35岁了,转去谷歌做人工智能靠谱吗?

35岁了,转去谷歌做人工智能靠谱吗?

原创: Cottbuser 湾区人工智能 1周前

作者:Cottbuser 会多国语言的海归 
公众号:湾区人工智能
微博:湾区人工智能
知乎:湾区人工智能
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每个程序员都有一个谷歌梦,看看这位电工是如何逆袭,争取谷歌的工作机会。

其实他的大学7年都是在研究电,只有博士才开始搞了5年计算机。人生浪费几年,走点弯路,很正常,只要意识到错了,及时修改路线都没有问题。把时间拉长了,回头看,修改路线的决定肯定是对的。不能一直在错误的电工专业浪费青春。

这个台湾人牛逼之处在于能够克服传统思维的阻力,去实现心中的梦想,做自己想做的事情。主要成果就是两个专利,几篇论文。一个语义分割模型让我认识了他。从我认识的几十个台湾人来看,他很台湾。

博士毕业都35岁的样子

硕士毕业两年后才去读博士

本科毕业两年才去美国读硕士

你工作两年后还能拿起书本吗?你结婚,生娃后还有勇气继续去全职读书吗?30岁了才打算改行去实现编程梦想(或者突然醒悟到这是互联网的时代,码农的天下,不会编程未来就是文盲),这个勇气你有吗?放弃一切,从零开始,你愿意承担相应的沉没成本吗?随着潮流,跟着糊里糊涂结婚生子,你快乐吗?你孩子快乐吗?

此刻,我领悟到了一句话《你的心有多大,你拥有的世界就有多大》,开放的思想,冲破环境思维的束缚,敢于面对因为不合群而获得周遭质疑的勇气,高度自律的能力,和超强的执行力,是成为万人景仰的大牛的基本功。

这位大牛35岁才去谷歌当程序员,国内喊着30岁就被企业抛弃了,确实不太合理。其实,不是大龄程序员被抛弃,是年龄和能力不匹配才会被抛弃。

大牛头像,下面看简历吧

Liang-Chieh (Jay) Chen- Home Page

 

Liang-Chieh Chen台湾人,香港人,他们是不会大陆的拼音的,看看他们名字的拼音,还有街道名称,大学名称,反正我看不懂
Google LA 

Email: lcchen at cs dot ucla dot edu

About me我是谁

Since February 2016, I have been working at Google, Los Angeles.在谷歌工作

I finished my Ph.D. in Computer Science at UCLA under the supervision of Alan L. Yuille in November 2015.

My research interests include Computer Vision, Graphical Models, and Machine Learning.

News最新动态

  • An implementation and checkpoint for the best Dense Prediction Cell trained on Cityscapes have been released, which attains 82.7% on the test set.

  • DeepLabv3 checkpoints with MobileNet-v2 depth-multiplier=0.5 (pretrained on COCO and PASCAL VOC 2012) have been released, which targets at faster inference speed.

  • DeepLabv3+ was featured on Computer Vision News.

  • One paper (neural architecture search for dense image prediction) is accepted to NIPS 2018.

  • Two papers (DeepLabv3+ and PersonLab) are accepted to ECCV 2018.

  • Check out our latest work, PesonLab, on joint person instance segmentation and pose estimation.

  • Google AI blog about DeepLabv3+ open source.

  • Our DeepLabv3+ implementation in TensorFlow is publicly available now!

Education教育背景

  • Ph.D., Computer Science, University of California- Los Angeles, September 2010 - November 2015美国加州大学洛杉矶分校博士,计算机科学专业

  • M.S., Electrical Engineering: Systems, University of Michigan- Ann Arbor, September 2006 - June 2008美国密歇根大学安娜堡分校电气工程专业

    • Major: Signal Processing, Minor: Communication

  • B.S., Electronics Engineering, National Chiao-Tung University, Taiwan, September 2000 - June 2004台湾国立交通大学电子系本科(你能看出来是交通大学吗)反正我是靠度娘才翻译出来的

Papers论文

Searching for Efficient Multi-Scale Architectures for Dense Image Prediction 
Liang-Chieh Chen, Maxwell D. Collins, Yukun Zhu, George Papandreou, Barret Zoph, Florian Schroff, Hartwig Adam, Jonathon Shlens 
In Neural Information Processing Systems (NIPS), Montréal, Canada, December 2018. 
[preprint (arxiv: 1809.04184)] [code]

PersonLab: Person Pose Estimation and Instance Segmentation with a Bottom-Up, Part-Based, Geometric Embedding Model 
George Papandreou, Tyler Zhu, Liang-Chieh Chen, Spyros Gidaris, Jonathan Tompson, Kevin Murphy 
In European Conference in Computer Vision (ECCV), Munich, Germany, September 2018. 
[preprint (arxiv: 1803.08225)]

Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation 
Liang-Chieh Chen, Yukun Zhu, George Papandreou, Florian Schroff, Hartwig Adam
In European Conference in Computer Vision (ECCV), Munich, Germany, September 2018. 
[preprint (arxiv: 1802.02611)] [code]

MobileNetV2: Inverted Residuals and Linear Bottlenecks 
Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, Liang-Chieh Chen
In Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, Utah, USA, June 2018. 
[preprint (arxiv: 1801.04381)] [code]

MaskLab: Instance Segmentation by Refining Object Detection with Semantic and Direction Features 
Liang-Chieh Chen, Alexander Hermans, George Papandreou, Florian Schroff, Peng Wang, Hartwig Adam
In Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, Utah, USA, June 2018. 
[preprint (arxiv: 1712.04837)]

The Devil is in the Decoder 
Zbigniew Wojna, Vittorio Ferrari, Sergio Guadarrama, Nathan Silberman, Liang-Chieh Chen, Alireza Fathi, Jasper Uijlings 
In British Machine Vision Conference (BMVC), Imperial College London, September 2017. 
[pdf (arxiv: 1707.05847)]

Rethinking Atrous Convolution for Semantic Image Segmentation 
Liang-Chieh Chen, George Papandreou, Florian Schroff, Hartwig Adam 
Technical report 
[preprint (arxiv: 1706.05587)] [code]

DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs 
Liang-Chieh Chen*, George Papandreou*, Iasonas Kokkinos, Kevin Murphy, Alan L. Yuille (*equal contribution) 
Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
[preprint (arxiv: 1606.00915)] [project] [code]

Zoom Better to See Clearer: Human Part Segmentation with Auto Zoom Net 
Fangting Xia, Peng Wang, Liang-Chieh Chen, Alan L. Yuille
In European Conference in Computer Vision (ECCV), Amsterdam, Netherlands, October 2016. 
[preprint (arxiv: 1511.06881)]

Semantic Image Segmentation with Task-Specific Edge Detection Using CNNs and a Discriminatively Trained Domain Transform 
Liang-Chieh Chen, Jonathan T. Barron, George Papandreou, Kevin Murphy, Alan L. Yuille 
In Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, Nevada, USA, June 2016. 
[preprint (arxiv: 1511.03328)] [project] [code]

Attention to Scale: Scale-aware Semantic Image Segmentation 
Liang-Chieh Chen, Yi Yang, Jiang Wang, Wei Xu, Alan L. Yuille 
In Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, Nevada, USA, June 2016. 
[preprint (arxiv: 1511.03339)] [Test results on subset of MPII] [project] [code]

ABC-CNN: An Attention Based Convolutional Neural Network for Visual Question Answering 
Kan Chen, Jiang Wang, Liang-Chieh Chen, Haoyuan Gao, Wei Xu, Ram Nevatia 
Technical Report 
[preprint (arxiv: 1511.05960)]

Weakly- and Semi-Supervised Learning of a Deep Convolutional Network for Semantic Image Segmentation 
George Papandreou*, Liang-Chieh Chen*, Kevin Murphy, Alan L. Yuille 
(*equal contribution) 
International Conference on Computer Vision (ICCV), Santiago, Chile, December 2015. 
[preprint (arxiv: 1502.02734)] [spotlight] [project] [code]

Learning Deep Structured Models (oral)
Liang-Chieh Chen*, Alexander G. Schwing*, Alan L. Yuille, Raquel Urtasun 
(*equal contribution) 
International Conference on Machine Learning (ICML), Lille, France, July 2015. 
[pdf] [talk]

Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs 
Liang-Chieh Chen*, George Papandreou*, Iasonas Kokkinos, Kevin Murphy, Alan L. Yuille 
(*equal contribution) 
International Conference on Learning Representations (ICLR), San Diego, California, USA, May 2015. 
[pdf (arXiv:1412.7062)] [project] [code]

Beat the MTurkers: Automatic Image Labeling from Weak 3D Supervision 
Liang-Chieh Chen, Sanja Fidler, Alan L. Yuille, Raquel Urtasun 
In Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, Ohio, USA, June 2014. 
[pdf] [Supplementary Doc] [project] [CAD models]

Modeling Image Patches with a Generic Dictionary of Mini-Epitomes 
George Papandreou, Liang-Chieh Chen, Alan L. Yuille 
In Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, Ohio, USA, June 2014. 
[pdf] [Supplementary Doc]

Learning a Dictionary of Shape Epitomes with Applications to Image Labeling 
Liang-Chieh Chen, George Papandreou, Alan L. Yuille 
In International Conference on Computer Vision (ICCV), Sydney, Australia, Dec. 2013. 
[pdf] [Supplementary Doc]

US Patents

  • Systems and Methods for Data Page Management of NAND Flash Memory Arrange- ments, November 2008 
    Liang-Chieh Chen and Xueshi Yang

  • Multi-Mode Encoding for Data Compression, February 2009 
    Liang-Chieh Chen and Xueshi Yang

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决心和意志是学好编程的关键。
生命不息,刷题不止!
程序员之路,别怂,就是干!

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