新的一期博士招生正式启动！本期我们将为大家介绍美国普渡大学电子工程系李海桐 NanoX 实验室招收人工智能硬件方向全奖博士生的相关信息。
Purdue ranks No. 4 by U.S. News in "2023 Best Engineering Schools", and No. 9 in "Best Electrical Engineering Programs". Purdue is a world leader in the field of microelectronics and is growing a strong R&D ecosystem with foundry and fabless near the campus. Purdue ECE alumni are well placed in both academia and industry globally.
Multiple fully-funded PhD positions are available for Fall 2023 in the NanoX Lab directed by Prof. Haitong Li at Purdue University. We work across the stack to realize energy-efficient electronic systems for ubiquitous machine intelligence, enabled by new nanotechnologies and their system integration. ‘ X ’ represents: ( a ) synergistic research at the intersection of devices, circuits, systems, and computational models; ( b ) diverse nanotechnologies to augment leading-edge silicon CMOS through integration. For prospective students with background and interests in nanoelectronics, VLSI circuits, and artificial intelligence, please visit our group website。
导师简介
Haitong Li is an Assistant Professor in the School of ECE at Purdue University. He obtained his Ph.D. and M.S. in Electrical Engineering from Stanford University advised by Prof. H.-S. Philip Wong, and B.S. in Microelectronics from Peking University. Haitong has published over 50 papers broadly on devices and circuits ( IEDM, VLSI, ISSCC, JSSC, Nature Electronics ) , as well as EDA and architectures ( DAC, DATE, ISCA ) . He has first-hand industry experience ( Meta, Arm ) and broad academia/industry collaborations.
招生信息
Our research group fosters passion, creativity, synergy, and is interdisciplinary and collaborative by nature. We cultivate the collective growth of the whole team, as we enter this new era of microelectronics where there are increasing global demands for a new generation of innovators traversing and blurring traditional boundaries.
We are mostly looking for students with passion, research background, and interests in the following areas:
Nanoelectronics: nanomaterials, semiconductor device fabrication, characterization, device modeling.
VLSI circuits: digital/analog circuit design, chip tape-out, domain-specific accelerators.
Machine learning, computational neuroscience, emerging application spaces ( e.g., AR/VR, autonomous systems, healthcare ) .
Meanwhile, beyond what ’ s mentioned above, we also believe that unique and diverse experiences can often generate new sparks to explore uncharted territory.
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