Michigan Engineering | University of Michigan A delegation from LG AI Research visited campus to review LG-funded projects in process and discuss future collaborations.
LG AI Research and CSE build on successful partnership
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U-M CSE research team advances to top five in Amazon Alexa Prize Simbot Challenge
The challenge is a means of pushing forward with their research into development of next-generation embodied AI agents.
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Diversity and inclusiveness are an essential part of the pursuit of AI at CSE
The Michigan AI Lab is focused on building a community of diverse viewpoints in an effort to reduce the bias we see in the exploding world of artificial intelligence.
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“It’s a supportive and collaborative environment” — making connections as a PhD student in and outside the classroom
U-M CSE PhD candidate Sarah Jabbour discusses how collaboration is centered in her experience as a graduate student.
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“It’s a supportive and collaborative environment” — making connections as a PhD candidate in and outside the classroom
U-M CSE PhD candidate Sarah Jabbour discusses how collaboration is centered in her experience as a graduate student.
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U-M, Schmidt Futures to partner on new AI research program
$10M will fund training for 60 postdoctoral fellows as part of international cohort.
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Decisive differences in healthcare AI
When decisions about your healthcare are informed by AI, bias in machine learning can have dire consequences. Ph.D. student Trenton Chang researches how inequities in healthcare delivery impact machine learning and AI.
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Six new projects funded by LG AI Research
The projects are a part of LG’s mission to advance AI such as Deep Reinforcement Learning, 3D Scene Understanding, and Reasoning with a Large-scale Language Model and Bias & Fairness related to AI ethics.
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U-M team reaches next phase of Amazon Alexa Prize SimBot Challenge
Team SEAGULL, led by doctoral student Yichi Zhang and advised by Prof. Joyce Chai, strives to develop embodied AI agents capable of attending to users’ needs, following natural language instructions, collaborating, and continuously improving through interaction.
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Prof. Xinyu Wang collaborates with UiPath to democratize automation
The two will collaborate on building new programming techniques that are accessible to non-experts and non-programmers.