PLENARY TRACKS CAREER POSTERS INFORMS PRIZES NETWORKING EXHIBITS PROMENADE LEVEL PROMENADE SOUTH ELEVATORS ESCALATORS MILANO BALLROOM SORRENTO SALERNO IMPERIAL BOARDROOM VERONA TURIN TREVI PISA PALERMO SIENA SENATE BOARDROOM CONSUL BOARDROOM LIVORNO MESSINA MODENA POMPEIAN BALLROOM I II III IV I II III IV ROMAN BALLROOM GENOA FLORENTINE BALLROOM I/II III IV CAPRI ANZIO INFORMS REGISTRATION Download INFORMS Meetings App or visit http://meetings.informs.org/analytics2017 WIRELESS ACCESS CODE: informs17 SCAN HERE for the latest schedule for MONDAY, APRIL 3 * Emperors I and Palace Ballrooms I & II - Emperors Level ESCALATORS BALCONY ELEVATORS ELEVATORS UMBRIA TUSCANY OCTAVIUS BALLROOM EXHIBITS POSTER SESSIONS ANALYTICS CONNECT INTERVIEWS 23 22 21 19 18 17 1/2/3 5/6 7/8 9/10 13/14 15/16
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PLENARY
TRACKS
CAREER
POSTERS
INFORMS PRIZES
NETWORKING
EXHIBITS
PRO
MEN
AD
E LE
VEL
PRO
MEN
AD
E SO
UTH
ELEVATO
RS
ESCALATORS
MILANO BALLROOM
SORR
ENTO
SALE
RNOIMPERIAL
BOARDROOM
VERONA
TURIN
TREVIPISA
PALERMO
SIENA
SENATE BOARDROOM
CONSULBOARDROOM
LIVORNO
MESSINA
MODENA
POMPEIAN BALLROOM
I II III IV
I II
III IV
ROMAN BALLROOM
GENOA
FLORENTINE BALLROOM
I/II III IV
CAPRI
ANZIO
INFORMS REGISTRATION
Download INFORMS Meetings App or visit http://meetings.informs.org/analytics2017
WIRELESS ACCESS CODE: informs17
SCAN HERE for the latest schedule forMONDAY, APRIL 3
* Emperors I and Palace Ballrooms I & II - Emperors Level
Third Party Compliance Risk Analytics with Incomplete DataJonathan Yan, Dun & Bradstreet
How to Deployyour Analytic Models to Empower Non-technicalBusiness UsersFICO
anyLogistix: Integrating Analytical & Dynamic Sim. Meth. for Precise Supply Chain Design & Analysis AnyLogic North America
Building & Solving Opt. Models with SASSAS Institute, Inc.
11:30am–12:20pm
Voice-of-customer Analytics: Evolving from Descriptive to Prescriptive Anthony Volpe, QuantWorks
Applying Cognitive Intel. to Real-world Use CasesSteve DeAngelis, Enterra Solutions
Prac. Approaches using Customer Web Behav. to Maximize Hospitality & Gaming RevenuesKirby Bosch and Pavan Kapur, Nor1
Revenue Management Provides Double-Digit Revenue Lift for Holiday RetirementHoliday Retirement with Prorize, LLC
Appl. of Machine Learning for Asset Failure Prediction to Improve Supply Chain PerformanceAdam McElhinney, Uptake
Where Does Data Sci. Go Next?Walter Frick, Harvard Business Review; Hilary Mason, Fast Forward Labs & Kalyan Veeramachaneni, MIT
Creating CompetitiveAdvantage using Analytics Peter Bell, Ivey Business School, Western University
Innov. in Forecasting Impact of Price Changes in a Portfolio of Prod. with Appl. to Food Service Indust.Erik Jensen, Pricing Solutions
Addressing the Gender Pay Gap with AnalyticsMargrét V. Bjarnadottir, University of Maryland College Park
Combining Predictive & Prescriptive Models in Gurobi: A Simple Case StudyGurobi
Opt. Modeling Tools from LINDO Lindo Systems, Inc.
Text Analytics SoftwareProvalis Research
2:10–3:00pm
Online Matching & Allocation in Advertising Markets Aranyak Mehta, Google
Marketplace EngineeringGarrett van Ryzin, Columbia University & Uber Technologies
It Shouldn’t Be This Complicated, But It IsLori Sinn, American Airlines
A Novel Movement Planning Algorithm for Dispatching TrainsGE with Norfolk Southern
Global Supply Network Modeling & Opt. at Caterpillar’s Assurance of Supply CenterAnthony Grichnik, Caterpillar
Growing an Analytics TeamZahir Balaporia, FICO; Linda Burtch, Burtch Works; Tim Jacobs, Amazon; Juergen Klenk, Deloitte; Olga Raskina, Juno Therapeutics
Imagining Predictive Analytics in HealthcareDenise White, University of Cincinnati
A Multidiscip. Analytics Effort to Support Public Health Pol. against Cervical Cancer Epidemics in ColombiaIvan Mura, Univ de los Andes
How to Safely Release a New Feature for Mobile App? A Staged Rollout Framework with Comparative AnalyticsZhenyu Zhao, Uber
Oper. Analytics in the Age of Big DataWebbMason
AMPL in the Cloud: Using Online Services to Develop & Deploy Opt. App. through Algebraic ModelingAMPL
Effectively Leveraging a Small Opt. Team across a Large OrganizationAIMMS
3:00–3:40pm
3:05–3:55p The Off-Hours Delivery Project in New York CityNYC DOT with RPI
Poster Session, Exhibits, and Refreshment Break - Octavius Ballroom
3:50– 4:40pm
Four Common Research MistakesRobert Peterson, University of Texas
A Tutorial for Deep LearningMustafa Kabul, SAS
Scalable Analytics in Interconnected Retail Xingchu Liu, BlackLocus
4:00–4:50pmARC Uses Analytics-based Methods to Improve Blood Collection Oper.American Red Cross with Georgia Tech
Opt. Delivery Time Windows at a Grocery Store Chain Luís Guimarães, University of Porto
Guide to Analytics Body of KnowledgeTerry Harrison, Penn State & James Cochran, University of Alabama
Winning at Litigation: Decision Analysis at Stanford MedicineJohn Celona, Decision Analysis Associates LLC