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qianyun_lu [2022/02/15 19:32] – [Qianyun (Savy) Lu] qyluqianyun_lu [2022/03/07 21:43] (current) – [Machine Learning for Circuits] qylu
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 **Email:** savylu (AT) stanford (DOT) edu **Email:** savylu (AT) stanford (DOT) edu
  
 +[[https://scholar.google.com/citations?user=ae3Nc-AAAAAJ&hl=en|Google Scholar]] 
 [[https://orcid.org/0000-0002-0466-5072|ORCID]]  [[https://orcid.org/0000-0002-0466-5072|ORCID]] 
 [[https://publons.com/researcher/1881177/qianyun-lu/|Publons]]  [[https://publons.com/researcher/1881177/qianyun-lu/|Publons]] 
-[[https://scholar.google.com/citations?user=ae3Nc-AAAAAJ&hl=en|Google Scholar]]  
-[[https://www.linkedin.com/in/qianyun-savy-lu-20770816b/|LinkedIn]] 
 [[https://twitter.com/lu_qianyun/|Twitter]] [[https://twitter.com/lu_qianyun/|Twitter]]
 +[[https://www.linkedin.com/in/qianyun-savy-lu-20770816b/|LinkedIn]]
  
    
 $[hdcolor #04838c$] $[hdcolor #04838c$]
-====== Machine Learning for Circuits ======+====== tinymL ======
 $[/hdcolor$] $[/hdcolor$]
  
-Convolutional neural networks (CNNs) for image sensors.\\+Ultra low power ML applications for IoT devices.\\ 
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 + 
 +====== Publications ====== 
 + 
 +  * Q. Lu and B. Murmann, "Improving the Energy Efficiency and Robustness of tinyML Computer Vision using Log-Gradient Input Images," to appear at tinyML Research Symposium, March 2022. [[https://arxiv.org/abs/2203.02571|URL]]

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