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--- qianyun_lu [2021/10/22 17:48] – [Qianyun "Savy" Lu] qylu
+++ qianyun_lu [2022/03/07 21:43] (current) – [Machine Learning for Circuits] qylu
@@ Line 1: / Line 1: @@
 ====== Qianyun (Savy) Lu ======
-{{:qianyun_lu.jpg?247|QianyunLu_Portrait}}\\
+{{:savy_selfie.jpeg?247|QianyunLu_Portrait}}\\
 BS, 2016, Southeast University, Nanjing, China
@@ Line 8: / Line 8: @@
 **Email:** savylu (AT) stanford (DOT) edu
-[[https://orcid.org/0000-0002-0466-5072|ORCID]] [[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://scholar.google.com/citations?user=ae3Nc-AAAAAJ&hl=en|Google Scholar]]
+[[https://orcid.org/0000-0002-0466-5072|ORCID]]
+[[https://publons.com/researcher/1881177/qianyun-lu/|Publons]]
+[[https://twitter.com/lu_qianyun/|Twitter]]
+[[https://www.linkedin.com/in/qianyun-savy-lu-20770816b/|LinkedIn]]
 $[hdcolor #04838c$]
-====== Machine Learning for Circuits ======
+====== tinymL ======
 $[/hdcolor$]
-Convolutional neural networks (CNNs) for image sensors.\\
+Ultra low power ML applications for IoT devices.\\
+====== 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]]