(lastest update: Aug. 2018)



2015-now,   Ph.D. candidate, EE, Princeton University, USA.

  • Efficient inference for deep neural networks
  • Latency driven deep neural network compression
  • Machine learning ensembles
  • Thesis advisor: Prof. Niraj K. Jha

2015-17,     M.A., EE, Princeton University, USA.

  • GPA: 3.88/4.00

2011-15,     B.Eng. (highest honor), EEE, Nanyang Technological University, Singapore.

  • GPA: 3.94/4.00, Minor in Business: GPA 4.00/4.00
  • Dean’s list for all 4 academic years
  • NTU President Scholar, with Distinction (3-year)
  • Honorable University Best Industrial-Orientation Prize
  • Gold Medal: Defence Science & Technology Agency Gold Medal (Best Final Year Project / Thesis)
  • Gold Medal: Thomson Asia Pacific Holdings Gold Medal (Best RF Circuits)


Invited Talk and Poster

  • H. Yin, 'Applied Machine Learning: From Theory to Practice', Invited Talk by IEEE Circuits and Systems Singapore Chapter & Centre for Infocomm Technology (INFINITUS), Singapore, Feb. 01, 2018.


  • H. Yin, 'A Health Decision Support System for Disease Diagnosis based on Wearable Medical Sensors and Machine Learning Ensembles', Poster at New Jersey Tech Concil's 'What's Next in Medical Devices' Forum, Princeton, Jun. 13, 2016.




05-09/2018     Research Intern, Machine Learning Group,  Alibaba Group, Sunnvale, CA, USA.

  • Hardware-aware low latency inference for deep neural networks 
    • Significantly reduce the inference latency
    • Compress the model sizes by one order of magnitude
    • Improve the accuracy 

05-09/2015     Project Manager, Pattern Discovery Technologies Inc., Singapore.

  • Machine-learning-based trend forecasting and vision for Port of Singapore Authority (PSA).


05-09/2014     Research Intern, Temasek Laboratories, Singapore.

  • FPGA-based real-time signal blind reconstruction
    • Multiband signal blind reconstruction based on multi-coset theory
    • 36-50% latency reduction
    • Paper publised in IEEE ISCAS-15


Teaching Assistant

  • (17-18 F') ELE364 Machine Learning for Predictive Data Analytics
  • (16-17 S') ELE464 Embedded Computing
  • (16-17)     Senior Thesis Assistant, Electrical Engineering, Princeton University.



Details in my Linkedin profile.

Copy and paste this code to your website.
Copy and paste this code to your website.