Contributing Authors
Edmon Begoli (“Storage and Read-Optimized Data Placement Structures for High Performance Analysis”) is the chief data architect and a senior scientist with Oak Ridge National Laboratory (ORNL). At ORNL, he is responsible for research, design and development of novel and state-of-the-art data-centric solutions in support of science community, and mission requirements of the U.S. federal agencies. His research interests are in high-performance architectures for data analysis, and specifically in probabilistic and synopsis data structures. He holds undergraduate, graduate and doctoral degrees in computer science.
Hamparsum Bozdogan (“Novel Dimension Reduction Techniques for High Dimensional Data Using Information Complexity”) is the Toby McKenzie Professor in Information Complexity and in Model Selection in the Department of Business Analytics and Statistics; founding member of the Center for Intelligent Systems and Machine Learning (CISML); and a faculty affiliate at the Department of Mathematics and the Institute of Biomedical Engineering at the University of Tennessee, in Knoxville. He is the Editor and Editorial Board Member of several prestigious international journals. He is the recipient of numerous prestigious awards. He is an internationally recognized renowned expert in the area of information complexity and information-theoretic statistical modeling and model selection.
Agostino Capponi (“Systemic Risk, Policies, and Data Needs”) received his Ph.D. in computer science and applied and computational mathematics from the California Institute of Technology. He joined Columbia University’s IEOR Department in August 2014, where he is also a member of the Institute for Data Science and Engineering. His main research interests are in the area of networks, with a special focus on systemic risk, counterparty risk, central clearing, and control. In the context of financial networks, the outcome of his research contributes to a better understanding of risk management practices, and to assess the impact of regulatory policies aimed at controlling financial markets. He has been awarded a prize from the MIT Center for Finance and Policy for the SIFI challenge, and the Bar Ilan prize for research in financial mathematics. His research has been published in top-tier journals including Operations Research, Mathematics of Operations Research, Management Science, Review of Asset Pricing Studies, and Mathematical Finance. His work has also been published in leading practitioner journals and invited book chapters. He is a frequently invited speaker at major conferences in the area of systemic risk. He holds a world patent for a target tracking methodology in military networks.
J. Blair Christian (“Storage and Read-Optimized Data Placement Structures for High Performance Analysis”) has a Ph.D. in statistics from Rice University and is a data scientist at PYA Analytics. Previously he was a Senior Research Statistician Developer at the SAS Institute. He has experience in high performance computing, multivariate statistics and visualization. He has worked on both product development and consulting in healthcare over the last two years. He has built predictive models for readmissions, adverse health outcomes and has incorporated large amounts of non-clinical data in these models.
Ananda Swarup Das (“Mining Qualitative Attributes to Assess Corporate Performance”) received his B.Tech in computer science and engineering from National Instititue of Technology Jalandhar, Punjab, India. He pursued hisMaster and Ph.D. from the International Institute of Information Technology, Hyderabad, India. At IIIT Hyderabad, Ananda designed space efficient data structures for efficient range query retrievals. He joined IBM India Research Lab, New Delhi in November 2012. Currently, he is working as a technical staff member in the Knowledge Engineering and Encrypted Analytics unit in IBM India Research Lab. His topic of interest are computational geometry, range queries, succint data structures, text mining, information retrieval and applications of machine learning.
Sanmay Das (“Multiagent Systems Modeling”) Sanmay Das is an associate professor of computer science and engineering at Washington University in St. Louis. He received an A.B. in computer science from Harvard College and S.M. and Ph.D. from the Massachusetts Institute of Technology. His research is at the intersection of machine learning, multiagent systems, and computational social science.
Garrett M. Dranichak (“Robust Multiobjective Optimization for Decision Making under Uncertainty and Conflict”) is a Ph.D. candidate in the Department of Mathematical Sciences at Clemson University with a concentration in operations research. He received a B.S. in mathematics (2012) from Pfeiffer University, and an M.S. in mathematical sciences (2014) from Clemson University. In 2015, he earned the Excellence in Graduate Teaching award from the Department of Mathematical Sciences at Clemson. His research interests include robust optimization and multiobjective programming. He is a member of INFORMS and the vice president of the Clemson student chapter of SIAM.
Eugene A. Feinberg (“Optimality Conditions for Inventory Control”) is Distinguished Professor in the Department of Applied Mathematics and Statistics at Stony Brook University. His research interests include stochastic models of operations research, Markov decision processes, and industrial applications of operations research and statistics. He has published more than 150 papers and edited the Handbook on Markov Decision Processes. He is a member of several editorial boards including Mathematics of Operations Research, Operations Research Letters, and Applied Mathematics Letters. Dr. Feinberg is a Fellow of INFORMS. He is a recipient of 2012 IEEE Charles Hirsh Award and 2012 IBM Faculty Award.
Aparna Gupta (“Mining Qualitative Attributes to Assess Corporate Performance”) is an associate professor of Quantitative Finance at the Lally School of Management at Rensselaer Polytechnic Institute (RPI). She is the academic director of the M.S. program in quantitative finance and risk analytics at the Lally School. She holds a joint appointment in the Department of Industrial and Systems Engineering at RPI. Dr. Gupta has developed and taught courses on corporate finance, financial computations, derivatives, risk management, financial econometrics, and financial simulation at RPI and in programs in India, Sri Lanka, Singapore, and China. She is the author of the book, Risk Management and Simulation. Dr. Gupta’s research interests are in risk management, financial engineering, and financial decision support. She has addressed a range of issues in risk management at the individual and the institutional level, along with financial network considerations. She conducts U.S. National Science Foundation funded research in financial innovation for risk management in network domains, such as electricity markets, communication network. Her research has been published in reputed journals, such as, Journal of Banking and Finance, Insurance: Mathematics and Economics, Physica A, European Journal of Operational Research, Journal of Financial Engineering, Journal of Financial Stability, Annals of Operations Research, Computational Optimization and Applications, Journal of Computational Finance, Computer Networks, Electricity Journal, etc. Dr. Gupta serves on the editorial board and as a reviewer for several business, finance and management science journals, and is the past Chair of the Financial Services Section of INFORMS. She has also served on the INFORMS Subdivisions Council. Dr. Gupta earned her doctorate from Stanford University.
Nicholas Hall (“Research and Teaching Opportunities in Project Management”) is Fisher College of Business Distinguished Professor at The Ohio State University. His research and teaching interests include project management, scheduling, and pricing, He published over 80 articles in Operations Research, Management Science, Mathematics of Operations Research, Mathematical Programming, Games and Economic Behavior, and other journals. His 330 presentations include 98 invited presentations in 23 countries, 11 conference keynote presentations, and eight INFORMS conference tutorials. He served as President of Manufacturing and Service Operations Management (1999–2000), Treasurer of INFORMS (2011-2014), and on the State of Ohio Steel Industry Advisory Council (1997–2002).
Mohammad Hasan (“Methods and Applications of Network Sampling”) is an associate professor of computer science at Indiana University–Purdue University, Indianapolis (IUPUI). He was an assistant professor at IUPUI from 2010-2015 and was a senior research scientist at eBay Research Labs, San Jose, CA from 2009-2010. He received his Ph.D. in computer science from Rensselaer Polytechnic Institute (RPI) in 2009, M.S. in computer science from the University of Minnesota, Twin Cities, in 2002. His research interest focuses on developing novel algorithms in data mining, network analysis, information retrieval, machine learning, and bioinformatics. He won PAKDD best paper award in 2009, ACM SIGKDD doctoral dissertation award in 2010, NSF CAREER award in 2012, and IUPUI Junior Faculty Research Award in 2013.
Alan King (“Recent Development in Multistage Stochastic Programming”) is a research staff member in the Mathematical Sciences Department at IBM’s Thomas J Watson Research Center. His research interests focus on stochastic programming modeling and solution technologies. He and co-author Stein Wallace have recently produced a book entitled Modeling with Stochastic Programming, a graduate/under-graduate text focused on learning and applying basic concepts in stochastic programming. He is also the project manager for the stochastic programming project Stochastic Modeling Interface in the open source COIN-OR collection.
Joris van de Klundert (“Healthcare Analytics: Big Data, Little Evidence”) holds an M.Sc. in management informatics from Erasmus University Rotterdam (EUR) and a Ph.D. in operations research from Maastricht University. He is a founder of university spin off company Mateum, and a former president of the Dutch OR Society. He currently chairs the department of Health Services Management & Organisation of the Institute of Health Policy & Management of EUR, where he has also acted as vice-dean of education. His present research interest focuses on the optimization of health service networks. Recent work includes chairing the EU COST action on collaboration in kidney exchange programs, and projects for the World Bank and the WHO.
Esra Pamukçu (“Novel Dimension Reduction Techniques for High Dimensional Data Using Information Complexity”) is an assistant professor in the Department of Statistics at Firat University in Elazig, Turkey. She graduated from Fırat University with High Honors with a B.Sc. degree in mathematics. She obtained her M.Sc. and Ph.D. in applied statistics from the Institute of Natural and Applied Sciences, Fırat University. She was a Visiting Doctoral Scholar at the University of Tennessee in Knoxville during April-June 2013. She completed her Ph.D. under the supervision of Professor Bozdogan in March, 2015. Dr. Pamukcu has published various research papers and professional articles in several prestigious scientific journals.
Pragneshkumar Patel (“Storage and Read-Optimized Data Placement Structures for High Performance Analysis”) holds an M.S. in computer science. He works as a computational scientist at the Joint Institute for Computational Sciences, Oak Ridge National Laboratory. He has experience in scientific computing, high performance computing, large scale data analysis and visualization domains. He provides an advance support for parallelizing, optimizing, and implementation of scientific codes to scientific communities on different kinds of supercomputing resources. He is a developer and founding member of “programming with big data in R” project, which enables high-level distributed data parallelism in R.
Joe Pimbley (“Mathematical Finance, Models, Simulation and Today’s Pressing Problem”) is principal of Maxwell Consulting, a firm he founded in 2010. He is expert in complex financial instruments, financial risk management (certified as FRM by the Global Association of Risk Professionals), valuation, structured products, derivatives, and quantitative algorithms. He holds a Ph.D. in theoretical physics and is a co-author of Banking on Failure (2014), Simple Money (2013), and Advanced CMOS Process Technology (1989). Dr. Pimbley serves on several corporate and academic boards and has written more than 40 finance articles and nearly 100 physics, engineering, and mathematics articles. He has presented more than 60 finance seminars and holds numerous patents for engineering inventions.
Warren B. Powell (“A Unified Framework for Optimization under Uncertainty”) is a professor in the department of operations research and financial engineering at Princeton University, where he has taught since 1981. He is the founder and director of the laboratory for computational stochastic optimization and learning (CASTLE Labs), which spans contributions to models and algorithms in stochastic optimization, with applications in energy, transportation, health and finance. He has written two books and 200 publications, and is an INFORMS Fellow.
Gagandeep Singh (“Mining Qualitative Attributes to Assess Corporate Performance”) received his B.Tech in computer science and engineering from the National Instititue of Technology Jalandhar, Punjab, India and Master from Indian Institute of Science, Bangalore, India. He joined IBM India Research Lab, Bangalore in August 2014. He is currently working as a software engineer in the Knowledge Engineering and Encrypted Analytics unit in IBM India Research Lab. Prior to joining IBM, Gagandeep has also worked for Erricson as a Solution Integrator.
L. Venkata Subramaniam (“Mining Qualitative Attributes to Assess Corporate Performance”) is a senior technical staff member and a senior manager for the Knowledge Engineering and Data Platforms team. He pursued his B. Tech from PES College of Engineering, Mandya, India, Master from Washington University, St. Louis and Ph.D. from Indian Institute of Technology, New Delhi, India. He joined IBM India Research Lab, New Delhi in June 1998. He has been awarded with IBM Outstanding Technical Achievement Awards in 2011, 2012 and twice in 2015. He has a number of publications in international conferences and prestigious journals. He is also involved with academic activities in Indian Institute of Technology, New Delhi and is on the senate of IIIT Delhi.
Glen Swindle (“Assets and Structured Hedges in Energy Markets”) has held senior positions at Constellation Energy, where he ran the Strategies Group for the merchant energy business, and at Credit Suisse, where, as Managing Director and Co-Head of Power and Natural Gas Trading, he ran structured trading teams responsible for significant aspects of the North American energy business. Previously he held tenured positions at UCSB and Cornell University. He currently holds an adjunct faculty position at New York University where he lectures on energy valuation and portfolio management. He is also on the Energy Oversight Committee for GARP’s Energy Risk Professional Program and is a frequent speaker at panel discussions and webinars. He is the author of Valuation and Risk Management in Energy Markets (Cambridge University Press, 2014). He holds a Ph.D. in Applied Mathematics from Cornell University, an M.S.E in Mechanical Aerospace Engineering from Princeton, and a B.S. in Mechanical Engineering from Caltech.
Margaret M. Wiecek (“Robust Multiobjective Optimization for Decision Making under Uncertainty and Conflict”) is a professor of mathematical sciences at Clemson University. She has a Ph.D. in systems engineering from the AGH University of Science and Technology in Krakow, Poland. Her research area includes theory, methodology, and applications of mathematical programming with special interest in multiobjective optimization and decision-making. She has introduced new multiobjective optimization concepts and methods into engineering optimization to enrich the field of automotive and structural design. She is a member of the editorial board of the International Journal of Multicriteria Decision Making and serves as the president of the INFORMS Section on Multiple Criteria Decision Making.
William T. Ziemba (“Understanding the U.S. Index Futures Stock Market using Research”) is the Alumni Professor (Emeritus) of Financial Modeling and Stochastic Optimization in the Sauder School of Business, University of British Columbia where he taught from 1968-2006. His Ph.D. is from the University of California, Berkeley. He is the Distinguished Visiting Research Associate, Systemic Risk Centre, London School of Economics. He has been a consultant to a number of leading financial institutions His research is in asset-liability management, portfolio theory and practice, security market imperfections, Japanese and Asian financial markets, hedge fund strategies, risk management, sports and lottery investments and applied stochastic programming. His co-written practitioner paper on the Russell-Yasuda model won second prize in the 1993 Edelman Practice of Management Science Competition. He has been a futures and equity trader and hedge fund and investment manager since 1983. In 2015, he won the futures part of the Battle of the Quants in New York. He is series editor for North Holland’s and World Scientific’s Handbooks in Financial Economics and World Scientific’s books in finance. He has published widely in books and in journals such as Operations Research, Management Science, Mathematics of OR, Mathematical Programming, American Economic Review, Journal of Economic Perspectives, Journal of Finance, Journal of Economic Dynamics and Control, JFQA, Quantitative Finance, Journal of Portfolio Management, and Journal of Banking and Finance.
