Hyun-soo Ahn

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Hyun-soo Ahn is an Associate Professor of Operations and Management Science at the Michigan Business School. He joined Michigan in 2003 from the department of Industrial Engineering and Operations Research at UC Berkeley. In his research, Hyun-soo develops and analyzes mathematical models related to supply chain management, dynamic pricing and revenue management, workforce agility, and resource allocation. He is also interested in modeling the customer’s behavior (such as subscription) and how it affects the firm’s profit. He has worked with more than 20 companies and his research has been funded by several organizations including National Science Foundation. His papers appear in leading journals in the field, including Operations Research, M&SOM, and Journal of Applied Probability.

At Ross, he teaches supply chain analytics and business statistics to MBAs, Exec. MBAs, MSCM, and BBAs. He has won a number of teaching awards voted by students, including 2012 Exec MBA teaching excellence award, 2012 Global MBA teaching excellence award, and 2006 BBA teaching excellence award.

Vahid Lotfi

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My current research interest is focused on improving efficiency and utilization of outpatient clinics, using data mining techniques such as decision tree analysis, Bayesian networks, neural networks, and similar techniques.  While our previous and continuing research have been focused on using some of these techniques to develop more sophisticated methods of patients scheduling within physical therapy clinics, we can see the applicability of the techniques to other types of health services providers.  There is also applicability to university administration in developing predictive models using data mining techniques for assessing student success.

Yi-Su Chen

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My current data science research interest lies in the broad area of supply chain and its management.   I am particularly interested in using longitudinal data set to identify early signals (or warning) and to draw causal inferences pertaining to supply chain security and product quality and safety.   I am also interested in developing experiments to capture the behavioral side of decision makings to be complementary to secondary data analysis.   Industry setting wise, I have based my research on the auto industry, and will expand my auto-industry centered research into a broader, transportation industry oriented context.   I am also interested in food and agricultural products, pharmaceutical, and medical devices industries where product quality and safety have significant implications to human life and society as a whole.

Charu Chandra

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My research interests are in developing inter-disciplinary knowledge in System Informatics, as the basis for study of complex system problems with the fusion of theory, computation, and application components adopted from Systems and Informatics fields. In this framework, a complex system such as the supply chain is posited as a System-of-Systems; i.e., a collection of individual business entities organized as a composite system with their resources and capabilities pooled to obtain an interoperable and synergistic system, possessing common and shared goals and objectives. Informatics facilitates coordination and integration in the system by processing and sharing information among supply chain entities for improved decision-making.

A common theme of my research is the basic foundation of universality of system and the realization that what makes it unique is its environment. This has enabled to categorize problems, designs, models, methodologies, and solution techniques at macro and micro levels and develop innovative solutions by coordinating these levels in an integrated environment.

My goal is to study the efficacy of the body of knowledge available in Systems Theory, Information Science, Artificial Intelligence & Knowledge Management, Management Science, Industrial Engineering and Operations Research fields; applied uniquely to issues and problems of complex systems in the manufacturing and service sectors.

Theoretical work investigated by me in this research thrust relates to:

  • Developing Generalized System Taxonomies and Ontologies for complex systems management.
  • Experimenting with Problem Taxonomies for design and modeling efficiencies in complex system networks.
  • Developing methodologies, frameworks and reference models for complex systems management.
  • Computation and application development focused on developing algorithms and software development for:
    • Supply chain information system and knowledge library using Web-based technology as a dissemination tool.
    • Integration with Enterprise Resource Planning modules in SAP software.
    • Supply chain management problem-solving through application of problem specific simulation and optimization.

My research has extended to application domains in healthcare, textiles, automotive, and defense sectors. Problems and issues addressed relate to health care management, operationalizing of sustainability, energy conservation, global logistics management, mega-disaster recovery, humanitarian needs management, and entrepreneurship management.

Currently, my application focus is on expanding the breadth and depth of inquiry in the healthcare domain. Among the topics being investigated are: (1) the organization and structure of health care enterprises; and (2) operations and strategies that relate to management of critical success factors, such as costs, quality, innovation and technology adoption by health care providers. Two significant topics that I have chosen to study with regard to care for elderly patients suffering from chronic congestive heart failure and hypertension are: (1) the design of patient-centered health care delivery to improve quality of care; and (2) managing enhanced care costs due to readmission of these patients.

Data science applications: Real-time data processing in supply chains, Knowledge portals for decision-making in supply chains, information sharing for optimizing patient-centered healthcare delivery

Romesh P. Nalliah

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Dr. Nalliah’s research expertise is process evaluation. He has studied various healthcare processes, educational processes and healthcare economics. Dr. Nalliah’s research studies were the first time nationwide data was used to highlight emergency room resource utilization for managing dental conditions in the United States. Dr. Nalliah is internationally recognized as a pioneer in the field of nationwide hospital dataset research for dental conditions and has numerous publications in peer reviewed journals. After completing a masters degree at Harvard School of Public Health, Dr. Nalliah’s interests have expanded and he has studied various public health issues including sports injuries, poisoning, child abuse, motor vehicle accidents and surgical processes (like stem cell transplants, cardiac valve surgery and fracture reduction). National recognition of his expertise in these broader topics of medicine have given rise to opportunities to lecture to medical residents, nurse practitioners, students in medical, pharmacy and nursing programs about oral health. This is his passion- that his research should inform an evolution of health education curriculum and practice.

Dr. Nalliah’s professional mission is to improve healthcare delivery systems and he is interested in improving processes, minimizing inefficiencies, reducing healthcare bottlenecks, increasing quality, and increase task sharing which will lead to a patient-centered, coherent healthcare system. Dr. Nalliah’s research has identified systems constraints and his goal is to influence policy and planning to break those constraints and improve healthcare delivery.

Vijay Subramanian

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Professor Subramanian is interested in a variety of stochastic modeling, decision and control theoretic, and applied probability questions concerned with networks. Examples include analysis of random graphs, analysis of processes like cascades on random graphs, network economics, analysis of e-commerce systems, mean-field games, network games, telecommunication networks, load-balancing in large server farms, and information assimilation, aggregation and flow in networks especially with strategic users.

Jieping Ye

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Jieping Ye, PhD, is Associate Professor of Computational Medicine and Bioinformatics in the Medical School at the University of Michigan, Ann Arbor.

The Ye Lab has been conducting fundamental research in machine learning and data mining, developing computational methods for biomedical data analysis, and building informatics software. We have developed novel machine learning algorithms for feature extraction from high-dimensional data, sparse learning, multi-task learning, transfer learning, active learning, multi-label classification, and matrix completion. We have developed the SLEP (Sparse Learning with Efficient Projections) package, which includes implementations of large-scale sparse learning models, and the MALSAR (Multi-tAsk Learning via StructurAl Regularization) package, which includes implementations of state-of-the-art multi-task learning models. SLEP achieves state-of-the-art performance for many sparse learning models, and it has become one of the most popular sparse learning software packages. With close collaboration with researchers at the biomedical field, we have successfully applied these methods for analyzing biomedical data, including clinical image data and genotype data.

Muzammil M. Hussain

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Muzammil M. Hussain is Assistant Professor of Communication and Media, Faculty Associate at the U-M International Institute and the U-M Institute for Social Research, and Faculty Affiliate at the U-M Ford School of Public Policy’s Science, Technology, and Public Policy Program (STPP) and the Michigan Institute for Data Science (MIDAS). Dr. Hussain’s interdisciplinary research is at the intersections of global communication, social analytics, and technology governance. At Michigan, Professor Hussain teaches courses on digital politics, research methods, and global innovation. He has authored numerous research articles, book chapters, and industry reports examining global ICT politics, innovation, and policy, including pieces in The Journal of Democracy, The Journal of International Affairs, The Brookings Institutions’ Issues in Technology and Innovation, The InterMedia Institute’s Development Research Series, International Studies Review, International Journal of Middle East Affairs, The Communication Review, Policy and Internet, and Journalism: Theory, Practice, and Criticism.

Viswanath Nagarajan

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My research is on the design of efficient (approximation) algorithms for combinatorial optimization problems. I work on deterministic optimization models, as well as richer models that handle uncertainty in data: stochastic, robust and online optimization. I am also interested in algorithms for scheduling and energy-efficiency in data centers.

Stephen M. Pollock

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Professor Pollock has taught courses in decision analysis, mathematical modeling, dynamic programming, and stochastic processes. He has applied operations research and decision analysis methods to problems in defense, criminal justice, manufacturing, epidemiology and medicine. He has authored over 60 technical papers, co-edited two books, and has served as a consultant to over 30 organizations, and on the editorial boards of three major journals.

He was chair of the IOE Department, chaired the University’s Research Policies Committee and Tenure Committee, served as Director of the Engineering College’s Financial Engineering Program and Engineering Global Leadership Program, was a member the College of Engineering’s Executive Committee, and a recipient of the College’s Attwood Award.

He has served on and chaired various NSF and NRC advisory boards and panels, and on the Army Science Board. He was President of the Operations Research Society of America, was awarded the 2001 INFORMS Kimball Medal, is a fellow of INFORMS and AAAS and is a member of the National Academy of Engineering