{"id":358,"date":"2021-11-04T16:16:10","date_gmt":"2021-11-04T07:16:10","guid":{"rendered":"https:\/\/ie.unist.ac.kr\/new\/?page_id=358"},"modified":"2025-11-05T11:38:32","modified_gmt":"2025-11-05T02:38:32","slug":"laboratory","status":"publish","type":"page","link":"https:\/\/ie.unist.ac.kr\/eng\/laboratory\/","title":{"rendered":"Laboratory"},"content":{"rendered":"[vc_row row_type=&#8221;row&#8221; text_align=&#8221;left&#8221; css_animation=&#8221;&#8221; el_class=&#8221;page_submenu&#8221;][vc_column][vc_column_text]\n<ul class=\"submenu col_4\">\n<li><a href=\"\/eng\/?p=23\/\">Research Activities<\/a><\/li>\n<li><a href=\"\/eng\/?p=358\/\"><strong>Laboratory<\/strong><\/a><\/li>\n<li><a href=\"\/eng\/?p=25\/\">Research Center<\/a><\/li>\n<li><a href=\"\/eng\/?p=24\/\">Research Result<\/a><\/li>\n<\/ul>\n[\/vc_column_text][\/vc_column][\/vc_row][vc_row row_type=&#8221;section&#8221; type=&#8221;grid&#8221; text_align=&#8221;left&#8221; video=&#8221;&#8221;][vc_column][vc_column_text]\n<div class=\"page_lab top\">\n<ul class=\"btn_list\">\n<li><a href=\"#lab_cont1\">\u00b7 Process-Aware AI Lab <\/a><\/li>\n<li><a href=\"#lab_cont2\">\u00b7 Data Analytics Lab<\/a><\/li>\n<li><a href=\"#lab_cont3\">\u00b7 Service Engineering &amp; Knowledge Discovery Lab<\/a><\/li>\n<li class=\"last\"><a href=\"#lab_cont4\">\u00b7 Accelerated Optimization Lab<\/a><\/li>\n<li><a href=\"#lab_cont6\">\u00b7 Financial Engineering Lab<\/a><\/li>\n<li><a href=\"#lab_cont9\">\u00b7 Statistical Decision Making (SDM) Lab<\/a><\/li>\n<li><a href=\"#lab_cont10\">\u00b7 Machine Learning and Finance Lab<\/a><\/li>\n<li><a href=\"#lab_cont11\">\u00b7 Safe Artificial Intelligence Lab <\/a><\/li>\n<li><a href=\"#lab_cont12\">\u00b7 Autonomous Systems and Decision-making Lab (ASDL) <\/a><\/li>\n<\/ul>\n<\/div>\n[\/vc_column_text][vc_column_text]\n<div class=\"page_lab table_scroll\">\n<table class=\"tbl_st4\" summary=\"Intelligent Enterprise Lab\">\n<caption>Process-Aware AI Lab<\/caption>\n<colgroup>\n<col width=\"12%\" \/>\n<col width=\"30%\" \/>\n<col width=\"12%\" \/>\n<col width=\"46%\" \/> <\/colgroup>\n<thead>\n<tr>\n<th colspan=\"4\">Process-Aware AI Lab <a class=\"link\" title=\"\uc0c8\ucc3d\uc5f4\uae30\" href=\"https:\/\/iel.unist.ac.kr\/\" target=\"_blank\" rel=\"noopener\">Website<\/a><\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td class=\"border_db_r tt_upper td_th\">Professor<\/td>\n<td class=\"border_db_r ta_l\">\u200bMarco Comuzzi<\/td>\n<td class=\"border_db_r tt_upper td_th ta_c\" rowspan=\"2\">Description<\/td>\n<td class=\"ta_l\" rowspan=\"2\">This lab focuses on the application of machine learning and computational intelligence techniques (e.g., classification\/regression, deep learning, genetic algorithms and other evolutionary techniques, statistical anomaly detection) to the analysis of business process event logs. These are logs generated by the information systems that support the execution of business processes in organizations. We solve problems like predicting the outcome of the execution of business processes, predicting the activities that will be executed next in a process, or identifying anomalies in event logs, considering also the event streaming perspective.<\/td>\n<\/tr>\n<tr>\n<td class=\"border_db_r tt_upper td_th\">Research<br \/>\nInterests<\/td>\n<td class=\"border_db_r ta_l\">Process Mining, Data Mining, Anomaly Detection, Blockchain<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n[\/vc_column_text][vc_column_text el_id=&#8221;lab_cont2&#8243;]\n<div class=\"page_lab table_scroll\">\n<table class=\"tbl_st4\" summary=\"Data Analytics Lab\">\n<caption>Data Analytics Lab<\/caption>\n<colgroup>\n<col width=\"12%\" \/>\n<col width=\"30%\" \/>\n<col width=\"12%\" \/>\n<col width=\"46%\" \/> <\/colgroup>\n<thead>\n<tr>\n<th colspan=\"4\">Data Analytics Lab<a class=\"link\" title=\"\uc0c8\ucc3d\uc5f4\uae30\" href=\"http:\/\/analytics.unist.ac.kr\" target=\"_blank\" rel=\"noopener\">Website<\/a><\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td class=\"border_db_r tt_upper td_th\">Professor<\/td>\n<td class=\"border_db_r ta_l\">\u200bSungil Kim<\/td>\n<td class=\"border_db_r tt_upper td_th ta_c\" rowspan=\"2\">Description<\/td>\n<td class=\"ta_l\" rowspan=\"2\">Dr. Kim&#8217;s research interests are in the broad areas of data science and business analytics. A major focus of his research is in developing novel statistical methods for solving complex engineering problems. He has several years of consulting experience in solving real business problems in industries.<\/td>\n<\/tr>\n<tr>\n<td class=\"border_db_r tt_upper td_th\">Research<br \/>\nInterests<\/td>\n<td class=\"border_db_r ta_l\">Business Analytics, Statistical Quality Control, Anomaly Detection, Data Mining and Machine Learning, Design of Experiments, Robust Parameter Design, Demand Forecasting, Predictive Analytics<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n[\/vc_column_text][vc_column_text el_id=&#8221;lab_cont3&#8243;]\n<div class=\"page_lab table_scroll\">\n<table class=\"tbl_st4\" summary=\"Service Engineering &amp; Knowledge Discovery Lab\">\n<caption>Service Engineering &amp; Knowledge Discovery Lab<\/caption>\n<colgroup>\n<col width=\"12%\" \/>\n<col width=\"30%\" \/>\n<col width=\"12%\" \/>\n<col width=\"46%\" \/> <\/colgroup>\n<thead>\n<tr>\n<th colspan=\"4\">Service Engineering &amp; Knowledge Discovery Lab<a class=\"link\" title=\"\uc0c8\ucc3d\uc5f4\uae30\" href=\"http:\/\/service.unist.ac.kr\" target=\"_blank\" rel=\"noopener\">Website<\/a><\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td class=\"border_db_r tt_upper td_th\">Professor<\/td>\n<td class=\"border_db_r ta_l\">\u200bChiehyeon Lim<\/td>\n<td class=\"border_db_r tt_upper td_th ta_c\" rowspan=\"2\">Description<\/td>\n<td class=\"ta_l\" rowspan=\"2\">We focus on developing data analytics methods to achieve learning tasks (i.e., knowledge discovery from data), such as representation, generation, prediction, and clustering. Based on such methods, we are also interested in solving real-world service problems with firms and governments (i.e., service engineering with data), including item recommendation, behavioral intervention, process monitoring, and service improvement.<\/td>\n<\/tr>\n<tr>\n<td class=\"border_db_r tt_upper td_th\">Research<br \/>\nInterests<\/td>\n<td class=\"border_db_r ta_l\">Knowledge Discovery on the Representation, Prediction, Generation, and Control by Machines<br \/>\nApplied Data Science and the Intelligence Development for Real-world Service Engineering<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n[\/vc_column_text][vc_column_text el_id=&#8221;lab_cont4&#8243;]\n<div class=\"page_lab table_scroll\">\n<table class=\"tbl_st4\" summary=\"Accelerated Optimization Laboratory\">\n<caption>Accelerated Optimization Laboratory<\/caption>\n<colgroup>\n<col width=\"12%\" \/>\n<col width=\"30%\" \/>\n<col width=\"12%\" \/>\n<col width=\"46%\" \/> <\/colgroup>\n<thead>\n<tr>\n<th colspan=\"4\">Accelerated Optimization Laboratory<a class=\"link\" title=\"\uc0c8\ucc3d\uc5f4\uae30\" href=\"#\" target=\"_blank\" rel=\"noopener\">Website<\/a><\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td class=\"border_db_r tt_upper td_th\">Professor<\/td>\n<td class=\"border_db_r ta_l\">Youngdae Kim<\/td>\n<td class=\"border_db_r tt_upper td_th ta_c\" rowspan=\"2\">Description<\/td>\n<td class=\"ta_l\" rowspan=\"2\">ACCOL (ACCelerated Optimization Laboratory) aims at developing accelerated mathematical optimization algorithms via GPUs and AI and improving the quality of AI solutions via mathematical optimization. To achieve this, we study i) GPU-accelerated distributed large-scale mathematical optimization algorithms; ii) the integration of mathematical optimization with AI; and iii) a computational framework that provides easy access to our technology. Our recent research results have been applied to large-scale power system optimization and biobank analysis.<\/td>\n<\/tr>\n<tr>\n<td class=\"border_db_r tt_upper td_th\">Research<br \/>\nInterests<\/td>\n<td class=\"border_db_r ta_l\">GPU-accelerated and AI-enhanced mathematical optimization, Integration of mathematical optimization with AI, Energy system optimization<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n[\/vc_column_text][vc_column_text el_id=&#8221;lab_cont6&#8243;]\n<div class=\"page_lab table_scroll\">\n<table class=\"tbl_st4\" summary=\"Financial Engineering Lab\">\n<caption>Financial Engineering Lab<\/caption>\n<colgroup>\n<col width=\"12%\" \/>\n<col width=\"30%\" \/>\n<col width=\"12%\" \/>\n<col width=\"46%\" \/> <\/colgroup>\n<thead>\n<tr>\n<th colspan=\"4\">Financial Engineering Lab<a class=\"link\" title=\"\uc0c8\ucc3d\uc5f4\uae30\" href=\"http:\/\/felab.unist.ac.kr\" target=\"_blank\" rel=\"noopener\">Website<\/a><\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td class=\"border_db_r tt_upper td_th\">Professor<\/td>\n<td class=\"border_db_r ta_l\">Yongjae Lee<\/td>\n<td class=\"border_db_r tt_upper td_th ta_c\" rowspan=\"2\">Description<\/td>\n<td class=\"ta_l\" rowspan=\"2\">We study quantitative approaches to financial planning of individuals and institutions. Most research topics can be categorized into three: (1) making optimal investment decisions using optimization and machine learning, (2) financial market modeling using econometrics and pattern recognition, and (3) investor data analysis using data science techniques. By developing advanced theories and practical technologies, we aim to make it possible for everyone to receive customized life-time financial planning services.<\/td>\n<\/tr>\n<tr>\n<td class=\"border_db_r tt_upper td_th\">Research<br \/>\nInterests<\/td>\n<td class=\"border_db_r ta_l\">Financial Engineering, Financial Optimization,<br \/>\nFinancial Data Analysis, Financial Planning<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n[\/vc_column_text][vc_column_text el_id=&#8221;lab_cont9&#8243;]\n<div class=\"page_lab table_scroll\">\n<table class=\"tbl_st4\" summary=\"Statistical Decision Making (SDM) Lab\">\n<caption>Statistical Decision Making (SDM) Lab<\/caption>\n<colgroup>\n<col width=\"12%\" \/>\n<col width=\"30%\" \/>\n<col width=\"12%\" \/>\n<col width=\"46%\" \/> <\/colgroup>\n<thead>\n<tr>\n<th colspan=\"4\">Statistical Decision Making (SDM) Lab<a class=\"link\" title=\"\uc0c8\ucc3d\uc5f4\uae30\" href=\"https:\/\/sdm.unist.ac.kr\/\" target=\"_blank\" rel=\"noopener\">Website<\/a><\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td class=\"border_db_r tt_upper td_th\">Professor<\/td>\n<td class=\"border_db_r ta_l\">Gi-Soo Kim<\/td>\n<td class=\"border_db_r tt_upper td_th ta_c\" rowspan=\"2\">Description<\/td>\n<td class=\"ta_l\" rowspan=\"2\">Our research interests are focused on statistical approaches to the sequential decision problem. The multi-armed bandit (MAB) problem formulates the sequential decision problem in which a learner is sequentially faced with a set of available actions, chooses an action, and receives a random reward in response. In our lab, we integrate online learning and optimization techniques to develop algorithms that efficiently learn the reward model while maximizing the rewards. We also apply the developed algorithms to real tasks such as recommendation systems and mobile health apps. We also use causal inference to evaluate the performance of multi-armed bandit algorithms in a retrospective way.<\/td>\n<\/tr>\n<tr>\n<td class=\"border_db_r tt_upper td_th\">Research<br \/>\nInterests<\/td>\n<td class=\"border_db_r ta_l\">Sequential Decision Making, Bandit Algorithms, Causal Inference, Missing Data Analysis<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n[\/vc_column_text][vc_column_text]\n<div class=\"page_lab table_scroll\">\n<table class=\"tbl_st4\" summary=\"Statistical Decision Making (SDM) Lab\">\n<caption>Machine Learning\u00a0and Finance Lab<\/caption>\n<colgroup>\n<col width=\"12%\" \/>\n<col width=\"30%\" \/>\n<col width=\"12%\" \/>\n<col width=\"46%\" \/> <\/colgroup>\n<thead>\n<tr>\n<th colspan=\"4\">Machine Learning\u00a0and Finance Lab<a class=\"link\" title=\"\uc0c8\ucc3d\uc5f4\uae30\" href=\"https:\/\/sites.google.com\/view\/dlim\/home?authuser=0\" target=\"_blank\" rel=\"noopener\">Website<\/a><\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td class=\"border_db_r tt_upper td_th\">Professor<\/td>\n<td class=\"border_db_r ta_l\">Dong-Young Lim<\/td>\n<td class=\"border_db_r tt_upper td_th ta_c\" rowspan=\"2\">Description<\/td>\n<td class=\"ta_l\" rowspan=\"2\">The research of Prof. Dong-Young Lim&#8217;s lab is focused on stochastic optimization algorithms, nonconvex optimization, and their applications in finance and insurance.<br \/>\nIn particular, we are interested in quantitative risk management in financial markets, the development of efficient algorithms for large-scale nonconvex optimization, the study of theoretical properties of such algorithms. Some of our current research projects are<\/p>\n<ul class=\"list_st_none\">\n<li>\u00b7 Diffusion-based algorithms for nonconvex optimization and generative model,<\/li>\n<li>\u00b7 MCMC algorithms<\/li>\n<li>\u00b7 AI application in finance and insurance<\/li>\n<\/ul>\n<\/td>\n<\/tr>\n<tr>\n<td class=\"border_db_r tt_upper td_th\">Research<br \/>\nInterests<\/td>\n<td class=\"border_db_r ta_l\">Stochastic and Nonconvex Optimization, Generative Models, Mathematical Finance, AI application in Finance and Insurance<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n[\/vc_column_text][vc_column_text]\n<div class=\"page_lab table_scroll\">\n<table class=\"tbl_st4\" summary=\"Statistical Decision Making (SDM) Lab\">\n<caption>Safe Artificial Intelligence Lab<\/caption>\n<colgroup>\n<col width=\"12%\" \/>\n<col width=\"30%\" \/>\n<col width=\"12%\" \/>\n<col width=\"46%\" \/> <\/colgroup>\n<thead>\n<tr>\n<th colspan=\"4\">Safe Artificial Intelligence Lab<a class=\"link\" title=\"\uc0c8\ucc3d\uc5f4\uae30\" href=\"https:\/\/sites.google.com\/view\/safe-ai-lab\/home \" target=\"_blank\" rel=\"noopener\">Website<\/a><\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td class=\"border_db_r tt_upper td_th\">Professor<\/td>\n<td class=\"border_db_r ta_l\">Saerom Park<\/td>\n<td class=\"border_db_r tt_upper td_th ta_c\" rowspan=\"2\">Description<\/td>\n<td class=\"ta_l\" rowspan=\"2\">Our research is focused on addressing the interconnected challenges of privacy, fairness, and security to promote the safe use of artificial intelligence (AI) algorithms in real-world systems. Our goal is to develop innovative solutions that enable privacy-preserving, fairness-aware, and security-enhanced machine learning. To achieve this goal, we are pursuing two key problem thrusts:<\/p>\n<p>(i) We are developing comprehensive approaches to ensure the reliability of AI while considering security and privacy threats.<\/p>\n<p>(ii) We are addressing the need for realistic threat models and evaluation for security-aware algorithms.<\/p>\n<p>We are committed to advancing the field of artificial intelligence in a responsible and ethical manner. We believe that these three pillars are critical for building AI systems that are safe and beneficial for individuals, industry, and society.<\/td>\n<\/tr>\n<tr>\n<td class=\"border_db_r tt_upper td_th\">Research<br \/>\nInterests<\/td>\n<td class=\"border_db_r ta_l\">Privacy-preserving machine learning, fairness-aware machine learning, security-enhanced machine learning<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n[\/vc_column_text][vc_column_text el_id=&#8221;lab_cont12&#8243;]\n<div class=\"page_lab table_scroll\">\n<table class=\"tbl_st4\" summary=\"Autonomous Systems and Decision-making Lab(ASDL)\">\n<caption>Autonomous Systems and Decision-making Lab (ASDL)<\/caption>\n<colgroup>\n<col width=\"12%\" \/>\n<col width=\"30%\" \/>\n<col width=\"12%\" \/>\n<col width=\"46%\" \/> <\/colgroup>\n<thead>\n<tr>\n<th colspan=\"4\">Autonomous Systems and Decision-making Lab(ASDL)<a class=\"link\" title=\"\uc0c8\ucc3d\uc5f4\uae30\" href=\"https:\/\/sites.google.com\/view\/asd-lab\" target=\"_blank\" rel=\"noopener\">Website<\/a><\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td class=\"border_db_r tt_upper td_th\">Professor<\/td>\n<td class=\"border_db_r ta_l\">Hyungho Na<\/td>\n<td class=\"border_db_r tt_upper td_th ta_c\" rowspan=\"2\">Description<\/td>\n<td class=\"ta_l\" rowspan=\"2\"><i><span lang=\"EN-US\">In this era of AI transformation, a wide range of research is actively integrating AI into domains such as manufacturing, finance, defense, and aerospace, with a strong focus on autonomous decision-making.\u00a0Within this trend,\u00a0<b>ASDL<\/b>\u00a0aims to develop autonomous systems and enhance decision-making capabilities across diverse domains. Our lab conducts research in both\u00a0<b>AI foundations<\/b>\u00a0(e.g., multi-agent reinforcement learning, representation learning, robot learning, and lifelong learning) and\u00a0<b>AI applications<\/b>\u00a0(e.g., defense systems, smart manufacturing, and complex network systems).<\/span><\/i><\/td>\n<\/tr>\n<tr>\n<td class=\"border_db_r tt_upper td_th\">Research<br \/>\nInterests<\/td>\n<td class=\"border_db_r ta_l\">Reinforcement Learning, Multi-Agent Systems, AI-based Decision-making, Autonomous Systems and Operations, Representation Learning, Robot Learning and Physical AI<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n[\/vc_column_text][\/vc_column][\/vc_row]\n","protected":false},"excerpt":{"rendered":"<p>[vc_row row_type=&#8221;row&#8221; text_align=&#8221;left&#8221; css_animation=&#8221;&#8221; el_class=&#8221;page_submenu&#8221;][vc_column][vc_column_text] Research Activities Laboratory Research Center Research Result [\/vc_column_text][\/vc_column][\/vc_row][vc_row row_type=&#8221;section&#8221; type=&#8221;grid&#8221; text_align=&#8221;left&#8221; video=&#8221;&#8221;][vc_column][vc_column_text] \u00b7 Process-Aware AI Lab \u00b7 Data Analytics Lab \u00b7 Service Engineering &amp; Knowledge Discovery Lab \u00b7 Accelerated Optimization Lab \u00b7 Financial Engineering Lab \u00b7 Statistical Decision Making (SDM)&#8230;<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"full_width.php","meta":{"footnotes":""},"class_list":["post-358","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/ie.unist.ac.kr\/eng\/wp-json\/wp\/v2\/pages\/358","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ie.unist.ac.kr\/eng\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/ie.unist.ac.kr\/eng\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/ie.unist.ac.kr\/eng\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ie.unist.ac.kr\/eng\/wp-json\/wp\/v2\/comments?post=358"}],"version-history":[{"count":38,"href":"https:\/\/ie.unist.ac.kr\/eng\/wp-json\/wp\/v2\/pages\/358\/revisions"}],"predecessor-version":[{"id":1446,"href":"https:\/\/ie.unist.ac.kr\/eng\/wp-json\/wp\/v2\/pages\/358\/revisions\/1446"}],"wp:attachment":[{"href":"https:\/\/ie.unist.ac.kr\/eng\/wp-json\/wp\/v2\/media?parent=358"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}