Bio: Guruduth Banavar is vice president and chief science officer for cognitive computing at IBM. He is responsible for advancing the next generation of cognitive technologies and solutions with IBM’s global scientific ecosystem, including academia, government agencies and other partners. Most recently, he led the team responsible for creating new cognitive systems in the family of IBM Watson. These systems are designed to create new partnerships between people and machines to augment and scale human expertise in all industries. Previously, as chief technology officer for IBM’s Smarter Cities initiative, Banavar designed and implemented big data and analytics systems to help make cities, such as Rio de Janeiro and New York, more livable and sustainable. Prior to that, he was director of IBM Research in India, where he and his team received a presidential award for innovation. He holds more than 25 patents and has published extensively, with his work featured in media outlets around the world.
Title: Cognitive Computing: From breakthroughs in the lab to applications on the field
Abstract: In the last decade, the availability of massive amounts of new data, the development of new machine learning technologies, and the availability of scalable computing infrastructure, have given rise to a new class of computing systems. These “Cognitive Systems” learn from data, reason from models, and interact naturally with us, to perform complex tasks better than either humans or machines can do by themselves. These tasks range from answering questions conversationally to extracting knowledge for discovering insights to evaluating options for difficult decisions. These cognitive systems are designed to create new partnerships between people and machines to augment and scale human expertise in every industry, from healthcare to financial services to education. This talk will provide an overview of cognitive computing, the technology breakthroughs that are enabling this trend, and the practical applications of this technology that are transforming every industry.
Bio: Ramayya Krishnan is the W. W. Cooper and Ruth F. Cooper Professor of Management Science and Information Systems at the H. John Heinz III College and the Department of Engineering and Public Policy at Carnegie Mellon University. A faculty member at CMU since 1988, Krishnan was appointed Dean when the Heinz College was created in 2008. He was reappointed upon the completion of his first term as Dean in 2014.
Krishnan was educated at the Indian Institute of Technology and the University of Texas at Austin. He has a Bachelor’s degree in mechanical engineering, a Master’s degree in industrial engineering and operations research, and a PhD in Management Science and Information Systems. Krishnan’s research interests focus on consumer and social behavior in digitally instrumented environments. His work has addressed technical, policy and business problems that arise in these contexts and he has published extensively on these topics. He has served as Department Editor for Information Systems at Management Science, the premier journal of the Operations Research and Management Science Community. Krishnan is an INFORMS Fellow, a member of the Global Agenda Council on Data Driven Development of the World Economic Forum, and a former President of the INFORMS Information Systems Society and the INFORMS Computing Society. He is the recipient of the prestigious Y. Nayuduamma award in 2015 for his contributions to telecommunications management and business technology.
Title: Analytic + IT + Deployment = Real World Impact
Abstract: The Heinz College is home to two highly ranked graduate schools: 1) Information Systems and Management and 2) Public Policy and Management, a deliberate structure which exists only at Carnegie Mellon University (CMU). Founded by noted Management Scientist W. W. Cooper to educate “men and women capable of intelligent action”, the unique structure of the college gives its educational programs a holistic focus on societal problem solving. This focus translates into teaching cutting-edge information technologies and analytic methods and providing students with multiple opportunities to apply them to solve real world problems that matter. This focus also means an emphasis on structuring unstructured problems and an education in the skills required to be effective at that structuring and at decision making, and engendering change through deployment. In this keynote, I will provide an overview of our award winning analytics program and describe how we combine industry-funded research centers and their partner ecosystems to provide students with multiple opportunities to learn an array of analytic skills and problem-solving expertise in order to be effective in the real world.
Keynote: Jeff Nichols (ORNL), High Performance Computing
Dr. Nichols became the associate laboratory director for ORNL’s Computing and Computational Sciences in April 2009. In this position, he oversees the Department of Energy’s (DOE) National Center for Computational Sciences (NCCS), the site of the Oak Ridge Leadership Computing Facility (OLCF), which delivers state-of-the-art scientific research and technological innovations. The OLCF is home to Titan, the nation’s most powerful computing resource. He leads the laboratory’s agenda in advanced high-performance computing in priority areas such as climate change, fusion energy, nanotechnology, biotechnology, cyber security, and big data initiatives.
Prior to assuming his new position, Dr. Nichols was the deputy associate laboratory director of Computing and Computational Sciences, where he led efforts to build, install, and deploy next‑generation supercomputers for DOE, the National Science Foundation, and the Department of Defense. A theoretical chemist and software developer, Dr. Nichols joined Oak Ridge National Laboratory in 2002 as the director of the Computer Science and Mathematics Division, a position which he held until 2009. From 2005–2006, he was Acting Director of NCCS. Before coming to ORNL, he led the Environmental Molecular Sciences Laboratory at DOE’s Pacific Northwest National Laboratory, where high priority was given to the development, deployment, and use of scalable computational science community codes to solve grand-challenge problems crucial to the nation.
Dr. Nichols holds a B.A. in Chemistry and a B.A. in Mathematics from Malone College, in Canton, Ohio, and a Ph.D. in Physical Chemistry from Texas A&M University. He has more than 25 years of experience as a theoretical chemist and software developer, and he has held professorships at Malone College (Ohio), the University of Utah, and the Georgia Institute of Technology. He is author or co-author of four software applications, a co-author with J. Simons of “Quantum Mechanics in Chemistry, A textbook in quantum chemistry for the beginning graduate student” (1997), and of more than 60 research papers in chemistry and in mathematical and computational applications.
Title: Creating the Exascale Ecosystem for Science
Abstract: The way we tackle grand challenge science questions at the national scale has changed over the past two decades with the advent of both modeling and simulation (M&S) and “big data” becoming more recognized and supported discovery paradigms. In fact, most large scientific problems today are solved as integrated solutions of experiment, theory, M&S, and data analytics. The past several decades of high performance computing have focused on delivering compute intensive systems and their performance measured by how fast they can accomplish a simple matrix multiply (e.g., high performance linpack). Today’s complex workflows require not only compute intensive capabilities, but also capabilities that target data analytics approaches such as deep learning, graph analytics, or map reduce. In this talk I will describe several scientific areas that require an integrated approach and discuss the ecosystem [ORNL’s Leadership Computing Facility (OLCF) and its Compute and Data Environment for Science (CADES)] that we have created. We continue to invest in the evolution of this ecosystem to enable successful delivery of important scientific solutions across a broad range of disciplines.
Bio: Rolf H. Möhring obtained his M.S. (1973) and P.h.D (1975) in Mathematics at the RWTH Aachen and is since 1987 Professor for Applied Mathematics and Computer Science at Berlin University of Technology, where he heads the research group “Combinatorial Optimization and Graph Algorithms” (COGA). He has held earlier positions as associate and assistant professor at the University of Bonn, the University of Hildesheim, and the RWTH Aachen. His research interests center around graph algorithms, combinatorial optimization, scheduling, logistics, and industrial applications. Part of his research has been done in DFG Research Center Matheon, where he was Scientist in Charge of Application Area “Logistics, traffic, and telecommunication networks”. He has been chair of the German Operations Research Society and the Mathematical Programming Society and has been awarded the Scientific Award of the German Operations Research Society and the EURO Gold Medal of the European Association of Operational Research Societies. Since 2014 he is a honorary professor at the Beijing University of Technology and in the Board of the Beijing Institute for Scientific and Engineering Computing BISEC.
Title: Optimizing the Kiel Canal – Online Routing of Bidirectional Traffic
Abstract: We introduce, discuss, and solve a hard practical optimization problem that deals with routing bidirectional traffic on the Kiel Canal, which is the world’s busiest artificial waterway with more passages than the Panama and Suez Canal together. The problem arises from scarce resources (locations) at which large ships can only pass each other in opposing directions.
This is a prototype problem for traffic management and routing in logistic systems. One wants to utilize the available street or logistic network in such a way that the network “load” is minimized or the “throughput” is maximized. The aspects of “time” and “congestion” play a crucial role in these problems and require new techniques that need to integrate dynamic network flows and scheduling.
The lecture will illustrate recent developments in this direction on the example of the Kiel Canal problem, which was a project with the German Federal Waterways and Shipping Administration. Here certain ships must wait in sidings to let opposing traffic pass. This requires decisions on who should wait for whom (scheduling), in which siding to wait (packing) and when and how far to steer a ship between sidings (routing), and all this for online arriving ships at both sides of the canal.
The combination of routing and scheduling (without the packing) leads to a new class of scheduling problems dealing with scheduling bidirected traffic on a path, and we will also address recent complexity and approximation results for this class.
For the application, we need a feasible assignment of parking slots within sidings over time that is consistent with the scheduling decisions between the sidings and the routing. We have developed a combinatorial algorithm that provides a unified view of routing and scheduling that combines simultaneous (global) and sequential (local) solution approaches to allocate scarce network resources to a stream of online arriving vehicles in a collision-free manner.
Computational experiments on real traffic data with results obtained by human expert planners show that our combinatorial algorithm improves upon manual planning by 25%. It was subsequently used to identify bottlenecks in the canal and to make suggestions for enlarging the capacity of critical sections of the canal to make it suitable for future traffic demands.
Bio: Margaret L. Brandeau is Coleman F. Fung Professor of Engineering and Professor of Medicine (by Courtesy) at Stanford University. Her research focuses on the development of applied mathematical and economic models to support health policy decisions. Her recent work has examined HIV and drug abuse prevention and treatment programs, programs to control the spread of hepatitis B virus, and preparedness plans for bioterror response. She is a Fellow of INFORMS and a member of the Omega Rho Honor Society for Operations Research and Management Science. She has received the President’s Award from INFORMS, the Pierskalla Prize from INFORMS, the Award for the Advancement of Advancement of Women in Operations Research and Advancement of Women in Operations Research and the Management Sciences from INFORMS, the Award for Excellence in Application of Pharmacoeconomics and Health Outcomes Research from the International Society for Pharmacoeconomics and Outcomes Research (ISPOR), and a Presidential Young Investigator Award from the National Science Foundation, among other awards. Professor Brandeau earned a BS in Mathematics and an MS in Operations Research from MIT, and a PhD in Engineering-Economic Systems from Stanford.
Title: Public Health Preparedness: Answering (Largely Unanswerable) Questions with Operations Research
Abstract: Public health security – achieved by effectively preventing, detecting, and responding to events that affect public health such as bioterrorism, disasters, and naturally occurring disease outbreaks – is a key aspect of national security. However, effective public health preparedness depends on answering largely unanswerable questions. For example: What is the chance of a bioterror attack in the United States in the next five years? What is the chance of an anthrax attack? What might be the location and magnitude of such an attack? This talk describes how OR-based analyses can provide insight into complex public health preparedness planning problems – and thus support good decisions.
Abstract: After a brief introduction to Omega Rho, International Honor Society for Operations Research and Management Science, as it celebrates its 40th birthday, four of its distinguished lecturers will revisit their lectures. All four were in the first group of INFORMS Fellows, created in 2002. Al Blumstein, J. Erik Jonsson University Professor of Urban Systems & Operations Research, Carnegie Mellon University, spoke about “OR/MS for the Public Sector: The New Frontier Under the Next President” in 1988, just before George H. W. Bush became President. What is the position today, in the closing days of the Obama presidency? In 1995, Ralph Keeney, Professor Emeritus at Duke University and University of Southern California, spoke on “Evaluating Life and Death Decisions”. What developments have taken place in the intervening three decades? “The World is Coming Our Way: OR/MS Opportunities in e-Commerce” was the subject of the lecture in 2000 by John Little, Professor of Operations Research & Management Science, Massachusetts Institute of Technology. Are there new opportunities for us 16 years on? In 2010, the fourth lecturer, John R. Birge, Jerry W. and Carol Lee Levin Professor of Operations Management, Booth School of Business, University of Chicago, addressed “ORMS and Risk Management Failures: What are We Doing Wrong?”. Are there any signs that we are now doing things right?
Alfred Blumstein, University Professor at Carnegie Mellon University, has had extensive experience in both research and policy with the criminal justice system since serving the President’s Commission on Law Enforcement and Administration of Justice in 1966-67 as Director of its Task Force on Science and Technology. His research over the past fifty years has covered many aspects of criminal-justice phenomena and policy, including crime measurement, criminal careers, sentencing, deterrence and incapacitation, prison population, demographic trends, juvenile violence, and drug policy. He was a member of the National Academy of Sciences Committee on Research on Law Enforcement and the Administration of Justice from its founding in 1975 until 1986 and a member of the Academy’s Commission on Behavioral and Social Sciences and Education from 1994-2000. He served from 1979 to 1990 as Chairman of the Pennsylvania Commission on Crime and Delinquency, the state’s criminal justice planning agency. He was appointed by US Attorney General Eric Holder as chair of the Science Advisory Board for the DoJ’s Office of Justice Programs and served from 2010-2014. Dr. Blumstein is a Fellow of the American Society of Criminology, was the 1987 recipient of the Society’s Sutherland Award for “contributions to research,” and was the president of the Society in 1991-92. In 1998 he received the Wolfgang Award for Distinguished Achievement in Criminology and in 2007 the Stockholm Prize in Criminology. He was President of ORSA in 1977-78, awarded its Kimball Medal in 1985, and its President’s Award in 1993. He was president of TIMS in 1987-88 and President of INFORMS in 1996. His degrees from Cornell University include a Bachelor of Engineering Physics and a Ph.D. in Operations Research and he has an honorary degree of Doctor of Laws from the John Jay College of Criminal Justice of the City University of New York.
Ralph L. Keeney, Research Professor Emeritus of Business Administration, Duke University, and Professor Emeritus of Industrial and Systems Engineering, University of Southern California, is an authority on decision analysis, decision making with multiple objectives, and value-focused thinking. His research interests include value models involving multiple objectives, risk analysis involving life-threatening risks, structuring decisions, and creating innovative alternatives. During his professional career, he has consulted on a wide range of decisions including corporate management problems, public policy, risk analyses, and energy decisions. His books, which have been translated into numerous languages, include Decisions with Multiple Objectives with Howard Raiffa (1976, 1993), Value-Focused Thinking: A Path to Creative Decisionmaking (1992), and Smart Choices: A Practical Guide to Making Better Decisions, with John S. Hammond and Howard Raiffa (1999). He recently received an honorary doctorate from the University of Waterloo in Canada and is a member of the National Academy of Engineering of the U.S. He received his Ph.D. from the Massachusetts Institute of Technology.
John Little has had a distinguished career spanning five decades. He has published seminal papers in operations research methodology, traffic signal control, decision support systems, and especially marketing. In operations research he is best known for his proof of the queuing formula L = λW, commonly known as Little’s Law. A pioneer in marketing science, he has done research on a broad set of modeling and decision support issues, including models of individual choice behavior, adaptive control of promotional spending, and marketing mix models for consumer packaged goods. He is co-editor with Blattberg and Glazer of The Marketing Information Revolution, HBS Press (1994). When the Internet burst on the scene, he was quickly attracted to e-commerce and co-taught the first course on the subject at MIT Sloan. A paper by John: “Models and Managers: the Concept of a Decision Calculus” was voted by the Management Science editorial board as one of the 10 most influential papers to appear in that journal in its first 50 years. Among John’s honors, he has been elected to the National Academy of Engineering and has received the Parlin and Converse Awards of the American Marketing Association, as well as the Kimball Medal of INFORMS. He has been President of ORSA (1979-80), TIMS (1984-85) and the first President of INFORMS (1995). He is a Fellow of the American Association for the Advancement of Science. He was awarded the first Ph.D in OR, by MIT in 1955.
John R. Birge, of the University of Chicago Booth School of Business, was previously Dean of the McCormick School of Engineering and Applied Science and Professor of Industrial Engineering and Management Sciences at Northwestern University. He also served as Professor and Chair of Industrial and Operations Engineering at the University of Michigan and established the University of Michigan Financial Engineering Program. He is former Editor-in-Chief of Mathematical Programming, Series B and former President of INFORMS. He has received many honors and awards including the IIE Medallion Award, the MSOM Society Distinguished Fellow Award, the Harold W. Kuhn Prize, the George E. Kimball Medal, the William Pierskalla Award, and election to the US National Academy of Engineering. He received M.S. and Ph.D. degrees from Stanford University in Operations Research, and an A.B. in Mathematics from Princeton University.
Bio: Suvrajeet Sen is Professor at the Daniel J. Epstein Department of Industrial and Systems Engineering at the University of Southern California. Prior to joining USC, he was a Professor at Ohio State University (2006-2012), and University of Arizona (1982-2006). He has also served as the Program Director of OR as well as Service Enterprise Systems at the National Science Foundation. In the past few years he has led a group of world-renowned OR visionaries to identifying new themes of OR for problems motivated by Grand Challenges of the National Academy of Engineering. Professor Sen’s research is devoted to many categories of optimization models, and he has published over a hundred papers, with the vast majority of them dealing with models, algorithms and applications of Stochastic Programming problems. He has served on several editorial boards, including Operations Research as Area Editor for Optimization and as Associate Editor for INFORMS Journal on Computing, Journal of Telecommunications Systems, Mathematical Programming B, and Operations Research. He also serves as an Advisory Editor for several newer journals. Professor Sen was instrumental in founding the INFORMS Optimization Society in 1995, and is currently serving as its Chair (2015-16). Except for his years at NSF, he has received continuous extramural research funding from NSF and other basic research agencies, totaling over nine million dollars as PI over the past 25 years. In 2015, this research and his group’s contributions were recognized by the INFORMS Computing Society for seminal work on Stochastic Mixed-Integer Programming. Professor Sen is a Fellow of INFORMS.
Bio: Gareth M. James is the E. Morgan Stanley Chair in Business Administration and Professor of Data Sciences and Operations in the Marshall School of Business at the University of Southern California. He has been on the faculty since 1998 and is currently serving as Vice Dean for Faculty and Academic Affairs for the Marshall school. Dr. James has authored over thirty five journal articles, books, discussion articles, conference proceedings and book chapters. In particular he has published extensively in the areas of functional data analysis and high dimensional statistics. Dr. James has also served as the PI or Co-PI on several NSF research grants and as an Associate Editor for JASA Theory and Methods, JASA Case Studies and Applications, and Statistica Sinca. He is an elected Fellow of the American Statistical Association and a life member of the Institute of Mathematical Statistics. Dr. James has won several research and teaching awards, including two USC Dean’s Awards for Research Excellence (2005, 1011), two Golden Apple Awards (2006, 2007), the Evan C. Thompson Faculty Teaching and Learning Innovation Award (2006), and the USC Mellon Mentoring Award (2013). Dr. James received his Ph.D. in Statistics from Stanford University in 1998 after receiving a Fulbright Scholarship in 1994. He holds BSc and BCom degrees from the University of Auckland, New Zealand.
Title: Big Data and Big Decisions
Abstract: Over the past decade, the world of Statistical and Machine Learning have made dramatic in-roads into some of the more challenging AI problems ranging from speech recognition and natural language processing, to bio and health informatics. Both supervised and unsupervised learning methods have exploded in daily use for applications covering business analytics, e-commerce, educational/tutoring systems, and others. In many cases, new models and algorithms have been developed so that the results of learning are also easier to interpret (for a human decision maker). The partnership between AI and human cognition is not new, but its widespread success in recent years has transformed the way we do business today. The combination of modern informatics and high dimensional statistics has often been credited with this transformation. This lecture will not only highlight some successes of Big Data, but also explore settings where human cognition may not provide the best test of decision quality. This new class of problems involves not only Big Data, but also Big Decisions. For instance, many states in the U.S. have committed to transforming the electricity grid to one where a large fraction of electricity will be produced by renewable resources. In California, the goal is to have 50% of electric power generated using renewable resources by 2030. As of now, it is unclear whether this is a feasible target without a great deal of over-generation. Of course, the latter goes against the goal of reducing emissions. Since these trade-offs involve many “moving parts” (multiple markets, technologies and constraints) the human brain is not the ideal computational device for separating good decisions from bad ones. Such cases arise in many other socio-technical systems, such as transportation, water resources, and others. This lecture will explore the continuum between Big Data and Big Decisions.
Daniel H. Wagner earned his PhD in mathematics from Brown University in 1951. He began his career in the US Navy’s Operations Evaluation Group (OEG) at the Pentagon, where he worked on operations research for naval warfare. In 1963, he created the firm of Daniel H. Wagner Associates, Inc., which is still in existence today. During his years as president and principal owner of Wagner Associates, Dan brought many high-quality mathematicians into the operations research community. This led to significant advances in the firm’s fields of endeavor and delivery of significant applications to the Navy, Coast Guard, and other clients; many of these applications are still in service today. After retirement from his eponymous company, Dan Wagner continued his commitment to the field of operations research, serving in various teaching and research positions with the U.S. Naval Postgraduate School and the U.S. Naval Academy. He was an active member of ORSA, and then INFORMS, for more than 40 years.
The Daniel H. Wagner Prize for Excellence in Operations Research Practice emphasizes the quality and coherence of the analysis used in practice. Dr. Wagner strove for strong mathematics applied to practical problems, supported by clear and intelligible writing. This prize recognizes those principles by emphasizing good writing, strong analytical content, and verifiable practice successes.
Bio: Jason joined Amazon in 1999 as a Software Development Engineer in Fulfillment Center (FC) Systems and moved to a Development Manager role in 2003. In 2007, he joined Fulfilled by Amazon (FBA). He took over Inventory Planning & Control (IPC) in 2009, and was promoted to Director in 2010. Under his leadership, the IPC team grew to over 300 employees worldwide. IPC is responsible for Economically Optimal Ordering, Sourcing Cost Optimization, Optimal Inventory Health, Vendor Returns, EDI, Inventory Flow Simulation and Inbound Performance Management.
In 2013, he was promoted to Vice President of Supply Chain Optimization Technologies (SCOT) were he led 700 global employees in the areas of Forecasting, Inventory Planning, Optimal Sourcing, FC Topology planning and Customer Promise. The platform is responsible for the automated buying, markdown, order assignment and placement of inventory in our fulfillment network. SCOT is also responsible determining customer delivery promise and planning the topology and capacity of our fulfillment network.
In 2016, he was appointed the Vice President of World-wide Retail Systems. Jason runs a world-wide organization consisting of approximately 6000 global employees. Retail Systems helps product lines grow profitably by providing automation and workflows for increasing selection, matching relevant competitors on value, and getting the best terms from vendors. The team also works with subsidiaries to deliver the services, integration support, and solutions design to migrate onto the Amazon platform. Retail Services provides the operational and creative resources behind product imaging, new item setup, competitive monitoring and various flex tasks.
Jason holds a Computer Science degree in Engineering from the University of Washington. He is an avid runner and practitioner of Brazilian jiu-jitsu. He lives in Bellevue, Washington with his wife and 3 children.
Title: Optimizing the Future – Supply Chain at Amazon
Abstract: The retail supply chain of the future will be built on massive data, advanced analytics and innovative technology. At Amazon, we are constantly pushing the frontier in each of these areas to help create that future. Our vision is to move products at an unprecedented scale through the most technologically advanced supply chain possible, where intelligent optimization algorithms drive efficiency. To achieve this vision, we focus on three core pillars: research, technology, and business ownership. We develop new research, implement it in technology, and own the top- and bottom-line of the business. To be successful, we believe business ownership, research, and development must be tightly coupled.
During this presentation, I will discuss our vision for the future of retail supply chain — where we have been, where we are, and where we plan to go. I will share some cases of research innovation and its integration with technology and business. These include inter-disciplinary modeling and optimization (from machine learning, statistics, simulation and optimization) to make Amazon’s supply chain more efficient. Finally, I will provide examples of some challenges we will need to overcome to make our vision a reality.
Title: UPS Optimizes Delivery Routes
Abstract: UPS, the leading logistics provider in the world, and long known for its penchant for efficiency, embarked on a journey to streamline and modernize its pickup and delivery operations in 2003. This journey resulted in a suite of systems, including an optimization system, which is called “On Road Integrated Optimization and Navigation” (ORION). Every day, ORION provides an optimized route for each of UPS’ 55,000 U.S. drivers based on the packages to be picked up and delivered on that day. The innovative system creates routes that maintain the desired level of consistency from day to day. To bring this transformational system from concept to reality, UPS instituted extensive change management practices to ensure buy-in from both users and executives. Costing more than $250 million to build and deploy, ORION is expected to save UPS $300 to $400 million annually. ORION is also contributing the sustainability efforts of UPS by reducing the CO2 emissions by 100,000 tons annually. By providing a foundation for a new generation of advanced planning systems, ORION is transforming the pickup and delivery operations at UPS.
Bio: Edmund Jackson is Vice President & Chief Data Scientist at HCA in Nashville, TN. Hospital Corporation of America (HCA) is the nation’s leading provider of healthcare services, a company comprised of locally managed facilities that includes about 165 hospitals and 115 freestanding surgery centers in 20 states and England and employing approximately 204,000 people. Approximately four to five percent of all inpatient care delivered in the country today is provided by HCA facilities. He leads a dynamic team of business intelligence (BI) specialists, software developers and data scientists. His core mission is to create clinical, operational and financial value from several data sources including our large clinical data warehouse and big data platform.
Title: Can Prediction be Better than Cure? On Analytics in Health-Care.
Abstract: Healthcare is different: the intrinsic complexity, absolute moral imperatives and regulatory oversight of this business are unique. As such many of the technologies in healthcare differ from other industries. That said, the industry is entering a new regime where data is widely available, technology exists for analytics to run in real-time and the intention of bringing this intelligence into the workflow is widespread. Moreover, the advent of techniques such as diagnostic, predictive, and prescriptive analytics in other industries have ready applications in healthcare. The potential benefits of these activities to all stakeholders in the healthcare system, such as patients, providers and payers are enormous. In this talk Dr Edmund Jackson, Vice President and Chief Data Scientist of HCA will discuss this topic and provide a perspective of what has already been achieved and what is soon to come.
Bio: Gerald G. Brown, Ph.D., is a Distinguished Professor of Operations Research and Executive Director of the Center for Infrastructure Defense at the Naval Postgraduate School, where he has taught and conducted research in optimization and optimization-based decision support since 1973, earning awards for both outstanding teaching and research. His military research has been applied by every uniformed service, in areas ranging from strategic nuclear targeting to capital planning. He has been awarded the Barchi, Rist, and Thomas prizes for military operations research, and been credited with guiding investments of more than a trillion dollars. He has designed and implemented decision support software used by the majority of the Fortune 50, in areas ranging from vehicle routing to supply chain optimization. His research appears in scores of open-literature publications and classified reports, some of which are seminal references. Brown is a member of the National Academy of Engineering, a recipient of the U.S. Navy Distinguished Civilian Service Medal, and an INFORMS Fellow.
Title: The Goals of Analysis are Understanding, Decisions, and Influencing Policy
Abstract: While we are variously skilled at applying a diverse set of mathematical tools to analysis, we all share (or should share) the same goals: understand the problem at hand; advise decisions influencing that problem; and influence policy for dealing with entire classes of problems resembling the one we analyze. Sometimes, our answers are not welcomed by a client who brings us a problem, and we face significant obstacles to conveying good, convincing advice and thus contributing to good decision policy. There are a number of techniques that apply to such situations and cross all our various analysis domains. Few of these appear in textbooks or our open literature. These turn out to be vitally important for success.
Keynote: Stephen Prather, SportSource Analytics
Bio: Stephen Prather is one of the co-founders of SportSource Analytics. Stephen is a native of Atlanta, GA and earned his undergraduate and MBA degree from Vanderbilt University. His experiences have taken him from Capitol Hill to commercial real estate brokerage to advanced data analytics. He lives in Nashville, TN with his wife and four girls.
Title: SportSource Analytics and the Pursuit of Usefulness
Abstract: Think back about 15 years ago about how difficult it was for anyone to access large amounts of data on virtually any subject. Now, think about how easy it is today for virtually anyone to access enormous amounts of data with the click of a few buttons. We live in an extremely data rich world. We are surrounded by information and data in all walks of life. The problem with all of this “big data” is that we are really struggling in finding ways to make it small and more importantly make it USEFUL.
My talk is going to be about how four guys all working full-time jobs and without a single advanced degree in any sort of statistical analysis between them were able to become the official analytic consultant to the college football playoff selection committee. This is a story of the pursuit of being useful and understanding that data is only as good as the analysis associated with it.