2015 Informs Annual Meeting

SB26

INFORMS Philadelphia – 2015

SB23 23-Franklin 13, Marriott Reflected Diffusions and Stochastic Networks Sponsor: Applied Probability Sponsored Session Chair: Kavita Ramanan, Professor, Brown University, 182, George Street, Box F, Providence, RI, 02912, United States of America, kavita_ramanan@brown.edu Co-Chair: Mohammadreza Aghhajani, Brown University, Providence, RI, United States of America, Mohammadreza_Aghajani@Brown.edu 1 - Reflected Brownian Motions in Stable Models for Large Equity Markets Ioannis Karatzas, Columbia University, Department of Mathematics, New York, NY, 10027, United States of America, ik@math.columbia.edu We construct systems of Brownian particles interacting through their ranks. These interactions give rise to invariant measures which are in broad agreement with stability properties observed in large equity markets over long time-periods. The models have connections with the analysis of Queueing Networks in heavy traffic. Their hydrodynamic-limit behavior is governed by generalized porous medium equations with convection. We survey briefly recent progress on some of these fronts. 2 - Pathwise Differentiability of Semimartingale Reflected Brownian Motions in Convex Polyhedrons We consider the pathwise differentiability of semimartingale reflected Brownian motions (SRBMs) in convex polyhedrons with respect to input parameters that determine the initial condition and drift. The derivatives are characterized as solutions to time-dependent Skorokhod type problems associated with the SRBMs. As applications, we characterize derivatives of stochastic flows for SRBMs and compute the sensitivity of SRBMs to small perturbations of the drift. 3 - Existence and Nonexistence Results for Diffusion Limits of Serve-the-Longest-Queue Rami Atar, Technion, Department of Electrical Engineering, Technion,, Haifa, Israel, atar@ee.technion.ac.il, Subhamay Saha When serve-the-longest-queue is considered for a system with finite buffers that are equal in size, diffusion limits of queue length exist in conventional heavy traffic, while they do not always exist in the Halfin-Whitt regime. This phenomenon will be described, along with implications on a game theoretic set up of the network, in which customers are strategic. SB24 24-Room 401, Marriott Data Mining and Network Inference for Social and Health Application I Sponsor: Artificial Intelligence Sponsored Session Chair: Sung Won Han, New York University, 650 First Avenue, New York, NY, United States of America, sungwonhan2@gmail.com Co-Chair: Chen Kan, University of South Florida, 4202 E. Fowler Ave. ENB118, Tampa, FL, United States of America, chenkan@mail.usf.edu 1 - The Evolution of User Roles in Online Health Communities Xi Wang, The University of Iowa, S343 PBB, The University of Iowa, Iowa City, IA, 52242, United States of America, xi-wang-1@uiowa.edu, Zhiya Zuo, Kang Zhao Online health communities (OHCs) have become a major source of social support for people with health problems. By analyzing how users’ roles change over time, we constructed transition graphs to illustrate evolution of users’ roles in an OHC. It was revealed that the types social support received by a user may facilitate or delay her role transitioning. Our research has implications to for OHC operators to track users’ behaviors in order to manage an OHC. 2 - Extracting Biomedical Relationships from Unstructured Documents Adel Javanmard, Assistant Professor, Marshall School of Business, David Lipshutz, Postdoctoral Research Associate, Brown University, 182 George Street Box F, Providence, RI, 02912, United States of America, David_Lipshutz@brown.edu, Kavita Ramanan

becoming increasingly complex. This trend has driven the need for automated curation of scientific literature. We consider the problem of extracting drug-gene relationships from unstructured documents and propose a novel algorithm to this end. Our algorithm is intimately related to new advances in clustering sparse graphs. 3 - Network Models for Monitoring High-Dimensional Image Profiles Chen Kan, University of South Florida, 4202 E. Fowler Ave. ENB118, Tampa, FL, United States of America, chenkan@mail.usf.edu, Hui Yang Advanced sensing brings the proliferation of image profiles, which pose significant challenges for process monitoring and control. However, traditional SPC is limited in its ability to readily address complex structures of high-dimensional profiles. This paper presents a novel dynamic network methodology for monitoring and control of high-dimensional imaging streams. Experimental results show that the proposed approach provides an effective online control chart for monitoring image profiles. SB25 25-Room 402, Marriott Mobile and Social Data Analytics Sponsor: Information Systems Sponsored Session Chair: Rajiv Garg, Assistant Professor, McCombs School of Business, 2110 Speedway, UT-Austin, Austin, TX, 78705, United States of America, rajiv.garg@mccombs.utexas.edu 1 - Mobile Big Data Analytics Xueming Luo, Temple University, 1801 Liacouras Walk, Philadelphia, PA, United States of America, Xueming.Luo@temple.edu This presentation discusses how smart devices (smartphones, machine-to- machine connected solutions, wearables, Internet-of-things technologies) and big data affect advertising, promotions, marketing ROI, and omni-channel targeting effectiveness. Over 3.6 billion people worldwide are deeply engaged with smartphone devices. More than half of adult Americans rely on smartphones to go about daily life. 2 - An Expository Study of Human Geographic Affinity Measurement Based Mobility Network Rong Duan, AT&T Labs, Research, 1 AT&T Way, Bedminster, NJ, United States of America, rongduan@research.att.com Geographic data play critical roles in different domains.Based on the nearly complete coverage of mobile cell towers and the frequent activities of mobile devices, we propose a Human Geographic Affinity (HGA) metric. HGA measures the degree of recapture for a crowd in a specific geographic area during a time period. The metric quantifies the stability of a crowd in a geographic area, and categories areas by their dynamic of human mobility. This study is completed in- line with privacy policy. SB26 26-Room 403, Marriott INFORMS Undergraduate Operations Research Prize I Cluster: INFORMS Undergraduate Operations Research Prize Invited Session Chair: Aurelie Thiele, Lehigh University, 200 W Packer Ave, Bethlehem, PA, 18015, United States of America, aut204@lehigh.edu 1 - A Composite Risk Measure Framework for Decision Making under Uncertainty Pengyu Qian, Columbia University, Columbia Business School c/o PhD Office, 3022 Broadway,311 Uris Hall, New York, NY, 10027, United States of America, qianpengyu@pku.edu.cn, Zizhuo Wang, Zaiwen Wen In this talk, we present a unified framework for decision making under uncertainty. Our framework is based on the composite of two risk measures accounting for parametric (given distribution) and distributional uncertainty respectively. The framework generalizes many existing models. We also propose new models within this framework whose solutions have probabilistic guarantees and are less conservative comparing to traditional models. Numerical experiments demonstrate the strength of our models.

University of Southern California, Los Angeles, CA, United States of America, ajavanma@marshall.usc.edu

The published biomedical research is growing at an unprecedented rate. On the other hand, the information we need to extract for many research objectives is

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