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DTSTART;VALUE=DATE:20210104
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SUMMARY:Lifelong Learning: On Demand – Innovative Uses of Artificial Intelligence
DESCRIPTION:The Office of Alumni Relations is hosting “Lifelong Learning: On Demand – Innovative Uses of Artificial Intelligence”. Be introduced to a few innovative uses of AI in the fields of healthcare\, computers\, and robotics. Learn from Northeastern faculty experts Craig Johnson and Taskin Padir. This complimentary\, online program is available to you on demand from January 4 to 31. An opportunity to earn a non-credit digital badge is available. \nRegister Now
URL:https://coe.northeastern.edu/event/lifelong-learning-on-demand-innovative-uses-of-artificial-intelligence/
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20210127T130000
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DTSTAMP:20260517T032902
CREATED:20210119T202431Z
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SUMMARY:ECE Seminar: Dr. Jun Xiao
DESCRIPTION:Seminar Title: 2D Materials For Next-Generation Information Technology: From Functional Material Miniaturization To Energy-Efficient Phase Engineering \nLocation: Zoom Link \nAbstract: The emergence of artificial intelligence and 5G technology is transforming our world with novel applications such as the Internet of Things\, smart manufacturing\, and AI-empowered medical care. However\, this information revolution sets a massive demand for information capacity and energy supply. Such a big challenge urges innovations in device engineering and its material building blocks to boost information capacity and reduce energy consumption. In this talk\, I will focus on the exciting progress of the emergent 2D layered materials and their device engineering in this direction. First\, I will introduce our discovery of intrinsic 2D out-of-plane ferroelectricity in semiconducting In2Se3\, which holds great promise for ferroelectric device miniaturization. I will then present our electrostatic doping control innovation as a new energy-efficient mechanism for structural phase engineering in layered materials. I will further show how we utilize such technology to invent the non-volatile Berry curvature memory\, a new type of energy-efficient quantum devices. Inspired by these findings and techniques\, I will also briefly discuss the exciting future opportunities of leveraging the structure-property relationship and light-matter interactions in layered quantum materials and devices to boost the translation of novel quantum notions into technological advantages for energy-efficient neuromorphic computing\, robust quantum processing\, and biosensing. \nSpeaker Bio: Dr. Jun Xiao is a postdoctoral scholar working with Prof. Aaron Lindenberg in the Department of Materials Science & Engineering and Prof. Tony Heinz in the Department of Applied Physics at Stanford University. He earned his Ph.D. in Applied Science and Technology from UC Berkeley (2018) under Prof. Xiang Zhang’s supervision. His research experience and interests focus on leveraging quantum materials and devices for energy-efficient neuromorphic engineering\, robust quantum computing\, THz sensing\, and high-throughput manufacturing.
URL:https://coe.northeastern.edu/event/ece-seminar-dr-jun-xiao/
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DTSTART;TZID=America/New_York:20210127T150000
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CREATED:20210126T180728Z
LAST-MODIFIED:20210126T180728Z
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SUMMARY:AIX Seminar
DESCRIPTION:Please join us for our first AIX Seminar. \nLocation: Zoom Link \nSeminar 1 title: Allostasis and Interoception: Brain-Body Interactions and Implications for Robotics \nSpeakers: Dr. Karen Quigley\, Northeastern University\, and Dr. Erin Reilly\, Veteran Affairs \nAbstract: For much of the history of psychology\, sensation\, perception\, action\, emotion\, and cognition were studied as if they were separate\, biologically-defined faculties — they are not. A prominent current neuroscientific perspective (and variants thereof) suggest that a brain runs an internal\, predictive model or simulation of itself in the world. This model supports all functions achieved by a brain\, and in this view\, predictions constitute the internal model. Our lab has marshaled neuroanatomical evidence that predictions arise from visceromotor control regions in the brain to support anticipated action and other metabolically-costly functions such as learning. Collectively\, these anticipatory regulatory processes are called allostasis. Allostasis is the major task of a brain\, which utilizes 20% of the energetic budget of a human. A brain also requires a body\, which is the effector by which the brain supports maintenance of its own energetic needs. The internal model also is modified by prediction error arising from unanticipated inputs from both exteroceptive (e.g.\, vision) and interoceptive (e.g.\, viscerosensory) sources. Interoceptive sensations provide critical information to the brain about the status of the body\, enabling motor and visceromotor actions that can most efficiently support the brain’s energetic needs. Understanding these biological realities can bring new ideas to both the design of robots\, and also to our understanding of how to optimize humans-robot interactions. \n  \nSeminar 2 title: Improving Interaction using Intelligence \nSpeaker: Dr. Jaime Ruiz\, University of Florida \nAbstract: Adding intelligence to user interfaces provides unique opportunities to improve the way users interact with computing systems. In this talk\, I will give a broad overview of the types of projects undertaken by may lab. I will also highlight several projects that aim to use neration of multimodal interfaces.
URL:https://coe.northeastern.edu/event/aix-seminar/
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