{"id":4456,"date":"2024-01-23T16:15:04","date_gmt":"2024-01-23T16:15:04","guid":{"rendered":"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/?page_id=4456"},"modified":"2024-03-21T19:21:11","modified_gmt":"2024-03-21T19:21:11","slug":"segev-wasserkrug","status":"publish","type":"page","link":"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/speakers\/segev-wasserkrug\/","title":{"rendered":"Segev Wasserkrug"},"content":{"rendered":"<!--themify_builder_content-->\n<div id=\"themify_builder_content-4456\" data-postid=\"4456\" class=\"themify_builder_content themify_builder_content-4456 themify_builder tf_clear\">\n                    <div  data-lazy=\"1\" class=\"module_row themify_builder_row dropPadding-bottom tb_0l52602 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 col4-1 tb_0ygc603 first\">\n                    <!-- module image -->\n<div  class=\"module module-image tb_esex603 image-top   tf_mw\" data-lazy=\"1\">\n        <div class=\"image-wrap tf_rel tf_mw\">\n            <img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"300\" src=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/01\/Segev_Wasserkrug.jpg\" class=\"wp-post-image wp-image-4400\" title=\"Segev Wasserkrug\" alt=\"Segev Wasserkrug headshot\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/01\/Segev_Wasserkrug.jpg 300w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/01\/Segev_Wasserkrug-150x150.jpg 150w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/>    \n        <\/div>\n    <!-- \/image-wrap -->\n    \n        <div class=\"image-content\">\n                    <h3 class=\"image-title\">\n                                    Segev Wasserkrug                            <\/h3>\n                    <\/div>\n    <!-- \/image-content -->\n        <\/div>\n<!-- \/module image -->        <\/div>\n                    <div  data-lazy=\"1\" class=\"module_column tb-column col4-3 tb_g2w3604 last\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_t7c7604   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h1>Segev Wasserkrug<\/h1>\n<h5>Senior Technical Staff Member at IBM Research<\/h5>    <\/div>\n<\/div>\n<!-- \/module text --><!-- module accordion -->\n<div  class=\"module module-accordion tb_r5gz831 \" data-behavior=\"toggle\" data-lazy=\"1\">\n    \n    <ul class=\"ui module-accordion  glossy tb_default_color\">\n            <li>\n            <div class=\"accordion-title tf_rel\">\n                <a href=\"#acc-r5gz831-0\" class=\"tb_title_accordion\" aria-controls=\"acc-r5gz831-0-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-minus\" aria-hidden=\"true\"><use href=\"#tf-ti-minus\"><\/use><\/svg><\/i>                    <span class=\"accordion-title-wrap\">Bio<\/span>                <\/a>\n            <\/div><!-- .accordion-title -->\n            <div id=\"acc-r5gz831-0-content\" data-id=\"acc-r5gz831-0\" aria-hidden=\"true\" class=\"accordion-content tf_hide tf_clearfix\">\n                                    <div class=\"tb_text_wrap\">\n                        <p>Segev Wasserkrug, Ph.D., a Senior Technical Staff Member and technical leader at IBM Research, specializes in optimization, game theory and machine learning. With over 20 years of experience, Segev has applied advanced analytics, AI, and optimization techniques across various domains, including automated diagnosis and logistics, to help IBM and its clients make better decisions. Currently, he focuses on developing algorithms and tools that integrate large language models with optimization methods for business decision-making, and addresses multi-party decision making use cases through a blend of game theory and machine learning.<\/p>\n<p>Segev holds a strong academic record in operations research, computer science and AI, contributing to over 35 academic publications and around 30 patent submissions. He is a three-time INFORMS Wagner Prize finalist and was a finalist for the 2018 INFORMS Innovative Application in Analytics Award. Segev earned his Ph.D. in Information Systems Engineering and his M.Sc. and B.A. in Computer Science from the Technion. He also serves as a Research Associate in the Faculty of Decisions and Data Science at the Technion.<\/p>                    <\/div>\n                            <\/div><!-- .accordion-content -->\n        <\/li>\n        <\/ul>\n\n<\/div><!-- \/module accordion -->        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-css_id=\"u6fe602\" data-lazy=\"1\" class=\"module_row themify_builder_row fullwidth_row_container tb_u6fe602 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_84q1605 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_k572608 track  \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h6>Track: Machine Learning &amp; AI<\/h6>    <\/div>\n<\/div>\n<!-- \/module text --><!-- module text -->\n<div  class=\"module module-text tb_xwmz608   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h2>Leveraging Large Language Models in Analytics Practice: Opportunities, Challenges and Best Practices<\/h2>\n<p>Large Language Models (LLMs) such as ChatGPT have become widespread and are positioned to impact many jobs and roles. A notable study by the Harvard Business School in collaboration with Boston Consulting Group found that consultants using an LLM completed 12.5% more tasks, completed these tasks 25% quicker and produced 40% higher quality results than consultants which did not have access to an LLM. Conversely, this study also sheds light on some potential dangers of the usage of LLMs.<\/p>\n<p>In our presentation, we will delve into the practical implications of LLMs for analytics practitioners. Following work led by the INFORMS Practice Section Board and using a real-world use case, we will show how an LLM can be used throughout the lifecycle of designing, implementing, and deploying a data driven optimization solution. Key takeaways of this presentation include:<\/p>\n<ul>\n<li>A technical overview of LLMs, their capabilities and usage.<\/li>\n<li>Awareness of how an LLM could be used throughout the lifecycle of creating an analytics application, including precise problem formulation, optimization and data analysis code generation, and user interface and documentation creation.<\/li>\n<li>Guidelines for more effective LLM usage in analytics projects.<\/li>\n<li>Potential pitfalls and dangers of LLM usage for analytic solution creation, including ethical and intellectual property aspects.<\/li>\n<\/ul>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                        <\/div>\n        <\/div>\n        <\/div>\n<!--\/themify_builder_content-->","protected":false},"excerpt":{"rendered":"<p>Segev Wasserkrug Senior Technical Staff Member at IBM Research<\/p>\n","protected":false},"author":1001140,"featured_media":0,"parent":712,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"content-type":"","footnotes":""},"class_list":["post-4456","page","type-page","status-publish","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) - 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With over 20 years of experience, Segev has applied advanced analytics, AI, and optimization techniques across various domains, including automated diagnosis and logistics, to help IBM and its clients make better decisions. Currently, he focuses on developing algorithms and tools that integrate large language models with optimization methods for business decision-making, and addresses multi-party decision making use cases through a blend of game theory and machine learning.<\/p> <p>Segev holds a strong academic record in operations research, computer science and AI, contributing to over 35 academic publications and around 30 patent submissions. He is a three-time INFORMS Wagner Prize finalist and was a finalist for the 2018 INFORMS Innovative Application in Analytics Award. Segev earned his Ph.D. in Information Systems Engineering and his M.Sc. and B.A. in Computer Science from the Technion. He also serves as a Research Associate in the Faculty of Decisions and Data Science at the Technion.<\/p><\/li><\/ul>\n<h6>Track: Machine Learning &amp; AI<\/h6>\n<h2>Leveraging Large Language Models in Analytics Practice: Opportunities, Challenges and Best Practices<\/h2> <p>Large Language Models (LLMs) such as ChatGPT have become widespread and are positioned to impact many jobs and roles. A notable study by the Harvard Business School in collaboration with Boston Consulting Group found that consultants using an LLM completed 12.5% more tasks, completed these tasks 25% quicker and produced 40% higher quality results than consultants which did not have access to an LLM. Conversely, this study also sheds light on some potential dangers of the usage of LLMs.<\/p> <p>In our presentation, we will delve into the practical implications of LLMs for analytics practitioners. 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