{"id":889,"date":"2023-01-18T15:24:05","date_gmt":"2023-01-18T15:24:05","guid":{"rendered":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/tracks\/defense-copy\/"},"modified":"2023-03-01T19:06:28","modified_gmt":"2023-03-01T19:06:28","slug":"informs-prizes","status":"publish","type":"page","link":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/tracks\/informs-prizes\/","title":{"rendered":"INFORMS Prizes &amp; Special Sessions"},"content":{"rendered":"<!--themify_builder_content-->\n<div id=\"themify_builder_content-889\" data-postid=\"889\" class=\"themify_builder_content themify_builder_content-889 themify_builder tf_clear\">\n                    <div  data-lazy=\"1\" class=\"module_row themify_builder_row tb_mkwd706 tb_first tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_1 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col-full tb_7pu0707 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_iwcu708   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <div class=\"module_row themify_builder_row tb_n338895 tf_clearfix\" style=\"margin: 0px 0px 16.4688px; padding: 0px; position: relative; box-sizing: border-box; backface-visibility: hidden; color: #202225; font-family: 'Open Sans'; font-size: 16px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: #ffffff; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;\">\n<div class=\"row_inner col_align_top col-count-1 tf_box tf_w tf_rel\" style=\"margin: 0px auto; padding: 0px; width: 1160px; box-sizing: border-box; position: relative; display: flex; flex-flow: wrap; max-width: 100%;\">\n<div class=\"module_column tb-column col-full tb_gpk1896 tf_box last\" style=\"margin: 0px; padding: 0px; box-sizing: border-box; position: relative; display: flex; flex-flow: wrap; float: left; align-items: flex-start; align-content: flex-start; width: 823.594px; clear: left;\">\n<div class=\"tb-column-inner tf_box tf_w\" style=\"margin: 0px; padding: 0px; width: 823.594px; box-sizing: border-box;\">\n<div class=\"module module-text tb_uqfc896 integrate\" style=\"margin: 0px; padding: 0px; transition: background 0.5s ease 0s, font-size, line-height, color, padding, margin, border, border-radius, box-shadow, text-shadow, filter, transform; position: relative; box-sizing: border-box;\">\n<div class=\"tb_text_wrap\" style=\"margin: 0px; padding: 0px;\">\u00a0<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"module_row themify_builder_row tb_xful360 tf_clearfix\" style=\"margin: 0px 0px 16.4688px; padding: 0px; position: relative; box-sizing: border-box; backface-visibility: hidden; transition: background 0.5s ease 0s, font-size, line-height, color, padding, margin, border, border-radius, box-shadow, text-shadow, filter, transform; color: #202225; font-family: 'Open Sans'; font-size: 16px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; background-color: #ffffff; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;\">\n<div class=\"row_inner col_align_top col-count-1 tf_box tf_w tf_rel\" style=\"margin: 0px auto; padding: 0px; width: 1160px; box-sizing: border-box; position: relative; display: flex; flex-flow: wrap; max-width: 100%;\">\n<div class=\"module_column tb-column col-full tb_hldw360 tf_box last\" style=\"margin: 0px; padding: 0px; box-sizing: border-box; position: relative; display: flex; flex-flow: wrap; float: left; align-items: flex-start; align-content: flex-start; width: 823.594px; transition: background 0.5s ease 0s, font-size, line-height, color, padding, margin, border, border-radius, box-shadow, text-shadow, filter, transform; clear: left;\">\n<div class=\"tb-column-inner tf_box tf_w\" style=\"margin: 0px; padding: 0px; width: 823.594px; box-sizing: border-box;\">\n<div class=\"module module-text tb_e092360 prizes\" style=\"margin: 0px; padding: 0px; transition: background 0.5s ease 0s, font-size, line-height, color, padding, margin, border, border-radius, box-shadow, text-shadow, filter, transform; position: relative; box-sizing: border-box;\">\n<div class=\"tb_text_wrap\" style=\"margin: 0px; padding: 0px;\">\n<p style=\"margin: 0px 0px 1.3em; padding: 0px;\">INFORMS grants several prestigious Institute-wide prizes and awards for meritorious achievement each year. This track will feature presentations for the Wagner Prize, INFORMS Prize, and the UPS George D. Smith Prize winner. Innovative Applications in Analytics Award (IAAA) finalists will also present. Special sessions include presentations hosted by our Certified Analytics Professional (CAP<sup style=\"margin: 0px; padding: 0px;\">\u00ae<\/sup>) Program and Women in OR\/MS.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-lazy=\"1\" class=\"module_row themify_builder_row tb_j8y6706 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_1 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col-full tb_8n4b710 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_l1rs861 all  \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h6><a href=\"https:\/\/www.informs.org\/Recognizing-Excellence\/INFORMS-Prizes\/Daniel-H.-Wagner-Prize-for-Excellence-in-the-Practice-of-Advanced-Analytics-and-Operations-Research\" data-feathr-click-track=\"true\" data-feathr-link-aids=\"[&quot;622fa93bb0ebf976bd76e19a&quot;]\">2022 Daniel H. Wagner Prize Reprise: Generalized Synthetic Control for TestOps at ABl: Models, Algorithms, and Infrastructure<\/a><\/h6>\n<p>Speakers: Tianyi Peng, MIT and Iva Rosa Montenegro, Anheuser-Busch InBev<\/p>    <\/div>\n<\/div>\n<!-- \/module text --><!-- module accordion -->\n<div  class=\"module module-accordion tb_zgod937 \" data-behavior=\"toggle\" data-lazy=\"1\">\n    \n    <ul class=\"ui module-accordion   tb_default_color\">\n            <li>\n            <div class=\"accordion-title tf_rel\">\n                <a href=\"#acc-zgod937-0\" class=\"tb_title_accordion\" aria-controls=\"acc-zgod937-0-content\" aria-expanded=\"false\">\n                    <i class=\"accordion-icon\"><svg  class=\"tf_fa tf-ti-plus\" aria-hidden=\"true\"><use href=\"#tf-ti-plus\"><\/use><\/svg><\/i>                    <i class=\"accordion-active-icon tf_hide\"><svg  class=\"tf_fa tf-ti-close\" aria-hidden=\"true\"><use href=\"#tf-ti-close\"><\/use><\/svg><\/i>                    <span class=\"accordion-title-wrap\">Click to view abstract<\/span>                <\/a>\n            <\/div><!-- .accordion-title -->\n            <div id=\"acc-zgod937-0-content\" data-id=\"acc-zgod937-0\" aria-hidden=\"true\" class=\"accordion-content tf_hide tf_clearfix\">\n                                    <div class=\"tb_text_wrap\">\n                        <p>In this presentation they describe a novel approach to learning from experiments in the world of physical retail, and an associated platform, TestOps, implemented by ABI and MIT. TestOps leverages a recent theoretical breakthrough to learn from experiments when treatment effects are small, the environment is noisy and non-stationary, and adherence problems are commonplace, resulting in ~100x increase of experimental power relative to alternatives. TestOps currently runs experiments impacting ~135M USD in revenue every month and routinely identifies interventions that result in a 1-2% increase in sales volume.<\/p>                    <\/div>\n                            <\/div><!-- .accordion-content -->\n        <\/li>\n        <\/ul>\n\n<\/div><!-- \/module accordion -->        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-lazy=\"1\" class=\"module_row themify_builder_row tb_aqvf878 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_1 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col-full tb_omd3878 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_evxu879 all  \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h6><a href=\"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/speakers\/jeff-cohen\/\" data-feathr-click-track=\"true\" data-feathr-link-aids=\"[&quot;622fa93bb0ebf976bd76e19a&quot;]\">INFORMS Advocacy Initiative: Promoting Data-Driven Decision Making in Washington, DC<\/a><\/h6>\n<p>Speaker: Jeff Cohen, Chief Strategy &amp; Innovation Officer at INFORMS<\/p>    <\/div>\n<\/div>\n<!-- \/module text --><!-- module text -->\n<div  class=\"module module-text tb_wq6j879 level executive  \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <p>Executive<\/p>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-lazy=\"1\" class=\"module_row themify_builder_row tb_m7u0101 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_1 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col-full tb_0h0x101 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_xmx3101 all  \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h6><a href=\"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/speakers\/janice-lichenwaldt\/\">Filling Your Cup: What it Takes to Be an Effective Leader\u00a0 (<em>Hosted by Women in OR\/MS)<\/em><\/a><\/h6>\n<p>Speaker: Janice Lichtenwaldt, Executive Leadership Coach at Virago Coaching<\/p>    <\/div>\n<\/div>\n<!-- \/module text --><!-- module text -->\n<div  class=\"module module-text tb_42ww101 level executive  \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <p>Executive<\/p>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-lazy=\"1\" class=\"module_row themify_builder_row tb_q3d9606 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_1 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col-full tb_d9qo606 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_ijdw606 all  \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h6>Innovative Applications in Analytics Award (IAAA)<\/h6>\n<p>The IAAA Finalists will present at the conference on Tuesday, April 18 in the INFORMS Prizes &amp; Special Sessions Track from 9:10 \u2013 11:55am EST. Judges will then review the rank and announce the winner at the INFORMS Analytics Society luncheon.<\/p>    <\/div>\n<\/div>\n<!-- \/module text --><!-- module accordion -->\n<div  class=\"module module-accordion tb_il30221 \" data-behavior=\"toggle\" data-lazy=\"1\">\n    \n    <ul class=\"ui module-accordion   tb_default_color\">\n            <li>\n            <div class=\"accordion-title tf_rel\">\n                <a href=\"#acc-il30221-0\" class=\"tb_title_accordion\" aria-controls=\"acc-il30221-0-content\" aria-expanded=\"false\">\n                    <i class=\"accordion-icon\"><svg  class=\"tf_fa tf-ti-plus\" aria-hidden=\"true\"><use href=\"#tf-ti-plus\"><\/use><\/svg><\/i>                    <i class=\"accordion-active-icon tf_hide\"><svg  class=\"tf_fa tf-ti-close\" aria-hidden=\"true\"><use href=\"#tf-ti-close\"><\/use><\/svg><\/i>                    <span class=\"accordion-title-wrap\">An Integrated Deep Learning and Online Optimization Approach to Assign the Fulfillment Routes to Parcels<\/span>                <\/a>\n            <\/div><!-- .accordion-title -->\n            <div id=\"acc-il30221-0-content\" data-id=\"acc-il30221-0\" aria-hidden=\"true\" class=\"accordion-content tf_hide tf_clearfix\">\n                                    <div class=\"tb_text_wrap\">\n                        <p>Cainiao Network, a logistics arm of the Alibaba Group, collaborates with logistics partners to provide delivery services. For a sequence of randomly created parcels within a period (e.g., one day), we need to make decisions sequentially and select a series of fulfillment routes with minimal costs while satisfying the constraints (e.g., the limited number of orders that a partner can assign). For this online decision problem, we first design a forecasting algorithm based on deep learning to predict the number of parcels created in the period. Then, taking the number as input, we employ an online algorithm based on the optimality condition to make real-time decisions. Since April 2021, the approach has been implemented for parcels from China to other countries, thus saving millions of dollars annually.<\/p>                    <\/div>\n                            <\/div><!-- .accordion-content -->\n        <\/li>\n        <\/ul>\n\n<\/div><!-- \/module accordion --><!-- module accordion -->\n<div  class=\"module module-accordion tb_71yl699 \" data-behavior=\"toggle\" data-lazy=\"1\">\n    \n    <ul class=\"ui module-accordion   tb_default_color\">\n            <li>\n            <div class=\"accordion-title tf_rel\">\n                <a href=\"#acc-71yl699-0\" class=\"tb_title_accordion\" aria-controls=\"acc-71yl699-0-content\" aria-expanded=\"false\">\n                    <i class=\"accordion-icon\"><svg  class=\"tf_fa tf-ti-plus\" aria-hidden=\"true\"><use href=\"#tf-ti-plus\"><\/use><\/svg><\/i>                    <i class=\"accordion-active-icon tf_hide\"><svg  class=\"tf_fa tf-ti-close\" aria-hidden=\"true\"><use href=\"#tf-ti-close\"><\/use><\/svg><\/i>                    <span class=\"accordion-title-wrap\">From Particulate processes to In-vitro Fertilization: Theory to Clinical Practice<\/span>                <\/a>\n            <\/div><!-- .accordion-title -->\n            <div id=\"acc-71yl699-0-content\" data-id=\"acc-71yl699-0\" aria-hidden=\"true\" class=\"accordion-content tf_hide tf_clearfix\">\n                                    <div class=\"tb_text_wrap\">\n                        <p>The success of In-vitro fertilization (IVF) majorly depends upon successful superovulation, defined by the number and uniformly high quality of eggs retrieved in a cycle. Currently, this step is executed using almost daily monitoring of the follicular development using ultrasound and blood tests. Although there are general guidelines for the dosage, the dose is not optimized for each patient, and overstimulation complications can occur. The cost of testing and drugs makes this stage very expensive. To overcome the shortcoming of this system, we have developed a mathematical procedure that can provide a personalized model and optimal drug treatment for each patient. Recently, we conducted clinical trials in India. The results show that the dosage predicted by using the model is 30-40% less than that suggested by the IVF doctors. The testing for patients is reduced by 72%. We also found that the number of good-quality embryos obtained using this approach was significantly higher than in current practice. This model and optimal control procedure were released in early September as a decision support tool Opt-IVF for hospitals to use in their clinical practice. So far, five hospitals have signed up to use (and are using it daily).<\/p>                    <\/div>\n                            <\/div><!-- .accordion-content -->\n        <\/li>\n        <\/ul>\n\n<\/div><!-- \/module accordion --><!-- module accordion -->\n<div  class=\"module module-accordion tb_y2yc177 \" data-behavior=\"toggle\" data-lazy=\"1\">\n    \n    <ul class=\"ui module-accordion   tb_default_color\">\n            <li>\n            <div class=\"accordion-title tf_rel\">\n                <a href=\"#acc-y2yc177-0\" class=\"tb_title_accordion\" aria-controls=\"acc-y2yc177-0-content\" aria-expanded=\"false\">\n                    <i class=\"accordion-icon\"><svg  class=\"tf_fa tf-ti-plus\" aria-hidden=\"true\"><use href=\"#tf-ti-plus\"><\/use><\/svg><\/i>                    <i class=\"accordion-active-icon tf_hide\"><svg  class=\"tf_fa tf-ti-close\" aria-hidden=\"true\"><use href=\"#tf-ti-close\"><\/use><\/svg><\/i>                    <span class=\"accordion-title-wrap\">Instrumenting While Experimenting: An Empirical Method for Competitive Pricing at Scale<\/span>                <\/a>\n            <\/div><!-- .accordion-title -->\n            <div id=\"acc-y2yc177-0-content\" data-id=\"acc-y2yc177-0\" aria-hidden=\"true\" class=\"accordion-content tf_hide tf_clearfix\">\n                                    <div class=\"tb_text_wrap\">\n                        <p>We partner with a leading U.S. e-commerce retailer and develop a competitive pricing method in the context of increasing competition in online retailing. Our method allows retailers to more accurately respond to competitors&#8217; price changes at scale. First, we construct a parsimonious demand model that captures the key trade-off in competitive pricing by accounting for two types of customers heterogeneous in their \u201cprice-shopping\u201d&#8217; behavior. Next, we design and implement a large-scale randomized price experiment on over 10,000 products. Leveraging the experiment as well as the control function approach, we are able to obtain unbiased estimates of the demand model, in particular, price elasticities of both loyal and price-shopping consumers as well as the sales lift when we undercut competitors in price. Lastly, we recommend price responses by solving a constrained optimization problem which uses the estimated demand model as an input. We test this pricing method through another large-scale controlled field experiment on over 10,000 products and demonstrate significant improvements&#8212;increasing revenue by over 15% and increasing profit by over 10%.<\/p>                    <\/div>\n                            <\/div><!-- .accordion-content -->\n        <\/li>\n        <\/ul>\n\n<\/div><!-- \/module accordion --><!-- module accordion -->\n<div  class=\"module module-accordion tb_33e2629 \" data-behavior=\"toggle\" data-lazy=\"1\">\n    \n    <ul class=\"ui module-accordion   tb_default_color\">\n            <li>\n            <div class=\"accordion-title tf_rel\">\n                <a href=\"#acc-33e2629-0\" class=\"tb_title_accordion\" aria-controls=\"acc-33e2629-0-content\" aria-expanded=\"false\">\n                    <i class=\"accordion-icon\"><svg  class=\"tf_fa tf-ti-plus\" aria-hidden=\"true\"><use href=\"#tf-ti-plus\"><\/use><\/svg><\/i>                    <i class=\"accordion-active-icon tf_hide\"><svg  class=\"tf_fa tf-ti-close\" aria-hidden=\"true\"><use href=\"#tf-ti-close\"><\/use><\/svg><\/i>                    <span class=\"accordion-title-wrap\">Vaccine Equity and Occupational Health and Safety Analytics for COVID<\/span>                <\/a>\n            <\/div><!-- .accordion-title -->\n            <div id=\"acc-33e2629-0-content\" data-id=\"acc-33e2629-0\" aria-hidden=\"true\" class=\"accordion-content tf_hide tf_clearfix\">\n                                    <div class=\"tb_text_wrap\">\n                        <p>From March 2020 through March 2022 a team from the U.S. Army Engineer Research and Development Center (ERDC) was constituted to develop a suite of innovative analytics applications to describe, predict, and inform COVID-19 risks and societal implications. Two key innovations developed for FEMA and ASPR Region I included (a) a vaccine equity modeling and analysis platform, and (b) a return-to-work simulator and decision support system. For (a), and in accordance with President Biden\u2019s Executive Order 13995 (Ensuring an Equitable Pandemic Response and Recovery), ERDC\u2019s Vaccine Equity Methodology included a three-step process to evaluate, at a county, state, regional, and national level, the various equity considerations and equity gaps relative to vaccine distribution and community uptake from March 2021 through January 2022. For (b), ERDC\u2019s Workplace Micro-Exposure Model (MEM) was used to guide return-to-work decisions for emergency responders in Region 1 beginning Summer 2020. The MEM model harvested epidemiological forecast data and assessed workforce risk based on in-office participation against random-transit-events and building blueprints\/population flow. Both tools were used to guide elements of the COVID emergency response effort, promoting a safer workforce as well as more responsive and equitable vaccine distribution efforts to various underserved communities across New England.<\/p>                    <\/div>\n                            <\/div><!-- .accordion-content -->\n        <\/li>\n        <\/ul>\n\n<\/div><!-- \/module accordion --><!-- module accordion -->\n<div  class=\"module module-accordion tb_tmws567 \" data-behavior=\"toggle\" data-lazy=\"1\">\n    \n    <ul class=\"ui module-accordion   tb_default_color\">\n            <li>\n            <div class=\"accordion-title tf_rel\">\n                <a href=\"#acc-tmws567-0\" class=\"tb_title_accordion\" aria-controls=\"acc-tmws567-0-content\" aria-expanded=\"false\">\n                    <i class=\"accordion-icon\"><svg  class=\"tf_fa tf-ti-plus\" aria-hidden=\"true\"><use href=\"#tf-ti-plus\"><\/use><\/svg><\/i>                    <i class=\"accordion-active-icon tf_hide\"><svg  class=\"tf_fa tf-ti-close\" aria-hidden=\"true\"><use href=\"#tf-ti-close\"><\/use><\/svg><\/i>                    <span class=\"accordion-title-wrap\">Analytical Pipeline for Identifying Potential Sex Trafficking Victims in Commercial Sex Ad Data<\/span>                <\/a>\n            <\/div><!-- .accordion-title -->\n            <div id=\"acc-tmws567-0-content\" data-id=\"acc-tmws567-0\" aria-hidden=\"true\" class=\"accordion-content tf_hide tf_clearfix\">\n                                    <div class=\"tb_text_wrap\">\n                        <p>Sex trafficking refers to the use of force, fraud, or coercion for sexual exploitation and is facilitated by commercial sex ad websites. Each day, more than 100,000 new ads and more than 500,000 images are posted on these sites. Although ad data can provide important insights for counter-trafficking efforts, linking the large volume of ads is challenging. Additionally, scammers create ads seeking to obtain deposits via electronic payment methods. These ads do not correspond to legitimate individuals and add noise to the data-linking process. In 2020, the Institute of Data and Analytics (IDA) at The University of Alabama launched the Sex Trafficking Analytics for Network Detection and Disruption (STANDD) initiative. The STANDD team developed and maintains an analytical pipeline that utilizes novel technologies and methodologies from information systems, network science, and machine learning to remove anomalies due to scam ads, link the remaining data into groups representing individuals, and utilize these data groups for network and movement detection. Data products from this pipeline have helped law enforcement and non-profit organizations establish contact with more than 40 potential sex trafficking victims, many of whom are now connected with services to get them out of \u201cthe life.\u201d<\/p>                    <\/div>\n                            <\/div><!-- .accordion-content -->\n        <\/li>\n        <\/ul>\n\n<\/div><!-- \/module accordion -->        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-lazy=\"1\" class=\"module_row themify_builder_row tb_r1fe950 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_1 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col-full tb_m5fz951 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_zxrp951 all  \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h6>INFORMS Prize<\/h6>\n<p>This prize is awarded annually to the company that effectively integrates analytics into organizational decision-making, and has repeatedly applied ORMS principles in pioneering, novel and lasting ways.\u00a0 The 2023 winner will be recognized at the Edelman Gala on Monday evening and present their innovative O.R. work. on Tuesday afternoon.<\/p>\n<p>Previous winners include BNSF Railway, Disney, U.S. Air Force, GM, Chevron, Memorial Sloan-Kettering Cancer Center, Sasol, Jeppesen, Intel, General Electric Global Research Center, Schneider National, Air Products and Chemicals, Procter &amp; Gamble, UPS, Wayfair and other leading companies.<\/p>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-lazy=\"1\" class=\"module_row themify_builder_row tb_0ubo822 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_1 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col-full tb_19tz823 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_fuxp823 all  \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h6>UPS George D. Smith Prize<\/h6>\n<p>The George D. Smith Prize is aimed at strengthening ties between academia and industry by rewarding institutions of higher education for effective and innovative preparation of students to be good practitioners of operations research. The Prize is generously underwritten by UPS. Awarded for the first time in 2012, past winners are Carnegie Mellon University, H. John Heinz III College, Sauder School of Business, University of British Columbia \u2013 Center for Operations Excellence, MIT Leaders for Global Operations, Naval Postgraduate School, and Tauber Institute for Global Operations at University of Michigan.<\/p>\n<p>The teams will present their work to the judges on Sunday, April 16. The Smith Prize winner will be announced at the Edelman Gala on Monday, April 17 and the 2023 winner will give their presentation on Tuesday afternoon.<\/p>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                        <\/div>\n        <\/div>\n        <\/div>\n<!--\/themify_builder_content-->","protected":false},"excerpt":{"rendered":"<p>\u00a0 INFORMS grants several prestigious Institute-wide prizes and awards for meritorious achievement each year. This track will feature presentations for the Wagner Prize, INFORMS Prize, and the UPS George D. Smith Prize winner. Innovative Applications in Analytics Award (IAAA) finalists will also present. Special sessions include presentations hosted by our Certified Analytics Professional (CAP\u00ae) Program [&hellip;]<\/p>\n","protected":false},"author":1001094,"featured_media":153,"parent":396,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"content-type":"","footnotes":""},"class_list":["post-889","page","type-page","status-publish","has-post-thumbnail","hentry","has-post-title","has-post-date","has-post-category","has-post-tag","has-post-comment","has-post-author",""],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v26.0 (Yoast SEO v26.0) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>INFORMS Prizes &amp; Special Sessions - 2023 INFORMS Business Analytics Conference<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/tracks\/informs-prizes\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"INFORMS Prizes &amp; Special Sessions\" \/>\n<meta property=\"og:description\" content=\"\u00a0 INFORMS grants several prestigious Institute-wide prizes and awards for meritorious achievement each year. 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This track will feature presentations for the Wagner Prize, INFORMS Prize, and the UPS George D. Smith Prize winner. Innovative Applications in Analytics Award (IAAA) finalists will also present. Special sessions include presentations hosted by our Certified Analytics Professional (CAP<sup style=\"margin: 0px; padding: 0px;\">\u00ae<\/sup>) Program and Women in OR\/MS.<\/p>\n<h6><a href=\"https:\/\/www.informs.org\/Recognizing-Excellence\/INFORMS-Prizes\/Daniel-H.-Wagner-Prize-for-Excellence-in-the-Practice-of-Advanced-Analytics-and-Operations-Research\" data-feathr-click-track=\"true\" data-feathr-link-aids=\"[&quot;622fa93bb0ebf976bd76e19a&quot;]\">2022 Daniel H. Wagner Prize Reprise: Generalized Synthetic Control for TestOps at ABl: Models, Algorithms, and Infrastructure<\/a><\/h6> <p>Speakers: Tianyi Peng, MIT and Iva Rosa Montenegro, Anheuser-Busch InBev<\/p>\n<ul><li><h4>Click to view abstract<\/h4><p>In this presentation they describe a novel approach to learning from experiments in the world of physical retail, and an associated platform, TestOps, implemented by ABI and MIT. TestOps leverages a recent theoretical breakthrough to learn from experiments when treatment effects are small, the environment is noisy and non-stationary, and adherence problems are commonplace, resulting in ~100x increase of experimental power relative to alternatives. TestOps currently runs experiments impacting ~135M USD in revenue every month and routinely identifies interventions that result in a 1-2% increase in sales volume.<\/p><\/li><\/ul>\n<h6><a href=\"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/speakers\/jeff-cohen\/\" data-feathr-click-track=\"true\" data-feathr-link-aids=\"[&quot;622fa93bb0ebf976bd76e19a&quot;]\">INFORMS Advocacy Initiative: Promoting Data-Driven Decision Making in Washington, DC<\/a><\/h6> <p>Speaker: Jeff Cohen, Chief Strategy &amp; Innovation Officer at INFORMS<\/p>\n<p>Executive<\/p>\n<h6><a href=\"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/speakers\/janice-lichenwaldt\/\">Filling Your Cup: What it Takes to Be an Effective Leader\u00a0 (<em>Hosted by Women in OR\/MS)<\/em><\/a><\/h6> <p>Speaker: Janice Lichtenwaldt, Executive Leadership Coach at Virago Coaching<\/p>\n<p>Executive<\/p>\n<h6>Innovative Applications in Analytics Award (IAAA)<\/h6> <p>The IAAA Finalists will present at the conference on Tuesday, April 18 in the INFORMS Prizes &amp; Special Sessions Track from 9:10 \u2013 11:55am EST. Judges will then review the rank and announce the winner at the INFORMS Analytics Society luncheon.<\/p>\n<ul><li><h4>An Integrated Deep Learning and Online Optimization Approach to Assign the Fulfillment Routes to Parcels<\/h4><p>Cainiao Network, a logistics arm of the Alibaba Group, collaborates with logistics partners to provide delivery services. For a sequence of randomly created parcels within a period (e.g., one day), we need to make decisions sequentially and select a series of fulfillment routes with minimal costs while satisfying the constraints (e.g., the limited number of orders that a partner can assign). For this online decision problem, we first design a forecasting algorithm based on deep learning to predict the number of parcels created in the period. Then, taking the number as input, we employ an online algorithm based on the optimality condition to make real-time decisions. Since April 2021, the approach has been implemented for parcels from China to other countries, thus saving millions of dollars annually.<\/p><\/li><\/ul>\n<ul><li><h4>From Particulate processes to In-vitro Fertilization: Theory to Clinical Practice<\/h4><p>The success of In-vitro fertilization (IVF) majorly depends upon successful superovulation, defined by the number and uniformly high quality of eggs retrieved in a cycle. Currently, this step is executed using almost daily monitoring of the follicular development using ultrasound and blood tests. Although there are general guidelines for the dosage, the dose is not optimized for each patient, and overstimulation complications can occur. The cost of testing and drugs makes this stage very expensive. To overcome the shortcoming of this system, we have developed a mathematical procedure that can provide a personalized model and optimal drug treatment for each patient. Recently, we conducted clinical trials in India. The results show that the dosage predicted by using the model is 30-40% less than that suggested by the IVF doctors. The testing for patients is reduced by 72%. We also found that the number of good-quality embryos obtained using this approach was significantly higher than in current practice. This model and optimal control procedure were released in early September as a decision support tool Opt-IVF for hospitals to use in their clinical practice. So far, five hospitals have signed up to use (and are using it daily).<\/p><\/li><\/ul>\n<ul><li><h4>Instrumenting While Experimenting: An Empirical Method for Competitive Pricing at Scale<\/h4><p>We partner with a leading U.S. e-commerce retailer and develop a competitive pricing method in the context of increasing competition in online retailing. Our method allows retailers to more accurately respond to competitors' price changes at scale. First, we construct a parsimonious demand model that captures the key trade-off in competitive pricing by accounting for two types of customers heterogeneous in their \u201cprice-shopping\u201d' behavior. Next, we design and implement a large-scale randomized price experiment on over 10,000 products. Leveraging the experiment as well as the control function approach, we are able to obtain unbiased estimates of the demand model, in particular, price elasticities of both loyal and price-shopping consumers as well as the sales lift when we undercut competitors in price. Lastly, we recommend price responses by solving a constrained optimization problem which uses the estimated demand model as an input. We test this pricing method through another large-scale controlled field experiment on over 10,000 products and demonstrate significant improvements---increasing revenue by over 15% and increasing profit by over 10%.<\/p><\/li><\/ul>\n<ul><li><h4>Vaccine Equity and Occupational Health and Safety Analytics for COVID<\/h4><p>From March 2020 through March 2022 a team from the U.S. Army Engineer Research and Development Center (ERDC) was constituted to develop a suite of innovative analytics applications to describe, predict, and inform COVID-19 risks and societal implications. Two key innovations developed for FEMA and ASPR Region I included (a) a vaccine equity modeling and analysis platform, and (b) a return-to-work simulator and decision support system. For (a), and in accordance with President Biden\u2019s Executive Order 13995 (Ensuring an Equitable Pandemic Response and Recovery), ERDC\u2019s Vaccine Equity Methodology included a three-step process to evaluate, at a county, state, regional, and national level, the various equity considerations and equity gaps relative to vaccine distribution and community uptake from March 2021 through January 2022. For (b), ERDC\u2019s Workplace Micro-Exposure Model (MEM) was used to guide return-to-work decisions for emergency responders in Region 1 beginning Summer 2020. The MEM model harvested epidemiological forecast data and assessed workforce risk based on in-office participation against random-transit-events and building blueprints\/population flow. Both tools were used to guide elements of the COVID emergency response effort, promoting a safer workforce as well as more responsive and equitable vaccine distribution efforts to various underserved communities across New England.<\/p><\/li><\/ul>\n<ul><li><h4>Analytical Pipeline for Identifying Potential Sex Trafficking Victims in Commercial Sex Ad Data<\/h4><p>Sex trafficking refers to the use of force, fraud, or coercion for sexual exploitation and is facilitated by commercial sex ad websites. Each day, more than 100,000 new ads and more than 500,000 images are posted on these sites. Although ad data can provide important insights for counter-trafficking efforts, linking the large volume of ads is challenging. Additionally, scammers create ads seeking to obtain deposits via electronic payment methods. These ads do not correspond to legitimate individuals and add noise to the data-linking process. In 2020, the Institute of Data and Analytics (IDA) at The University of Alabama launched the Sex Trafficking Analytics for Network Detection and Disruption (STANDD) initiative. The STANDD team developed and maintains an analytical pipeline that utilizes novel technologies and methodologies from information systems, network science, and machine learning to remove anomalies due to scam ads, link the remaining data into groups representing individuals, and utilize these data groups for network and movement detection. Data products from this pipeline have helped law enforcement and non-profit organizations establish contact with more than 40 potential sex trafficking victims, many of whom are now connected with services to get them out of \u201cthe life.\u201d<\/p><\/li><\/ul>\n<h6>INFORMS Prize<\/h6> <p>This prize is awarded annually to the company that effectively integrates analytics into organizational decision-making, and has repeatedly applied ORMS principles in pioneering, novel and lasting ways.\u00a0 The 2023 winner will be recognized at the Edelman Gala on Monday evening and present their innovative O.R. work. on Tuesday afternoon.<\/p> <p>Previous winners include BNSF Railway, Disney, U.S. Air Force, GM, Chevron, Memorial Sloan-Kettering Cancer Center, Sasol, Jeppesen, Intel, General Electric Global Research Center, Schneider National, Air Products and Chemicals, Procter &amp; Gamble, UPS, Wayfair and other leading companies.<\/p>\n<h6>UPS George D. Smith Prize<\/h6> <p>The George D. Smith Prize is aimed at strengthening ties between academia and industry by rewarding institutions of higher education for effective and innovative preparation of students to be good practitioners of operations research. The Prize is generously underwritten by UPS. Awarded for the first time in 2012, past winners are Carnegie Mellon University, H. John Heinz III College, Sauder School of Business, University of British Columbia \u2013 Center for Operations Excellence, MIT Leaders for Global Operations, Naval Postgraduate School, and Tauber Institute for Global Operations at University of Michigan.<\/p> <p>The teams will present their work to the judges on Sunday, April 16. The Smith Prize winner will be announced at the Edelman Gala on Monday, April 17 and the 2023 winner will give their presentation on Tuesday afternoon.<\/p>","_links":{"self":[{"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/wp-json\/wp\/v2\/pages\/889","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/wp-json\/wp\/v2\/users\/1001094"}],"replies":[{"embeddable":true,"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/wp-json\/wp\/v2\/comments?post=889"}],"version-history":[{"count":32,"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/wp-json\/wp\/v2\/pages\/889\/revisions"}],"predecessor-version":[{"id":3117,"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/wp-json\/wp\/v2\/pages\/889\/revisions\/3117"}],"up":[{"embeddable":true,"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/wp-json\/wp\/v2\/pages\/396"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/wp-json\/wp\/v2\/media\/153"}],"wp:attachment":[{"href":"https:\/\/meetings.informs.org\/wordpress\/analytics2023\/wp-json\/wp\/v2\/media?parent=889"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}