3-Minute Thesis Competition
10 Finalists will compete for prize money ($1000 to first place; $750 to second place; $500 to third place). Duke PhD students will share their research with a non-expert audience in 3 minutes.
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3-Minute Thesis Competition10 Finalists will compete for prize money ($1000 to first place; $750 to second place; $500 to third place). Duke PhD students will share their research with a non-expert audience in 3 minutes. |
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Enabling Resource-Efficient AI via SW-HW Co-designThe NSF AI Institute for Edge Computing (Athena) is pleased to present the next in the Seminar Series by Jong Hwan Ko, Kang Eun Jeon, Johnny Rhe, and Sangheum Yeon, titled "Enabling Resource-Efficient AI via SW-HW Co-design" on Wednesday, August 13, 2025, from 3-5pm EST in-person at Duke University Wilkinson Building Room 132, and via […] |
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Workplace Injuries & Your Role: A Guide to Duke’s Workers’ CompensationThis training provides an overview of how Pratt staff can influence key performance drivers within our self-insured, self-administered Workers' Compensation program. We'll also review Pratt-specific injury reporting and workers' compensation data from the past two years. Additionally, the session will cover unemployment claims management, with insights particularly relevant to HR staff, Business Managers, and others […] |
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Monday Coffee with Engineering StudentsStop by for a cuppa and meet some new friends. Monday, Aug 25, 10am-4pm, Teer 102 |
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Engineering Master’s Career Online Drop-In HoursEngineering Master's students: Attend Career Online Drop-In Hours to connect with a Career Coach for quick questions and feedback on your application documents. |
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Engineering Master’s Career Online Drop-In HoursEngineering Master's students: Attend Career Online Drop-In Hours to connect with a Career Coach for quick questions and feedback on your application documents. |
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Designing a hardware solution for deep neural network trainingThe size and complexity of recent deep learning models continue to increase exponentially, causing a serious amount of hardware overhead for training those models. Contrary to inference-only hardware, neural network training is very sensitive to computation errors; hence, training processors must support high-precision computation to avoid a large performance drop, severely limiting their processing efficiency. […] Engineering Master’s Career Online Drop-In HoursEngineering Master's students: Attend Career Online Drop-In Hours to connect with a Career Coach for quick questions and feedback on your application documents. |
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