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![Amsterdam AI x DSC presents: Exploring Generative AI in People Analytics and HRM](/Meetup_Generative_AI_(1).jpg?version=2742)
11 April 2024
Amsterdam AI x DSC presents: Exploring Generative AI in People Analytics and HRM
We have the honour of hosting three amazing speakers, they will each talk about the topic but from three different perspectives. The academic perspective, the Industry perspective and the Industry on Academic perspective.
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Programme:
15:30 - Walk In
15:45 - Introduction Amsterdam AI and Data Science Centre
15:50 - Talk #1 by Shuai Yuan: Revolutionize your HR daily work with GenAI? Promises and Challenges
16:10 - Discussion
16:15 - Talk #2 by Dr. Georgios Tsatsaronis (Elsevier)
16:40 - Discussion
16:45 - Talk #3 by Jakub M. Tomczak: Generative AI for the Industry: More than ChatGPT
17:05 - Discussion
17:10 - End!
15:30 - Walk In
15:45 - Introduction Amsterdam AI and Data Science Centre
15:50 - Talk #1 by Shuai Yuan: Revolutionize your HR daily work with GenAI? Promises and Challenges
16:10 - Discussion
16:15 - Talk #2 by Dr. Georgios Tsatsaronis (Elsevier)
16:40 - Discussion
16:45 - Talk #3 by Jakub M. Tomczak: Generative AI for the Industry: More than ChatGPT
17:05 - Discussion
17:10 - End!
Talk #1 by Shuai Yuan (Assistant Professor in People Analytics at the University of Amsterdam)
Title: revolutionize your HR daily work with GenAI? Promises and Challenges.
Abstract: In this brief presentation, we take a very practical angle to closely watch GenAI's transformational capability to revolutionize HR practices. With no empty words, I will showcase the potential of applying GenAI in a few novel demonstrations. The dark side of the story - the risks and challenges of applying GenAI - will then be revealed.
Bio: With a PhD degree in behavioral data science, Shuai Yuan works as an assistant professor at Amsterdam Business School and in the Amsterdam People Analytics Centre. His research interests are predictive modeling, modern technology, and data science methods for HRM research. He particularly enjoy working with companies on People Analytics projects
Title: revolutionize your HR daily work with GenAI? Promises and Challenges.
Abstract: In this brief presentation, we take a very practical angle to closely watch GenAI's transformational capability to revolutionize HR practices. With no empty words, I will showcase the potential of applying GenAI in a few novel demonstrations. The dark side of the story - the risks and challenges of applying GenAI - will then be revealed.
Bio: With a PhD degree in behavioral data science, Shuai Yuan works as an assistant professor at Amsterdam Business School and in the Amsterdam People Analytics Centre. His research interests are predictive modeling, modern technology, and data science methods for HRM research. He particularly enjoy working with companies on People Analytics projects
Talk #2 by Dr. Georgios Tsatsaronis (Elsevier)
Title: TBA
Title: TBA
Talk #3 by Jakub M. Tomczak (Eindhoven University of Technology)
Title: Generative AI for the Industry: More than ChatGPT
Abstract: AI is not enough to change the industry, we need Generative AI for that. The goals of Industry 5.0 are about collaboration between humans and machines, high personalization, responsiveness & distribution, autonomous behavior, and new content creation. To allow this paradigm shift, Generative AI provides us with all the necessary tools, namely, Large Language Models for communication and responsiveness, Foundation Models (models trained on general data and fine-tuned on individual data) for personalization and distribution, and image/text/audio generators for content synthesis. In this talk, we will show examples that there is no Industry 5.0 without Generative AI.
Bio: Jakub M. Tomczak is an associate professor and the PI of the Generative AI group at the Eindhoven University of Technology (TU/e). He is also the founder of Amsterdam AI Solutions. Before joining the TU/e, he was an assistant professor at Vrije Universiteit Amsterdam, a deep learning researcher (Engineer, Staff) in Qualcomm AI Research in Amsterdam, a Marie Sklodowska-Curie individual fellow in Prof. Max Welling's group at the University of Amsterdam, and an assistant professor and a postdoc at the Wroclaw University of Technology. His main research interests include deep generative modeling, deep learning, and Bayesian inference, with applications to image/text processing, Life Sciences, and Molecular Sciences. He is a program chair for NeurIPS 2024. He serves as an action editor of "Transactions of Machine Learning Research", and an area chair of major AI conferences (e.g., NeurIPS, ICML, AISTATS). He is the author of the book entitled "Deep Generative Modeling", the first comprehensive book on Generative AI.
Title: Generative AI for the Industry: More than ChatGPT
Abstract: AI is not enough to change the industry, we need Generative AI for that. The goals of Industry 5.0 are about collaboration between humans and machines, high personalization, responsiveness & distribution, autonomous behavior, and new content creation. To allow this paradigm shift, Generative AI provides us with all the necessary tools, namely, Large Language Models for communication and responsiveness, Foundation Models (models trained on general data and fine-tuned on individual data) for personalization and distribution, and image/text/audio generators for content synthesis. In this talk, we will show examples that there is no Industry 5.0 without Generative AI.
Bio: Jakub M. Tomczak is an associate professor and the PI of the Generative AI group at the Eindhoven University of Technology (TU/e). He is also the founder of Amsterdam AI Solutions. Before joining the TU/e, he was an assistant professor at Vrije Universiteit Amsterdam, a deep learning researcher (Engineer, Staff) in Qualcomm AI Research in Amsterdam, a Marie Sklodowska-Curie individual fellow in Prof. Max Welling's group at the University of Amsterdam, and an assistant professor and a postdoc at the Wroclaw University of Technology. His main research interests include deep generative modeling, deep learning, and Bayesian inference, with applications to image/text processing, Life Sciences, and Molecular Sciences. He is a program chair for NeurIPS 2024. He serves as an action editor of "Transactions of Machine Learning Research", and an area chair of major AI conferences (e.g., NeurIPS, ICML, AISTATS). He is the author of the book entitled "Deep Generative Modeling", the first comprehensive book on Generative AI.
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