoing events from the CEP server to the rest of the application world.

We will cover as many best practices as possible, from defining and upgrading the event definitions to its transformations, from the data gathering to the information generation, and from coding to business ROI.

Talk on Wednesday in the Healthcare track


Mark Proctor
Red Hat, Inc.

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Writing Classic Computer Games using Rule Based Programming

Writing classic computer games is a fun and challenging way to learn rule based programming.

This talk will develop games live, while explaining the mechanics of those things work. Starting with number guess and text adventures and eventually working up to Pong.

Talk on Tuesday

Decision Management Champion

Talk on Monday


Mike Weiss
NASDAQ OMX - Senior Software Developer 

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Mike joined NASDAQ OMX in 2011 where he has been working in the back office technologies division for over 2 years. His primary focus has been on billing related projects.  After joining NASDAQ OMX, Mike began the process of introducing BRMS to the company and continues this effort today.

Prior to joining NASDAQ OMX, Mike worked for Red Hat as a Middleware consulting for over 3 years. While at Red Hat Mike led and participated in several projects utilizing various open source technologies, including BRMS. In addition to implementing BRMS solutions for several clients, Mike was also part of a group of Red Hat employees who helped create an updated JBoss BRMS training
course.  

John X. Dinh
NASDAQ OMX -

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John joined NASDAQ OMX in 2011 where he has focused his efforts on measuring the performance of NASDAQ OMX’s U.S. derivatives business. He also provides the management team with insight on industry trends and customer behavior. He is also responsible for formulating price incentive structures across NASDAQ’s three U.S. Derivatives exchanges. 

Prior to joining NASDAQ, John was an Analyst at Freeman & Co., an M&A advisory and strategic management consulting firm based in New York City. During John’s tenure at Freeman & Co., he worked on an array of projects including benchmarking the competitive positions for firms in the Investment Banking and Private Equity industry.  Through a joint venture between Freeman & Co. and Thomson Reuters, John helped shape what is now known as Deals Business Intelligence, a tool utilizing Freeman & Co.’s proprietary fee based algorithm to help investment banks analyze, manage and grow their businesses. John graduated from The Smeal College of Business at The Pennsylvania State University with a B.S. in Economics.


The competitive edge in the ever-changing world of stock exchanges

The stock exchange space is an ever evolving world and to stay competitive one needs to have the ability to adapt quickly.  Outside of the speed of an exchange’s trading platform, the next most important thing to attract business is a competitive pricing schema. 
Firms will often determine where they are  going to trade based on where they will get the best pricing. Because of this  fact the business needs the ability to change rapidly to stay  competitive. 

This talk will cover why  Drools gives us an edge in this pricing war and how we are using it day to  day. The talk will be broken into a couple major sections:
• Why a rules engine?
• Where we were before using business rules
• Where we are currently at 
    o Lessons learned to–date
• Where we are doing with business rules

Talk on Wednesday in the Financial Services track


Neil Raden
Hired Brains Research - Founder and Principal Analyst

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Neil is the founder and Principal Analyst at Hired Brains Research, a
provider of consulting and implementation services in business intelligence, analytics and decision management. Hired Brains focuses on the needs of organizations and capabilities of technology.

He began his career as property and casualty actuary with AIG in New York before moving into predictive analytics services, software engineering, and systems integration with experience in delivering environments for decision making in fields as diverse as health care to nuclear waste management to cosmetics marketing and many others in between.

Neil is the co-author of the book, Smart (Enough) Systems: How to Deliver Competitive Advantage by Automating Hidden Decisions, 2007, Ptentice-Hall.  He is also the author of two forthcoming books on Data Science and Decision-Making. In 1995, Neil’s first in a series of feature articles appeared in InformationWeek, followed by dozens of others in magazines and journals. In 1998, he formed Hired Brains Magazine, a high-end monthly for professional consultants. Neil’s blog appears at hiredbrains.wordpress.com. He is a regular contributor to expert sites such as LinkedIn Groups, Focus, Quora and eBizQ, as well as contributed articles to Forbes Magazine in 2012 and 2013 on Big Data. Neil was also an early Wikipedia editor and administrator in areas of technology, health care and mathematics.

Included in Top 50 of Jonny Bentwood’s Technobabble 2.0 Top Industry Analyst Tweeters.

Recently, Neil was recognized as #34 of the top 100 most influential
people in Big Data

Keynote - Any Company can Compete on Analytics

Analytics is a broad subject area, but analytics in decision management has traditionally been a slow, artisanal process to create artifacts useful to rules engines at runtime. Those artifacts were created using techniques of data mining, predictive analysis and sometimes, optimization algorithms. But with the emergence of massively distributed processing grids, unstructured data and Hadoop, analytics has become something new - data science.

In this talk we'll discuss what the nature of data science and data scientists is, and apply some perspective on how it should and ultimately will affect your decision processes, both manual and automated.

Great strides have been made informing decisions with analytical processes. However, the challenge of analytics is communication and creating a shared understanding. It’s about focusing on high impact areas, moving forward one step at a time, being skeptical, being creative, searching for the truth.

Any company can compete on analytics.

Talk on Monday

CTO Panel

Neil will moderate the CTO Panel:
  • Jacob Feldman, CTO Open Rules
  • Mark Proctor, Red Hat Platform Architect
  • Gil Segal, Sapiens
  • Carlos Serrano-Morales, CTO Sparkling Logic

Talk on Tuesday at 9:30am


Ravi Singh
Knowledge Partners   International - Vice President, Strategy and Projects

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Ravi is a Vice President, Strategy and Projects, at Knowledge Partners   International, where he is responsible for defining company strategy and overseeing company’s projects and engagements. 
 
Prior to coming to KPI, Ravi was Business Rules Director at Freddie Mac, Where he was responsible for creating a Business Rules infrastructure using iLog, building Decision Architecture to adopt the MISMO Loan Delivery Spec and leading the effort to create and build the first Business Decision Management System (Sapiens Decision) with KPI and Sapiens. Ravi led several decision modeling engagements throughout Freddie Mac including rollout, training and adoption of Business Decision Management System. He also successfully established Center of Excellence for Decision Models in Freddie Mac to ensure consistent application of Decision Model principles, methodology and tool throughout Freddie Mac. 
 
Ravi has over 17 years’ experience in the software industry and has over 10 years’ experience in Mortgage Finance. He is a thought leader in Decision, Process and Business Rules space and has presented at several conferences including MISMO Business Rules Group, Business Process Management Institute, and was a panelist at Business Rules Forum. 

Ravi completed Leadership and Strategy Execution Program from Tuck School of Business at Dartmouth. He has a Bachelor in Engineering from Nagpur University in India.

Using TDM to simplify Business Rules Management

One of our industry’s biggest contention was the way business
requirements were captured and communicated between Business and IT.

The Decision Model (TDM) was introduced by Barbara von Halle and Larry Goldberg in 2009 when they published their book The Decision Model - A Framework Linking Business and IT (Taylor&Francis, 2009). TDM is a new way to capture, organize, manage, test and author business logic unambiguously. TDM eliminated the guesswork for IT interpreting natural language statements submitted by the Business.

This presentation will provide an overview of TDM and explain its profound impact on Business and IT.

Talk on Tuesday



Shash Hegde
Mariner

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Shash is a BI & Analytics professional and a thought leader with over
10 years of technology and business consulting experience. 

At Mariner he helps customers formulate BI strategies, select technologies,
craft solutions and also execute on their vision.

Shash works with Microsoft as
a Virtual Technology Specialist and has a Bachelors in Computer Science from Mangalore University and a Masters in Information Technology from the University of North Carolina.

Follow him @DataCzar

Is this Skynet? Giving machines a collective memory & intelligence

The term "internet of things", loosely defined as a world where physical objects are seamlessly integrated into the information network, and where the physical objects can become active participants in business processes has gained popularity in recent years. 

The talk will describe the case study of a small but visionary power management company in the Carolinas, which is building the next generation of a smart enterprise. An enterprise modeled on an event driven architecture which can sense and respond to stimuli faster than the competition. 
 
Achieving the vision has required our team to use a combination of data warehousing, decision management and analytics. Come learn
about the vision, the challenges and also the business drivers for  making this ambitious project a reality.

Talk on Tuesday


Srinivas Krovvidy
Fannie Mae

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Srinivas is a Technology Director at Fannie Mae where he has been involved in leading design, development and implementation efforts of knowledge-based systems and content management tools. He has been associated with knowledge-based systems and business rules applications development for more than 20 years.

He currently leads the Business Rules Management Center of Excellence at Fannie Mae and is responsible for developing standards, best practices for designing and deploying enterprise business rules applications. His interests include knowledge acquisitions, machine learning and business rules representation.

He received his BE from Osmania University, MTech from Indian Institute of Technology and a PhD in computer science and engineering from the University of Cincinnati. He is a member of ACM and AAAI.

Enterprise Business Rules Management: From Vision to Implementation

Fannie Mae has a long history of successfully deployed business rules applications since mid 1990s including launching of Desktop Underwriter(DU®), Custom Desktop Underwriter (Custom DU®),
Knowledge Acquisition and Rule Management Assistant (KARMA). However, the scope of these applications had been siloed and limited  to specific business domains and the experiences and lessons learned from these applications did not translate into an enterprise vision until 2010. 

This presentation focuses on how an enterprise business rules management strategy was conceived in 2010 and various stages of its implementation during last three years resulting in the deployment of an enterprise business  rules management system in 2011 and a centralized shared business rules  service in 2012. It also highlights the ongoing activities including standing  up a centralized rules governance process and adoption of various business applications that are planning to leverage the shared platform and business rules.

The enterprise business rules platform enabled us to develop a streamlined  license management process. We are also able to implement common business  rules analysis, design and development best practices and templates across  the organization. We are able to leverage skills and resources across  multiple applications. We identified opportunities to share rules across  applications resulting in consistent and cost effective policy automation.

Talk on Wednesday in the Financial Services track

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