{"id":766,"date":"2023-03-28T12:38:23","date_gmt":"2023-03-28T12:38:23","guid":{"rendered":"https:\/\/www.ukm.my\/ivic\/?page_id=766"},"modified":"2025-11-04T02:47:39","modified_gmt":"2025-11-04T02:47:39","slug":"workshops-2","status":"publish","type":"page","link":"https:\/\/www.ukm.my\/ivic\/workshops-2\/","title":{"rendered":"Workshops"},"content":{"rendered":"\t\t
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Workshop on\nVisGen: Exploring\nGenerative AI for\nVisual Data Science<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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In the era of Future AI-Powered Visual Informatics,\nGenerative AI (GenAI) is transforming the landscape of how\nvisual data is understood, manipulated, and utilized across\ndisciplines. As images, videos, and complex visual signals\nbecome central to decision-making in sectors like healthcare,\nurban planning, and creative industries, it is crucial to\nunderstand the fundamentals and evolving trends of GenAI\nthat enable such intelligent visual processing. From text-toimage\ngeneration to context-aware augmentation, GenAI\nmodels like Stable Diffusion and DALL\u00b7E are not just tools\nthey are becoming creative collaborators and analytical\nengines.\nThis workshop provides a gateway to explore real-world use\ncases where generative models enhance image quality,\nsynthesize training data, and create visual narratives.\nParticipants will gain hands-on experience with powerful\nplatforms such as RunwayML, GPT Vision, and Pythonbased\nCollab notebooks, enabling them to move beyond\ntheory into applied visual data science. Most importantly,\nattendees will learn how to embed these capabilities into\nvisual analytics pipelines, supporting scalable, data-driven\nresearch and innovation. As AI reshapes visual informatics,\nmastering GenAI is essential to building future-ready\nsolutions that are not only intelligent but also interpretable,\ninclusive, and impactful.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Trainer:<\/b> Prof. Dr. <\/em>J. Joshua Thomas
Date:<\/b> 10 Nov 2025<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Data Science with Orange: A Visual Approach to Data Analytics<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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This course will address the following key questions\n\n1.\tUnlock data insights and harness data analytics for scalable, future-ready solutions using Orange.\n2.\tApply the full data science workflow using CRISP-DM methodology\n3.\tTransform raw data into meaningful insights for decision-making.\n4.\tPerform data analysis and build machine learning models without programming.\n\n\n<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Trainer:<\/b> Assoc. Prof. Dr. Syahaneim binti Marzukhi
Date:<\/b> 10 Nov 2025<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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AI Large Models Reshape Enterprise Supply Chain and Production Management<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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The workshop explores how large scale AI models drive transformation in science, technology, and industry. It begins with an overview of AI large models, their evolution, architecture, and core technologies such as pretraining, multimodal learning, and distributed computing. The workshop then examines their impact on scientific research, highlighting breakthroughs in materials science, drug discovery, and quantum computing. It further discusses industrial innovations across sectors like manufacturing, agriculture, finance, healthcare, education, and autonomous systems, emphasizing intelligent upgrading and new business ecosystems. Through international and domestic case studies such as OpenAI, Google, Baidu, Alibaba, and DeepMind, participants will analyze success factors and challenges. Key issues such as model interpretability, efficiency, data security, ethics, and employment impact are addressed, with policy and technical countermeasures proposed. The workshop concludes with future trends and recommendations for sustainable AI driven innovation.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Trainer:<\/b> Dr. Wang Hao
Date:<\/b> 11 Nov 2025<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

Workshop on VisGen: Exploring Generative AI for Visual Data Science In the era of Future AI-Powered Visual Informatics, Generative AI (GenAI) is transforming the landscape of how visual data is understood, manipulated, and utilized across disciplines. As images, videos, and complex visual signals become central to decision-making in sectors like healthcare, urban planning, and creative industries, it is crucial to understand the fundamentals and evolving trends of GenAI that enable such intelligent visual processing. From text-toimage generation to context-aware augmentation, GenAI models like Stable Diffusion and DALL\u00b7E are not just tools they are becoming creative collaborators and analytical engines. This workshop provides a gateway to explore real-world use cases where generative models enhance image quality, synthesize training data, and create visual narratives. Participants will gain hands-on experience with powerful platforms such as RunwayML, GPT Vision, and Pythonbased Collab notebooks, enabling them to move beyond theory into applied visual data science. Most importantly, attendees will learn how to embed these capabilities into visual analytics pipelines, supporting scalable, data-driven research and innovation. As AI reshapes visual informatics, mastering GenAI is essential to building future-ready solutions that are not only intelligent but also interpretable, inclusive, and impactful. Brochure – Eng Brochure – zh-CN Trainer: Prof. Dr. J. Joshua ThomasDate: 10 Nov 2025 Data Science with Orange: A Visual Approach to Data Analytics This course will address the following key questions 1. Unlock data insights and harness data analytics for scalable, future-ready solutions using Orange. 2. Apply the full data science workflow using CRISP-DM methodology 3. Transform raw data into meaningful insights for decision-making. 4. Perform data analysis and build machine learning models without programming. Brochure – Eng Brochure – zh-CN Trainer: Assoc. Prof. Dr. Syahaneim binti MarzukhiDate: 10 Nov 2025 AI Large Models Reshape Enterprise Supply Chain and Production Management The workshop explores how large scale AI models drive transformation in science, technology, and industry. It begins with an overview of AI large models, their evolution, architecture, and core technologies such as pretraining, multimodal learning, and distributed computing. The workshop then examines their impact on scientific research, highlighting breakthroughs in materials science, drug discovery, and quantum computing. It further discusses industrial innovations across sectors like manufacturing, agriculture, finance, healthcare, education, and autonomous systems, emphasizing intelligent upgrading and new business ecosystems. Through international and domestic case studies such as OpenAI, Google, Baidu, Alibaba, and DeepMind, participants will analyze success factors and challenges. Key issues such as model interpretability, efficiency, data security, ethics, and employment impact are addressed, with policy and technical countermeasures proposed. The workshop concludes with future trends and recommendations for sustainable AI driven innovation. Brochure – Eng Speaker – Eng Brochure – zh-CN Brochure – zh-CN Trainer: Dr. Wang HaoDate: 11 Nov 2025<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"class_list":["post-766","page","type-page","status-publish","hentry"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/www.ukm.my\/ivic\/wp-json\/wp\/v2\/pages\/766","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.ukm.my\/ivic\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.ukm.my\/ivic\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.ukm.my\/ivic\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.ukm.my\/ivic\/wp-json\/wp\/v2\/comments?post=766"}],"version-history":[{"count":6,"href":"https:\/\/www.ukm.my\/ivic\/wp-json\/wp\/v2\/pages\/766\/revisions"}],"predecessor-version":[{"id":2600,"href":"https:\/\/www.ukm.my\/ivic\/wp-json\/wp\/v2\/pages\/766\/revisions\/2600"}],"wp:attachment":[{"href":"https:\/\/www.ukm.my\/ivic\/wp-json\/wp\/v2\/media?parent=766"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}