{"id":361,"date":"2022-05-26T12:41:59","date_gmt":"2022-05-26T12:41:59","guid":{"rendered":"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/?page_id=361"},"modified":"2022-09-29T19:40:31","modified_gmt":"2022-09-29T19:40:31","slug":"informs-workshop-on-data-mining-decision-analytics","status":"publish","type":"page","link":"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/informs-workshop-on-data-mining-decision-analytics\/","title":{"rendered":"INFORMS 17th Workshop on Data Mining &amp; Decision Analytics"},"content":{"rendered":"<!--themify_builder_content-->\n<div id=\"themify_builder_content-361\" data-postid=\"361\" class=\"themify_builder_content themify_builder_content-361 themify_builder tf_clear\">\n                    <div  data-lazy=\"1\" class=\"module_row themify_builder_row tb_xpkq378 tb_first tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_2 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col4-2 tb_trxc379 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_cm0c44   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h2>Saturday, October 15<\/h2>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                    <div  data-lazy=\"1\" class=\"module_column tb-column col4-2 tb_rjcm103 last\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_jde3508   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <p><strong>Organized by<\/strong><\/p>\n<p><a href=\"https:\/\/sites.google.com\/view\/dmdaworkshop2021\/home\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-759 size-full\" src=\"https:\/\/meetings.informs.org\/wordpress\/anaheim2021\/files\/2021\/06\/INFORMS_DataMiningSociety_logo.jpeg\" alt=\"INFORMS Data Mining Society logo\" width=\"356\" height=\"50\"><\/a><\/p>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-lazy=\"1\" class=\"module_row themify_builder_row tb_k5rt557 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_2 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col4-3 tb_vj7i558 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_x6km631   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <p><!--HubSpot Call-to-Action Code --><span id=\"hs-cta-wrapper-6604c853-7214-41ea-abaa-7e33f3facd19\" class=\"hs-cta-wrapper\"><span id=\"hs-cta-6604c853-7214-41ea-abaa-7e33f3facd19\" class=\"hs-cta-node hs-cta-6604c853-7214-41ea-abaa-7e33f3facd19\"><!-- [if lte IE 8]><\/p>\n<div id=\"hs-cta-ie-element\"><\/div>\n<p><![endif]--><a href=\"https:\/\/cta-redirect.hubspot.com\/cta\/redirect\/3449182\/6604c853-7214-41ea-abaa-7e33f3facd19\"><img decoding=\"async\" id=\"hs-cta-img-6604c853-7214-41ea-abaa-7e33f3facd19\" class=\"hs-cta-img\" style=\"border-width: 0px;\" src=\"https:\/\/no-cache.hubspot.com\/cta\/default\/3449182\/6604c853-7214-41ea-abaa-7e33f3facd19.png\" alt=\"Submit an Abstract\"><\/a><\/span><script charset=\"utf-8\" src=\"https:\/\/js.hscta.net\/cta\/current.js\"><\/script><script type=\"text\/javascript\"> hbspt.cta.load(3449182, '6604c853-7214-41ea-abaa-7e33f3facd19', {\"useNewLoader\":\"true\",\"region\":\"na1\"}); <\/script><\/span><!-- end HubSpot Call-to-Action Code --><\/p>\n<p>The Data Mining Society of INFORMS is organizing the\u00a0<a href=\"https:\/\/sites.google.com\/view\/dmdaworkshop2022\/home\">17th INFORMS Workshop on Data Mining and Decision Analytics<\/a> in conjunction with 2022 INFORMS Annual Meeting. You are cordially invited to join us and share your recent research work with peers from data mining, decision analytics, and artificial intelligence.<\/p>\n<p>To participate, a full paper must be submitted before the deadline for consideration. The workshop committee also announces the best paper competition in both theoretical and applied research tracks. All accepted papers are automatically considered for the best paper competition in the chosen track.<\/p>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                    <div  data-lazy=\"1\" class=\"module_column tb-column col4-1 tb_lpot559 last\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_g0u7225   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <p><strong><span id=\"hs-cta-wrapper-6604c853-7214-41ea-abaa-7e33f3facd19\" class=\"hs-cta-wrapper\"><a href=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/09\/DMDA-2022-Workshop-Schedule_final-v2.pdf\">Click here<\/a> to view the full DMDA Workshop schedule.<\/span><\/strong><!-- end HubSpot Call-to-Action Code --><\/p>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-anchor=\"speakers\" data-lazy=\"1\" class=\"module_row themify_builder_row tb_has_section tb_section-speakers tb_0679217 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_2 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col4-3 tb_xqhz218 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_r8mb710   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h2>Registration<\/h2>\n<p>Students and retirees: $75<br>Professionals: $150<\/p>\n<p><a href=\"https:\/\/myaccount.informs.org\/s\/community-event?id=a1Y1U000004VqNpUAK\">Register for this event<\/a><\/p>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                    <div  data-lazy=\"1\" class=\"module_column tb-column col4-1 tb_mjyq219 last\">\n                            <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-lazy=\"1\" class=\"module_row themify_builder_row tb_kffw163 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_2 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col4-3 tb_5wj4165 first\">\n                            <div  data-lazy=\"1\" class=\"module_subrow themify_builder_sub_row tf_w col_align_top tb_col_count_2 tb_an0w39\">\n                <div  data-lazy=\"1\" class=\"module_column sub_column col2-1 tb_mdzy40 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_chcj173   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h2>Topics of Interest<\/h2>\n<p>Include, but are not limited to:<\/p>\n<ul>\n<li>Analytics in Social Media &amp; Finance<\/li>\n<li>Anomaly Detection<\/li>\n<li>Bayesian Data Analytics<\/li>\n<li>Causal Mining (Inference)<\/li>\n<li>Data Science and Artificial Intelligence<\/li>\n<li>Deep Learning<\/li>\n<li>Emerging Data Analytics in Industrial Applications<\/li>\n<li>Ethics and Security in Data Mining<\/li>\n<li>Fairness in Machine Learning<\/li>\n<li>Healthcare Analytics<\/li>\n<li>Interpretable Data Mining<\/li>\n<li>Large-scale Data Analytics and Big Data<\/li>\n<li>Longitudinal Data Analysis<\/li>\n<li>Network Analysis and Graph Mining<\/li>\n<li>Privacy &amp; Fairness in Data Science<\/li>\n<li>Reinforcement Learning<\/li>\n<li>Reliability &amp; Maintenance<\/li>\n<li>Simulation\/Optimization in Data Analytics<\/li>\n<li>Text Mining &amp; Natural Language Processing<\/li>\n<li>Visual Analytics<\/li>\n<li>Web Analytics\/Web Mining<\/li>\n<\/ul>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                    <div  data-lazy=\"1\" class=\"module_column sub_column col2-1 tb_qlff40 last\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_v9no442   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h2>Timeline<\/h2>\n<p><strong>May 16:<\/strong> Paper submission begins<br><strong>August 8:<\/strong> Paper submission closes<br><strong>September 1:<\/strong>\u00a0Final review decision<br><strong>September 14:<\/strong> Workshop on Data Mining and Decision Analytics registration deadline<\/p>    <\/div>\n<\/div>\n<!-- \/module text --><!-- module text -->\n<div  class=\"module module-text tb_ql8n820   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h2>DM Workshop Co-chairs<\/h2>\n<p>Nathan Gaw, Air Force Institute of Technology\u00a0<br>Eyyub Kibis, Montclair State University<br>Feng Liu, Stevens Institute of Technology<br><br><\/p>\n<h2>DM Workshop <br>Management Committee<\/h2>\n<p>Paul Brooks, Virginia Commonwealth University<br>Matthew Lanham, Purdue University<br>Ramin Moghaddass, University of Miami<br>Asil Oztekin, University of Massachusetts Lowell<br>Cynthia Rudin, Duke University<br>George Runger, Arizona State University<br>Onur Seref, Virginia Tech<br>Durai Sundaramoorthi, Washington University<\/p>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                    <\/div>\n        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src=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/Feliciano-School-of-Business.jpg\" class=\"wp-post-image wp-image-1454\" title=\"Feliciano-School-of-Business\" alt=\"Feliciano School of Business logo\">        <\/a>\n    \n        <\/div>\n    <!-- \/image-wrap -->\n    \n        <\/div>\n<!-- \/module image -->        <\/div>\n                    <div  data-lazy=\"1\" class=\"module_column sub_column col4-1 tb_s1dx94 last\">\n                    <!-- module image -->\n<div  class=\"module module-image tb_qm3x39 image-center   tf_mw\" data-lazy=\"1\">\n        <div class=\"image-wrap tf_rel tf_mw\">\n            <a href=\"https:\/\/pubsonline.informs.org\/journal\/ijds\">\n                   <img decoding=\"async\" src=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/ijds.png\" width=\"150\" class=\"wp-post-image wp-image-1528\" title=\"ijds\" alt=\"INFORMS Journal on Data Science logo\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/ijds.png 200w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/ijds-150x150.png 150w\" sizes=\"(max-width: 200px) 100vw, 200px\" \/>        <\/a>\n    \n        <\/div>\n    <!-- \/image-wrap -->\n    \n        <\/div>\n<!-- \/module image -->        <\/div>\n                    <\/div>\n                <div  data-lazy=\"1\" class=\"module_subrow themify_builder_sub_row tf_w col_align_middle tb_col_count_4 tb_garv225\">\n                <div  data-lazy=\"1\" class=\"module_column sub_column col4-1 tb_rova225 first\">\n                    <!-- module image -->\n<div  class=\"module module-image tb_htpi452 image-center   tf_mw\" data-lazy=\"1\">\n        <div class=\"image-wrap tf_rel tf_mw\">\n            <a href=\"https:\/\/krannert.purdue.edu\/home.php\">\n                   <img decoding=\"async\" src=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/PURDUE1Krannert-School-of-Management_V-Full-RGB.jpg\" width=\"150\" class=\"wp-post-image wp-image-1439\" title=\"PURDUE1Krannert-School-of-Management_V-Full-RGB\" alt=\"Krannert School of Management logo\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/PURDUE1Krannert-School-of-Management_V-Full-RGB.jpg 525w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/PURDUE1Krannert-School-of-Management_V-Full-RGB-300x247.jpg 300w\" sizes=\"(max-width: 525px) 100vw, 525px\" \/>        <\/a>\n    \n        <\/div>\n    <!-- \/image-wrap -->\n    \n        <\/div>\n<!-- \/module image -->        <\/div>\n                    <div  data-lazy=\"1\" class=\"module_column sub_column col4-1 tb_sihc226\">\n                    <!-- module image -->\n<div  class=\"module module-image tb_8vtp76 image-center   tf_mw\" data-lazy=\"1\">\n        <div class=\"image-wrap tf_rel tf_mw\">\n            <a href=\"https:\/\/www.sas.com\/en_us\/home.html\">\n                   <img decoding=\"async\" src=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/sas-logo-midnight.jpg\" width=\"175\" class=\"wp-post-image wp-image-1441\" title=\"sas-logo-midnight\" alt=\"SAS logo\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/sas-logo-midnight.jpg 518w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/sas-logo-midnight-300x124.jpg 300w\" sizes=\"(max-width: 518px) 100vw, 518px\" \/>        <\/a>\n    \n        <\/div>\n    <!-- \/image-wrap -->\n    \n        <\/div>\n<!-- \/module image -->        <\/div>\n                    <div  data-lazy=\"1\" class=\"module_column sub_column col4-1 tb_4n40226\">\n                    <!-- module image -->\n<div  class=\"module module-image tb_gs0p717 image-center   tf_mw\" data-lazy=\"1\">\n        <div class=\"image-wrap tf_rel tf_mw\">\n            <a href=\"https:\/\/www.stevens.edu\/school-systems-enterprises\">\n                   <img loading=\"lazy\" decoding=\"async\" width=\"210\" height=\"300\" src=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/Stevens-SSE-logo-RGB_4C-210x300.png\" class=\"wp-post-image wp-image-1442\" title=\"Stevens-SSE-logo-RGB_4C\" alt=\"Stevens School of Systems &amp; Enterprises logo\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/Stevens-SSE-logo-RGB_4C-210x300.png 210w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/Stevens-SSE-logo-RGB_4C-716x1024.png 716w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/Stevens-SSE-logo-RGB_4C-768x1098.png 768w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/Stevens-SSE-logo-RGB_4C-1074x1536.png 1074w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/Stevens-SSE-logo-RGB_4C-1433x2048.png 1433w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/Stevens-SSE-logo-RGB_4C.png 1760w\" sizes=\"auto, (max-width: 210px) 100vw, 210px\" \/>        <\/a>\n    \n        <\/div>\n    <!-- \/image-wrap -->\n    \n        <\/div>\n<!-- \/module image -->        <\/div>\n                    <div  data-lazy=\"1\" class=\"module_column sub_column col4-1 tb_ag96226 last\">\n                    <!-- module image -->\n<div  class=\"module module-image tb_09ja86 image-center   tf_mw\" data-lazy=\"1\">\n        <div class=\"image-wrap tf_rel tf_mw\">\n            <a href=\"https:\/\/www.uml.edu\/msb\/\">\n                   <img decoding=\"async\" src=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/manning_school_indentifier_4color-scaled.jpg\" height=\"200\" class=\"wp-post-image wp-image-1440\" title=\"vertical_logo_with_tag\" alt=\"UMass Manning School logo\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/manning_school_indentifier_4color-scaled.jpg 2560w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/manning_school_indentifier_4color-300x98.jpg 300w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/manning_school_indentifier_4color-1024x333.jpg 1024w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/manning_school_indentifier_4color-768x250.jpg 768w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/manning_school_indentifier_4color-1536x500.jpg 1536w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/manning_school_indentifier_4color-2048x667.jpg 2048w\" sizes=\"(max-width: 2560px) 100vw, 2560px\" \/>        <\/a>\n    \n        <\/div>\n    <!-- \/image-wrap -->\n    \n        <\/div>\n<!-- \/module image -->        <\/div>\n                    <\/div>\n                <\/div>\n                    <div  data-lazy=\"1\" class=\"module_column tb-column col4-1 tb_so65165 last\">\n                            <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-lazy=\"1\" class=\"module_row themify_builder_row tb_jia2773 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_2 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col4-3 tb_9sa9774 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_clo1120   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h2>Papers submission guideline<\/h2>\n<ul>\n<li>Maximum of 10 pages (including abstract, tables, figures, and references)<\/li>\n<li>Single-spacing and 11-point font with one-inch margins on four sides<\/li>\n<li>Papers must be submitted via the provided submission link (TBD). Late submission will not be considered for further review.<\/li>\n<li><strong>Copyright: <\/strong>The DM workshop will not retain the copyrights on the papers. Authors are free to submit their papers to other outlets.<\/li>\n<\/ul>    <\/div>\n<\/div>\n<!-- \/module text --><!-- module text -->\n<div  class=\"module module-text tb_32bb250   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h2><a href=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/09\/DMDA-2022-Workshop-Schedule_final-v2.pdf\">Click here<\/a> to view the full DMDA Workshop schedule.<\/h2>\n<h2>Academic Keynote<\/h2>\n<p><img decoding=\"async\" style=\"float: right; width: 20%; margin: 0 0 12px 12px;\" src=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/03\/CynthiaNov2021_featured-speaker_2022-INFORMS-Annual-Meeting.jpg\"><\/p>\n<h3><em>Understanding How Dimension Reduction Tools Work<\/em><\/h3>\n<p><strong>Cynthia Rudin, Professor of Computer Science, Duke University<\/strong><\/p>\n<p>Dimension reduction (DR) techniques such as t-SNE, UMAP, and TriMap have demonstrated impressive visualization performance on many real world datasets. They are useful for understanding data and trustworthy decision-making, particularly for biological data. One tension that has always faced these methods is the trade-off between preservation of global structure and preservation of local structure: past methods can either handle one or the other, but not both. In this work, our main goal is to understand what aspects of DR methods are important for preserving both local and global structure: it is difficult to design a better method without a true understanding of the choices we make in our algorithms and their empirical impact on the lower-dimensional embeddings they produce. Towards the goal of local structure preservation, we provide several useful design principles for DR loss functions based on our new understanding of the mechanisms behind successful DR methods. Towards the goal of global structure preservation, our analysis illuminates that the choice of which components to preserve is important. We leverage these insights to design a new algorithm for DR, called Pairwise Controlled Manifold Approximation Projection (PaCMAP), which preserves both local and global structure. Our work provides several unexpected insights into what design choices both to make and avoid when constructing DR algorithms.<\/p>\n<p>The following papers will be discussed:<\/p>\n<ul>\n<li>Yingfan Wang, Haiyang Huang, Cynthia Rudin, Yaron Shaposhnik Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMAP, and PaCMAP for Data Visualization Journal of Machine Learning Research (JMLR), 2021 <a href=\"https:\/\/jmlr.org\/papers\/v22\/20-1061.html\" data-feathr-click-track=\"true\">https:\/\/jmlr.org\/papers\/v22\/20-1061.html<\/a><\/li>\n<li>Haiyang Huang, Yingfan Wang, Cynthia Rudin, and Edward P. Browne Towards a Comprehensive Evaluation of Dimension Reduction Methods for Transcriptomic Data Visualization Communications Biology (Nature), 2022. <a href=\"https:\/\/www.nature.com\/articles\/s42003-022-03628-x\" data-feathr-click-track=\"true\">https:\/\/www.nature.com\/articles\/s42003-022-03628-x<\/a><\/li>\n<\/ul>\n<h4>About Cynthia Rudin<\/h4>\n<p>Cynthia Rudin is a professor of computer science, electrical and computer engineering, statistical science, mathematics, and biostatistics &amp; bioinformatics at Duke University, and directs the Interpretable Machine Learning Lab. Previously, Prof. Rudin held positions at MIT, Columbia, and NYU. She holds an undergraduate degree from the University at Buffalo, and a Ph.D. from Princeton University. She is the recipient of the 2022 Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity from the Association for the Advancement of Artificial Intelligence (AAAI). This award is the most prestigious award in the field of artificial intelligence. Similar only to world-renowned recognitions, such as the Nobel Prize and the Turing Award, it carries a monetary reward at the million-dollar level. Prof. Rudin is also a three-time winner of the INFORMS Innovative Applications in Analytics Award, was named as one of the &#8220;Top 40 Under 40&#8221; by <i>Poets and Quants<\/i> in 2015, and was named by <i>Businessinsider.com<\/i> as one of the 12 most impressive professors at MIT in 2015, and is a 2022 Guggenheim Fellow. She is a fellow of the American Statistical Association, the Institute of Mathematical Statistics, and AAAI.<\/p>\n<p>Prof. Rudin is past chair of both the INFORMS Data Mining Section and the Statistical Learning and Data Science Section of the American Statistical Association. She has also served on committees for DARPA, the National Institute of Justice, AAAI, and ACM SIGKDD. She has served on several committees for the National Academies of Sciences, Engineering and Medicine, including the Committee on Applied and Theoretical Statistics, the Committee on Law and Justice, the Committee on Analytic Research Foundations for the Next-Generation Electric Grid, and the Committee on Facial Recognition Technology.\u00a0 She has given keynote\/invited talks at several conferences including KDD (twice), AISTATS, SDM, Machine Learning in Healthcare (MLHC), Fairness, Accountability and Transparency in Machine Learning (FAT-ML), ECML-PKDD, and the Nobel Conference. Her work has been featured in news outlets including the <i>NY Times<\/i>, <i>Washington Post<\/i>, <i>Wall Street Journal<\/i>, the <i>Boston Globe<\/i>, <i>Businessweek<\/i>, and <i>NPR<\/i>.<\/p>    <\/div>\n<\/div>\n<!-- \/module text --><!-- module text -->\n<div  class=\"module module-text tb_52qg526   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h2>Industry Keynote<\/h2>\n<h3><em><strong>Forecasting 2.0 &#8211; New Ways to See Around Corners<\/strong><\/em><\/h3>\n<p><strong>Kirk Borne, Chief Science Officer, DataPrime, Inc.<\/strong><\/p>\n<p>Predictive modeling and predictive analytics are among the most common industry and business applications of data science and machine learning. I will first review some interesting (amusing and\/or impactful) failure cases of traditional forecasting and predictive modeling. These include traditional autoregressive time series forecasting, which I refer to as &#8220;forecasting 1.0&#8221;. I will then introduce some approaches to predictive analytics that are different from standard forecasting 1.0. These novel &#8220;forecasting 2.0&#8221; methods are more contextual, exploiting the insights that come from external contextual data sources. Context-based methods are therefore more beneficial than autoregressive methods in the current data-intensive era in which data sources and data formats extend far beyond traditional time series. Contextual analytics approaches also enable opportunities for prescriptive analytics (causal analysis and causality discovery), which are similar to O.R., but again these go beyond traditional methods of optimization through the application of data from multiple diverse sensors, including the exploding growth of data sources in the IoT (Internet of Things). In this environment, I envision the IoT as the &#8220;Internet of Context&#8221; enabling &#8220;Forecasting-as-a-Service&#8221; (FaaS). Several examples and algorithm categories will be presented to illustrate diverse forecasting 2.0 applications.<\/p>\n<h4>About Kirk Borne<\/h4>\n<p>Dr. Kirk Borne is the Chief Science Officer at AI startup DataPrime Inc and is the owner and founder of his own freelance consulting business Data Leadership Group LLC. He is a career data professional, data science leader, and research astrophysicist. From 2015 to 2021, he was Principal Data Scientist, Data Science Fellow, and Executive Advisor at management consulting firm Booz Allen Hamilton. Previously, Kirk was professor of Astrophysics and Computational Science at George Mason University for 12 years where he co-founded the world&#8217;s first data science undergraduate degree program, and where did research and taught data science at the graduate and undergraduate levels. Before that, he spent 20 years supporting data systems activities for NASA space science missions, including a role as NASA&#8217;s Data Archive Project Scientist for the Hubble Telescope. He has a Ph.D. in astronomy from Caltech. He is an elected Fellow of the International Astrostatistics Association for his contributions to big data research in astronomy. In 2020, he was elected a Fellow of the American Astronomical Society for lifelong contributions to the field of astronomy. Since 2013, he has been identified as a top worldwide influencer on social media, promoting analytics, data science, machine learning, AI, and data literacy for all. He is currently advisor to several businesses and educational institutions. He is most recently exploring the synergies and innovation opportunities at the convergence of multiple emerging digital technologies: IoT, the metaverse, digital twins, intelligent edge, immersive realities, autonomous systems, and more!<\/p>    <\/div>\n<\/div>\n<!-- \/module text --><!-- module text -->\n<div  class=\"module module-text tb_gra5402   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h2>Joint Panel Discussion with Quality Statistics and Reliability (QSR) Workshop: <em>Fairness and Interpretability in AI\/ML<\/em><\/h2>\n<p style=\"margin: 12.0pt 0in 0in 0in;\"><span style=\"font-family: 'Arial',sans-serif; color: black;\">Many black box machine learning models are being used for high-stakes decisions in healthcare, manufacturing, social media, and various other fields. As a result, there is high susceptibility to bias toward different population demographics as well as poor interpretability in understanding why models make a variety of predictions. This panel will cover recent topics and developments across a number of applications for which fairness and interpretability of machine learning models are crucial.<\/span><\/p>\n<p><strong>Panelists:<\/strong><\/p>\n<p style=\"margin: 12.0pt 0in 0in 0in;\"><b><span style=\"font-family: 'Arial',sans-serif; color: black;\">Dr. Cynthia Rudin<\/span><\/b><span style=\"font-family: 'Arial',sans-serif; color: black;\">\u00a0is a professor of computer science and engineering at Duke University. She directs the Interpretable Machine Learning Lab, and her goal is to design predictive models that people can understand. Her lab applies machine learning in many areas, such as healthcare, criminal justice, and energy reliability. She holds degrees from the University at Buffalo and Princeton. She is the recipient of the 2022 Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity from the Association for the Advancement of Artificial Intelligence (the \u201cNobel Prize of AI\u201d). She received a 2022 Guggenheim fellowship, and is a fellow of the American Statistical Association, the Institute of Mathematical Statistics, and the Association for the Advancement of Artificial Intelligence. Her work has been featured in many news outlets including the NY Times, Washington Post, Wall Street Journal, and Boston Globe.<\/span><\/p>\n<p style=\"box-sizing: border-box; font-variant-ligatures: none; outline: none; text-decoration-line: inherit; white-space: pre-wrap; margin: 12.0pt 0in 0in 0in;\"><b><span style=\"font-family: 'Arial',sans-serif; color: #222222;\">Dr. Na Zou<\/span><\/b><span style=\"font-family: 'Arial',sans-serif; color: #222222;\"> is currently a Corrie &amp; Jim Furber \u201964 assistant professor in Engineering Technology and Industrial Distribution at Texas A&amp;M University. She was an Instructional Assistant Professor in Industrial and Systems Engineering at Texas A&amp;M University from 2016 to 2020. She holds both a Ph.D. in Industrial Engineering and a MSE in Civil, Environmental and Sustainable Engineering from Arizona State University. Her research focuses on fair and interpretable machine learning, transfer learning, network modeling and inference, supported by NSF and industrial sponsors. The research projects have resulted in publications at prestigious journals such as Technometrics, IISE Transactions and ACM Transactions, including one Best Paper Finalist and one Best Student Paper Finalist at INFORMS QSR section and two featured articles at ISE Magazine. She was the recipient of IEEE Irv Kaufman Award and Texas A&amp;M Institute of Data Science Career Initiation Fellow.<\/span><\/p>\n<p style=\"margin-top: 0in; text-align: justify; box-sizing: border-box; outline: none; text-decoration-line: inherit;\"><b><span style=\"font-family: 'Arial',sans-serif; color: #444444;\"><br>Dr. Kinjal\u00a0<span class=\"gmail-il\">Basu<\/span><\/span><\/b><span style=\"font-family: 'Arial',sans-serif; color: #444444;\">\u00a0is currently a Senior Staff Software Engineer in\u00a0LinkedIn&#8217;s\u00a0AI team, primarily focusing on Responsible AI, encompassing challenging problems in Fairness, Explainability and Privacy. He leads several efforts that can be applied to different product applications towards making LinkedIn a responsible and equitable platform. Throughout the years, Dr.\u00a0<span class=\"gmail-il\">Basu<\/span>\u00a0has worked on a variety of problems and on various product applications. His focus has ranged from developing prediction models for complex recommender systems powering News Feed Ranking and People You May Know (PYMK) to extreme large-scale optimization problems trying to solve complex matching and allocation problems. He has\u00a0been the chief architect and designer for the AutoML library used internally by various teams such as Feed, Notifications, Ads and PYMK. Dr.\u00a0<span class=\"gmail-il\">Basu<\/span> has also worked towards developing accurate causal estimates in the presence of network interference.<\/span><\/p>    <\/div>\n<\/div>\n<!-- \/module text --><!-- module text -->\n<div  class=\"module module-text tb_tj41854   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h2>Poster Competition<\/h2>\n<p>Are you a student or practitioner working on applied work in the fields of data mining or data science? Click <a href=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/09\/2022-INFORMS-DMDA-Poster-Competition-Flyer.pdf\">here<\/a> for more information on the Poster Competition.\u00a0<\/p>    <\/div>\n<\/div>\n<!-- \/module text --><!-- module text -->\n<div  class=\"module module-text tb_cnvx380   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h2>Previous Workshops<\/h2>\n<p><a href=\"https:\/\/meetings.informs.org\/wordpress\/anaheim2021\/informs-workshop-on-data-mining-decision-analytics\/\">16th Virtual INFORMS Workshop on Data Mining and Decision Analytics<\/a><\/p>\n<p><a href=\"https:\/\/www.google.com\/url?q=https%3A%2F%2Fsites.google.com%2Fview%2Fdmdaworkshop2020%2Fhome%3Fauthuser%3D2&amp;sa=D&amp;sntz=1&amp;usg=AFQjCNG34lapMmIt5M7VWyOVSIYoHG6Srw\">1<\/a><a href=\"https:\/\/www.google.com\/url?q=https%3A%2F%2Fsites.google.com%2Fview%2Fdmdaworkshop2020%2Fhome%3Fauthuser%3D2&amp;sa=D&amp;sntz=1&amp;usg=AFQjCNG34lapMmIt5M7VWyOVSIYoHG6Srw\">5<\/a><a href=\"https:\/\/www.google.com\/url?q=https%3A%2F%2Fsites.google.com%2Fview%2Fdmdaworkshop2020%2Fhome%3Fauthuser%3D2&amp;sa=D&amp;sntz=1&amp;usg=AFQjCNG34lapMmIt5M7VWyOVSIYoHG6Srw\">th Virtual INFORMS Workshop on Data Mining and Decision Analytics<\/a><\/p>\n<p><a href=\"https:\/\/www.google.com\/url?q=https%3A%2F%2Fsites.google.com%2Fview%2Fdmdaworkshop%2Fhome&amp;sa=D&amp;sntz=1&amp;usg=AFQjCNGzdttHfIIScET1lfByzVfd2gCp0w\">14th INFORMS Workshop on Data Mining and Decision Analytics<\/a><\/p>\n<p><a href=\"http:\/\/www.google.com\/url?q=http%3A%2F%2Fmeetings2.informs.org%2Fwordpress%2Fphoenix2018%2Fpre-meeting%2F%23data-mining&amp;sa=D&amp;sntz=1&amp;usg=AFQjCNHca6nTCtUf3K3NISyxJ0kbqQlp8A\">13th INFORMS Workshop on Data Mining and Decision Analytics<\/a><\/p>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                    <div  data-lazy=\"1\" class=\"module_column tb-column col4-1 tb_oqcl774 last\">\n                            <\/div>\n                        <\/div>\n        <\/div>\n        <\/div>\n<!--\/themify_builder_content-->","protected":false},"excerpt":{"rendered":"<p>Saturday, October 15 Organized by The Data Mining Society of INFORMS is organizing the\u00a017th INFORMS Workshop on Data Mining and Decision Analytics in conjunction with 2022 INFORMS Annual Meeting. You are cordially invited to join us and share your recent research work with peers from data mining, decision analytics, and artificial intelligence. To participate, a [&hellip;]<\/p>\n","protected":false},"author":1001133,"featured_media":7,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"content-type":"","footnotes":""},"class_list":["post-361","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 17th Workshop on Data Mining &amp; Decision Analytics - 2022 INFORMS Annual Meeting<\/title>\n<meta name=\"description\" content=\"The Data Mining Section of INFORMS is organizing the 17th INFORMS Workshop on Data Mining and Decision Analytics in conjunction with the 2022 INFORMS Annual Meeting.\" \/>\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\/indianapolis2022\/informs-workshop-on-data-mining-decision-analytics\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"INFORMS 17th Workshop on Data Mining &amp; 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Decision Analytics - 2022 INFORMS Annual Meeting","isPartOf":{"@id":"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/#website"},"primaryImageOfPage":{"@id":"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/informs-workshop-on-data-mining-decision-analytics\/#primaryimage"},"image":{"@id":"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/informs-workshop-on-data-mining-decision-analytics\/#primaryimage"},"thumbnailUrl":"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2021\/08\/2022_INFORMS_Annual_Meeting_logo_web.png","datePublished":"2022-05-26T12:41:59+00:00","dateModified":"2022-09-29T19:40:31+00:00","description":"The Data Mining Section of INFORMS is organizing the 17th INFORMS Workshop on Data Mining and Decision Analytics in conjunction with the 2022 INFORMS Annual Meeting.","breadcrumb":{"@id":"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/informs-workshop-on-data-mining-decision-analytics\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/informs-workshop-on-data-mining-decision-analytics\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/informs-workshop-on-data-mining-decision-analytics\/#primaryimage","url":"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2021\/08\/2022_INFORMS_Annual_Meeting_logo_web.png","contentUrl":"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2021\/08\/2022_INFORMS_Annual_Meeting_logo_web.png","width":600,"height":361},{"@type":"BreadcrumbList","@id":"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/informs-workshop-on-data-mining-decision-analytics\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/"},{"@type":"ListItem","position":2,"name":"INFORMS 17th Workshop on Data Mining &amp; Decision Analytics"}]},{"@type":"WebSite","@id":"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/#website","url":"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/","name":"2022 INFORMS Annual Meeting","description":"October 16-19, 2022 | Indianapolis, IN","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"}]}},"builder_content":"<h2>Saturday, October 15<\/h2>\n<p><strong>Organized by<\/strong><\/p> <p><a href=\"https:\/\/sites.google.com\/view\/dmdaworkshop2021\/home\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/meetings.informs.org\/wordpress\/anaheim2021\/files\/2021\/06\/INFORMS_DataMiningSociety_logo.jpeg\" alt=\"INFORMS Data Mining Society logo\" width=\"356\" height=\"50\"><\/a><\/p>\n<p><a href=\"https:\/\/cta-redirect.hubspot.com\/cta\/redirect\/3449182\/6604c853-7214-41ea-abaa-7e33f3facd19\"><img decoding=\"async\" id=\"hs-cta-img-6604c853-7214-41ea-abaa-7e33f3facd19\" style=\"border-width: 0px;\" src=\"https:\/\/no-cache.hubspot.com\/cta\/default\/3449182\/6604c853-7214-41ea-abaa-7e33f3facd19.png\" alt=\"Submit an Abstract\"><\/a><\/p> <p>The Data Mining Society of INFORMS is organizing the\u00a0<a href=\"https:\/\/sites.google.com\/view\/dmdaworkshop2022\/home\">17th INFORMS Workshop on Data Mining and Decision Analytics<\/a> in conjunction with 2022 INFORMS Annual Meeting. You are cordially invited to join us and share your recent research work with peers from data mining, decision analytics, and artificial intelligence.<\/p> <p>To participate, a full paper must be submitted before the deadline for consideration. The workshop committee also announces the best paper competition in both theoretical and applied research tracks. All accepted papers are automatically considered for the best paper competition in the chosen track.<\/p>\n<p><strong><a href=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/09\/DMDA-2022-Workshop-Schedule_final-v2.pdf\">Click here<\/a> to view the full DMDA Workshop schedule.<\/strong><\/p>\n<h2>Registration<\/h2> <p>Students and retirees: $75<br>Professionals: $150<\/p> <p><a href=\"https:\/\/myaccount.informs.org\/s\/community-event?id=a1Y1U000004VqNpUAK\">Register for this event<\/a><\/p>\n<h2>Topics of Interest<\/h2> <p>Include, but are not limited to:<\/p> <ul> <li>Analytics in Social Media &amp; Finance<\/li> <li>Anomaly Detection<\/li> <li>Bayesian Data Analytics<\/li> <li>Causal Mining (Inference)<\/li> <li>Data Science and Artificial Intelligence<\/li> <li>Deep Learning<\/li> <li>Emerging Data Analytics in Industrial Applications<\/li> <li>Ethics and Security in Data Mining<\/li> <li>Fairness in Machine Learning<\/li> <li>Healthcare Analytics<\/li> <li>Interpretable Data Mining<\/li> <li>Large-scale Data Analytics and Big Data<\/li> <li>Longitudinal Data Analysis<\/li> <li>Network Analysis and Graph Mining<\/li> <li>Privacy &amp; Fairness in Data Science<\/li> <li>Reinforcement Learning<\/li> <li>Reliability &amp; Maintenance<\/li> <li>Simulation\/Optimization in Data Analytics<\/li> <li>Text Mining &amp; Natural Language Processing<\/li> <li>Visual Analytics<\/li> <li>Web Analytics\/Web Mining<\/li> <\/ul>\n<h2>Timeline<\/h2> <p><strong>May 16:<\/strong> Paper submission begins<br><strong>August 8:<\/strong> Paper submission closes<br><strong>September 1:<\/strong>\u00a0Final review decision<br><strong>September 14:<\/strong> Workshop on Data Mining and Decision Analytics registration deadline<\/p>\n<h2>DM Workshop Co-chairs<\/h2> <p>Nathan Gaw, Air Force Institute of Technology\u00a0<br>Eyyub Kibis, Montclair State University<br>Feng Liu, Stevens Institute of Technology<br><br><\/p> <h2>DM Workshop <br>Management Committee<\/h2> <p>Paul Brooks, Virginia Commonwealth University<br>Matthew Lanham, Purdue University<br>Ramin Moghaddass, University of Miami<br>Asil Oztekin, University of Massachusetts Lowell<br>Cynthia Rudin, Duke University<br>George Runger, Arizona State University<br>Onur Seref, Virginia Tech<br>Durai Sundaramoorthi, Washington University<\/p>\n<h2>Thank You to Our Sponsors<\/h2>\n<a href=\"http:\/\/www.afitfoundation.org\"> <img src=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/AFITFoundation.png\" title=\"AFITFoundation\" alt=\"AFITF Foundation logo\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/AFITFoundation.png 480w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/AFITFoundation-300x42.png 300w\" sizes=\"(max-width: 480px) 100vw, 480px\" \/> <\/a>\n<a href=\"https:\/\/tippie.uiowa.edu\"> <img src=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/Tippie-Business-Analytics-LockupStacked-RGB.jpg\" title=\"Tippie-Business-Analytics-LockupStacked-RGB\" alt=\"Tippie School of Business logo\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/Tippie-Business-Analytics-LockupStacked-RGB.jpg 433w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/Tippie-Business-Analytics-LockupStacked-RGB-300x143.jpg 300w\" sizes=\"(max-width: 433px) 100vw, 433px\" \/> <\/a>\n<a href=\"https:\/\/business.montclair.edu\"> <img src=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/Feliciano-School-of-Business.jpg\" title=\"Feliciano-School-of-Business\" alt=\"Feliciano School of Business logo\"> <\/a>\n<a href=\"https:\/\/pubsonline.informs.org\/journal\/ijds\"> <img src=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/ijds.png\" width=\"150\" title=\"ijds\" alt=\"INFORMS Journal on Data Science logo\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/ijds.png 200w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/ijds-150x150.png 150w\" sizes=\"(max-width: 200px) 100vw, 200px\" \/> <\/a>\n<a href=\"https:\/\/krannert.purdue.edu\/home.php\"> <img src=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/PURDUE1Krannert-School-of-Management_V-Full-RGB.jpg\" width=\"150\" title=\"PURDUE1Krannert-School-of-Management_V-Full-RGB\" alt=\"Krannert School of Management logo\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/PURDUE1Krannert-School-of-Management_V-Full-RGB.jpg 525w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/PURDUE1Krannert-School-of-Management_V-Full-RGB-300x247.jpg 300w\" sizes=\"(max-width: 525px) 100vw, 525px\" \/> <\/a>\n<a href=\"https:\/\/www.sas.com\/en_us\/home.html\"> <img src=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/sas-logo-midnight.jpg\" width=\"175\" title=\"sas-logo-midnight\" alt=\"SAS logo\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/sas-logo-midnight.jpg 518w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/sas-logo-midnight-300x124.jpg 300w\" sizes=\"(max-width: 518px) 100vw, 518px\" \/> <\/a>\n<a href=\"https:\/\/www.stevens.edu\/school-systems-enterprises\"> <img src=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/Stevens-SSE-logo-RGB_4C-210x300.png\" title=\"Stevens-SSE-logo-RGB_4C\" alt=\"Stevens School of Systems &amp; Enterprises logo\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/Stevens-SSE-logo-RGB_4C-210x300.png 210w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/Stevens-SSE-logo-RGB_4C-716x1024.png 716w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/Stevens-SSE-logo-RGB_4C-768x1098.png 768w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/Stevens-SSE-logo-RGB_4C-1074x1536.png 1074w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/Stevens-SSE-logo-RGB_4C-1433x2048.png 1433w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/Stevens-SSE-logo-RGB_4C.png 1760w\" sizes=\"(max-width: 210px) 100vw, 210px\" \/> <\/a>\n<a href=\"https:\/\/www.uml.edu\/msb\/\"> <img src=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/manning_school_indentifier_4color-scaled.jpg\" height=\"200\" title=\"vertical_logo_with_tag\" alt=\"UMass Manning School logo\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/manning_school_indentifier_4color-scaled.jpg 2560w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/manning_school_indentifier_4color-300x98.jpg 300w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/manning_school_indentifier_4color-1024x333.jpg 1024w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/manning_school_indentifier_4color-768x250.jpg 768w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/manning_school_indentifier_4color-1536x500.jpg 1536w, https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/08\/manning_school_indentifier_4color-2048x667.jpg 2048w\" sizes=\"(max-width: 2560px) 100vw, 2560px\" \/> <\/a>\n<h2>Papers submission guideline<\/h2> <ul> <li>Maximum of 10 pages (including abstract, tables, figures, and references)<\/li> <li>Single-spacing and 11-point font with one-inch margins on four sides<\/li> <li>Papers must be submitted via the provided submission link (TBD). Late submission will not be considered for further review.<\/li> <li><strong>Copyright: <\/strong>The DM workshop will not retain the copyrights on the papers. Authors are free to submit their papers to other outlets.<\/li> <\/ul>\n<h2><a href=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/09\/DMDA-2022-Workshop-Schedule_final-v2.pdf\">Click here<\/a> to view the full DMDA Workshop schedule.<\/h2> <h2>Academic Keynote<\/h2> <p><img decoding=\"async\" style=\"float: right; width: 20%; margin: 0 0 12px 12px;\" src=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/03\/CynthiaNov2021_featured-speaker_2022-INFORMS-Annual-Meeting.jpg\"><\/p> <h3><em>Understanding How Dimension Reduction Tools Work<\/em><\/h3> <p><strong>Cynthia Rudin, Professor of Computer Science, Duke University<\/strong><\/p> <p>Dimension reduction (DR) techniques such as t-SNE, UMAP, and TriMap have demonstrated impressive visualization performance on many real world datasets. They are useful for understanding data and trustworthy decision-making, particularly for biological data. One tension that has always faced these methods is the trade-off between preservation of global structure and preservation of local structure: past methods can either handle one or the other, but not both. In this work, our main goal is to understand what aspects of DR methods are important for preserving both local and global structure: it is difficult to design a better method without a true understanding of the choices we make in our algorithms and their empirical impact on the lower-dimensional embeddings they produce. Towards the goal of local structure preservation, we provide several useful design principles for DR loss functions based on our new understanding of the mechanisms behind successful DR methods. Towards the goal of global structure preservation, our analysis illuminates that the choice of which components to preserve is important. We leverage these insights to design a new algorithm for DR, called Pairwise Controlled Manifold Approximation Projection (PaCMAP), which preserves both local and global structure. Our work provides several unexpected insights into what design choices both to make and avoid when constructing DR algorithms.<\/p> <p>The following papers will be discussed:<\/p> <ul> <li>Yingfan Wang, Haiyang Huang, Cynthia Rudin, Yaron Shaposhnik Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMAP, and PaCMAP for Data Visualization Journal of Machine Learning Research (JMLR), 2021 <a href=\"https:\/\/jmlr.org\/papers\/v22\/20-1061.html\" data-feathr-click-track=\"true\">https:\/\/jmlr.org\/papers\/v22\/20-1061.html<\/a><\/li> <li>Haiyang Huang, Yingfan Wang, Cynthia Rudin, and Edward P. Browne Towards a Comprehensive Evaluation of Dimension Reduction Methods for Transcriptomic Data Visualization Communications Biology (Nature), 2022. <a href=\"https:\/\/www.nature.com\/articles\/s42003-022-03628-x\" data-feathr-click-track=\"true\">https:\/\/www.nature.com\/articles\/s42003-022-03628-x<\/a><\/li> <\/ul> <h4>About Cynthia Rudin<\/h4> <p>Cynthia Rudin is a professor of computer science, electrical and computer engineering, statistical science, mathematics, and biostatistics &amp; bioinformatics at Duke University, and directs the Interpretable Machine Learning Lab. Previously, Prof. Rudin held positions at MIT, Columbia, and NYU. She holds an undergraduate degree from the University at Buffalo, and a Ph.D. from Princeton University. She is the recipient of the 2022 Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity from the Association for the Advancement of Artificial Intelligence (AAAI). This award is the most prestigious award in the field of artificial intelligence. Similar only to world-renowned recognitions, such as the Nobel Prize and the Turing Award, it carries a monetary reward at the million-dollar level. Prof. Rudin is also a three-time winner of the INFORMS Innovative Applications in Analytics Award, was named as one of the \"Top 40 Under 40\" by <i>Poets and Quants<\/i> in 2015, and was named by <i>Businessinsider.com<\/i> as one of the 12 most impressive professors at MIT in 2015, and is a 2022 Guggenheim Fellow. She is a fellow of the American Statistical Association, the Institute of Mathematical Statistics, and AAAI.<\/p> <p>Prof. Rudin is past chair of both the INFORMS Data Mining Section and the Statistical Learning and Data Science Section of the American Statistical Association. She has also served on committees for DARPA, the National Institute of Justice, AAAI, and ACM SIGKDD. She has served on several committees for the National Academies of Sciences, Engineering and Medicine, including the Committee on Applied and Theoretical Statistics, the Committee on Law and Justice, the Committee on Analytic Research Foundations for the Next-Generation Electric Grid, and the Committee on Facial Recognition Technology.\u00a0 She has given keynote\/invited talks at several conferences including KDD (twice), AISTATS, SDM, Machine Learning in Healthcare (MLHC), Fairness, Accountability and Transparency in Machine Learning (FAT-ML), ECML-PKDD, and the Nobel Conference. Her work has been featured in news outlets including the <i>NY Times<\/i>, <i>Washington Post<\/i>, <i>Wall Street Journal<\/i>, the <i>Boston Globe<\/i>, <i>Businessweek<\/i>, and <i>NPR<\/i>.<\/p>\n<h2>Industry Keynote<\/h2> <h3><em><strong>Forecasting 2.0 - New Ways to See Around Corners<\/strong><\/em><\/h3> <p><strong>Kirk Borne, Chief Science Officer, DataPrime, Inc.<\/strong><\/p> <p>Predictive modeling and predictive analytics are among the most common industry and business applications of data science and machine learning. I will first review some interesting (amusing and\/or impactful) failure cases of traditional forecasting and predictive modeling. These include traditional autoregressive time series forecasting, which I refer to as \"forecasting 1.0\". I will then introduce some approaches to predictive analytics that are different from standard forecasting 1.0. These novel \"forecasting 2.0\" methods are more contextual, exploiting the insights that come from external contextual data sources. Context-based methods are therefore more beneficial than autoregressive methods in the current data-intensive era in which data sources and data formats extend far beyond traditional time series. Contextual analytics approaches also enable opportunities for prescriptive analytics (causal analysis and causality discovery), which are similar to O.R., but again these go beyond traditional methods of optimization through the application of data from multiple diverse sensors, including the exploding growth of data sources in the IoT (Internet of Things). In this environment, I envision the IoT as the \"Internet of Context\" enabling \"Forecasting-as-a-Service\" (FaaS). Several examples and algorithm categories will be presented to illustrate diverse forecasting 2.0 applications.<\/p> <h4>About Kirk Borne<\/h4> <p>Dr. Kirk Borne is the Chief Science Officer at AI startup DataPrime Inc and is the owner and founder of his own freelance consulting business Data Leadership Group LLC. He is a career data professional, data science leader, and research astrophysicist. From 2015 to 2021, he was Principal Data Scientist, Data Science Fellow, and Executive Advisor at management consulting firm Booz Allen Hamilton. Previously, Kirk was professor of Astrophysics and Computational Science at George Mason University for 12 years where he co-founded the world's first data science undergraduate degree program, and where did research and taught data science at the graduate and undergraduate levels. Before that, he spent 20 years supporting data systems activities for NASA space science missions, including a role as NASA's Data Archive Project Scientist for the Hubble Telescope. He has a Ph.D. in astronomy from Caltech. He is an elected Fellow of the International Astrostatistics Association for his contributions to big data research in astronomy. In 2020, he was elected a Fellow of the American Astronomical Society for lifelong contributions to the field of astronomy. Since 2013, he has been identified as a top worldwide influencer on social media, promoting analytics, data science, machine learning, AI, and data literacy for all. He is currently advisor to several businesses and educational institutions. He is most recently exploring the synergies and innovation opportunities at the convergence of multiple emerging digital technologies: IoT, the metaverse, digital twins, intelligent edge, immersive realities, autonomous systems, and more!<\/p>\n<h2>Joint Panel Discussion with Quality Statistics and Reliability (QSR) Workshop: <em>Fairness and Interpretability in AI\/ML<\/em><\/h2> <p style=\"margin: 12.0pt 0in 0in 0in;\">Many black box machine learning models are being used for high-stakes decisions in healthcare, manufacturing, social media, and various other fields. As a result, there is high susceptibility to bias toward different population demographics as well as poor interpretability in understanding why models make a variety of predictions. This panel will cover recent topics and developments across a number of applications for which fairness and interpretability of machine learning models are crucial.<\/p> <p><strong>Panelists:<\/strong><\/p> <p style=\"margin: 12.0pt 0in 0in 0in;\"><b>Dr. Cynthia Rudin<\/b>\u00a0is a professor of computer science and engineering at Duke University. She directs the Interpretable Machine Learning Lab, and her goal is to design predictive models that people can understand. Her lab applies machine learning in many areas, such as healthcare, criminal justice, and energy reliability. She holds degrees from the University at Buffalo and Princeton. She is the recipient of the 2022 Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity from the Association for the Advancement of Artificial Intelligence (the \u201cNobel Prize of AI\u201d). She received a 2022 Guggenheim fellowship, and is a fellow of the American Statistical Association, the Institute of Mathematical Statistics, and the Association for the Advancement of Artificial Intelligence. Her work has been featured in many news outlets including the NY Times, Washington Post, Wall Street Journal, and Boston Globe.<\/p> <p style=\"box-sizing: border-box; font-variant-ligatures: none; outline: none; text-decoration-line: inherit; white-space: pre-wrap; margin: 12.0pt 0in 0in 0in;\"><b>Dr. Na Zou<\/b> is currently a Corrie &amp; Jim Furber \u201964 assistant professor in Engineering Technology and Industrial Distribution at Texas A&amp;M University. She was an Instructional Assistant Professor in Industrial and Systems Engineering at Texas A&amp;M University from 2016 to 2020. She holds both a Ph.D. in Industrial Engineering and a MSE in Civil, Environmental and Sustainable Engineering from Arizona State University. Her research focuses on fair and interpretable machine learning, transfer learning, network modeling and inference, supported by NSF and industrial sponsors. The research projects have resulted in publications at prestigious journals such as Technometrics, IISE Transactions and ACM Transactions, including one Best Paper Finalist and one Best Student Paper Finalist at INFORMS QSR section and two featured articles at ISE Magazine. She was the recipient of IEEE Irv Kaufman Award and Texas A&amp;M Institute of Data Science Career Initiation Fellow.<\/p> <p style=\"margin-top: 0in; text-align: justify; box-sizing: border-box; outline: none; text-decoration-line: inherit;\"><b><br>Dr. Kinjal\u00a0Basu<\/b>\u00a0is currently a Senior Staff Software Engineer in\u00a0LinkedIn's\u00a0AI team, primarily focusing on Responsible AI, encompassing challenging problems in Fairness, Explainability and Privacy. He leads several efforts that can be applied to different product applications towards making LinkedIn a responsible and equitable platform. Throughout the years, Dr.\u00a0Basu\u00a0has worked on a variety of problems and on various product applications. His focus has ranged from developing prediction models for complex recommender systems powering News Feed Ranking and People You May Know (PYMK) to extreme large-scale optimization problems trying to solve complex matching and allocation problems. He has\u00a0been the chief architect and designer for the AutoML library used internally by various teams such as Feed, Notifications, Ads and PYMK. Dr.\u00a0Basu has also worked towards developing accurate causal estimates in the presence of network interference.<\/p>\n<h2>Poster Competition<\/h2> <p>Are you a student or practitioner working on applied work in the fields of data mining or data science? Click <a href=\"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/files\/2022\/09\/2022-INFORMS-DMDA-Poster-Competition-Flyer.pdf\">here<\/a> for more information on the Poster Competition.\u00a0<\/p>\n<h2>Previous Workshops<\/h2> <p><a href=\"https:\/\/meetings.informs.org\/wordpress\/anaheim2021\/informs-workshop-on-data-mining-decision-analytics\/\">16th Virtual INFORMS Workshop on Data Mining and Decision Analytics<\/a><\/p> <p><a href=\"https:\/\/www.google.com\/url?q=https%3A%2F%2Fsites.google.com%2Fview%2Fdmdaworkshop2020%2Fhome%3Fauthuser%3D2&amp;sa=D&amp;sntz=1&amp;usg=AFQjCNG34lapMmIt5M7VWyOVSIYoHG6Srw\">1<\/a><a href=\"https:\/\/www.google.com\/url?q=https%3A%2F%2Fsites.google.com%2Fview%2Fdmdaworkshop2020%2Fhome%3Fauthuser%3D2&amp;sa=D&amp;sntz=1&amp;usg=AFQjCNG34lapMmIt5M7VWyOVSIYoHG6Srw\">5<\/a><a href=\"https:\/\/www.google.com\/url?q=https%3A%2F%2Fsites.google.com%2Fview%2Fdmdaworkshop2020%2Fhome%3Fauthuser%3D2&amp;sa=D&amp;sntz=1&amp;usg=AFQjCNG34lapMmIt5M7VWyOVSIYoHG6Srw\">th Virtual INFORMS Workshop on Data Mining and Decision Analytics<\/a><\/p> <p><a href=\"https:\/\/www.google.com\/url?q=https%3A%2F%2Fsites.google.com%2Fview%2Fdmdaworkshop%2Fhome&amp;sa=D&amp;sntz=1&amp;usg=AFQjCNGzdttHfIIScET1lfByzVfd2gCp0w\">14th INFORMS Workshop on Data Mining and Decision Analytics<\/a><\/p> <p><a href=\"http:\/\/www.google.com\/url?q=http%3A%2F%2Fmeetings2.informs.org%2Fwordpress%2Fphoenix2018%2Fpre-meeting%2F%23data-mining&amp;sa=D&amp;sntz=1&amp;usg=AFQjCNHca6nTCtUf3K3NISyxJ0kbqQlp8A\">13th INFORMS Workshop on Data Mining and Decision Analytics<\/a><\/p>","_links":{"self":[{"href":"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/wp-json\/wp\/v2\/pages\/361","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/wp-json\/wp\/v2\/users\/1001133"}],"replies":[{"embeddable":true,"href":"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/wp-json\/wp\/v2\/comments?post=361"}],"version-history":[{"count":94,"href":"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/wp-json\/wp\/v2\/pages\/361\/revisions"}],"predecessor-version":[{"id":1978,"href":"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/wp-json\/wp\/v2\/pages\/361\/revisions\/1978"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/wp-json\/wp\/v2\/media\/7"}],"wp:attachment":[{"href":"https:\/\/meetings.informs.org\/wordpress\/indianapolis2022\/wp-json\/wp\/v2\/media?parent=361"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}