ZHEN QIN ()

Ph.D. in Computer Science
Staff Machine Learning Engineer, Google Inc.
New York City, New York

Email: zqin001@cs.ucr.edu or {firstname+lastname}@google.com

2017.01- 2015.08 - 2017.01 2010.09 - 2015.06 2006.09 - 2010.06


What's NEW

Two papers accepted to NAACL 2024.

One paper accepted to SIGIR 2024.

One paper accepted to EMNLP 2023.

Two papers accepted to NeurIPS 2023.

One paper accepted to CIKM 2023.

One paper accepted to KDD 2023.

One paper accepted to SIGIR 2023.

OSS

Large scale ranking package Tensorflow-Ranking.
Composable learning to rank with JAX RAX.
Fast online learning package Vowpal Wabbit.

Bio

HI! My name is Zhen Qin. I am a Staff Machine Learning track Software Engineer at Google Research at New York, working on machine learning for search and recommender systems. My Linkedin is here.

I received my PhD degree in Computer Science from University of California, Riverside in 2015. I was pleased to do research in Dr.Christian Shelton (who is brilliant)'s group. Prior to coming to UCR, I obtained my Bachelor's degree in Information Engineering at Beijing University of Posts and Telecommunications (BUPT), in June 2010. I was a member of the Pattern Recognition and Intelligence System Laboratory there, working with Dr.Honggang Zhang.

Education

Work Experience

  • Staff Software Engineer, Machine Learning (01/2017 - present): Google Inc., New York, with Ranking Technology team at Google Research. Building state-of-art large scale search and recommendation algorithm and systems across Google.
  • Data Science Manager and Senior Data Scientist (08/2015 - 01/2017): Ticketmaster, Hollywood, CA. Contextual bandits, online learning, personalized recommendations, SEM (search engine marketing)
  • Software Engineering Intern (06/2014 - 09/2014): Google Inc., Mountain View, CA, with Dr. Shinko Cheng and Dr. Shengyang Dai. Made AutoAwesome under G+ photos more awesome.
  • Machine Learning Intern (06/2013 - 09/2013): eHarmony Matching Team, Santa Monica, CA, with Dr. Vaclav Petricek. Worked on Vowpal Wabbit (awesome large-scale online learning package) improvements.
  • Summer R&D Intern (06/2012 - 09/2012): Sharp Laboratories of America, Camas, Washington, with Dr. Peter van Beek. Worked on defect detection on LCD TV panels.

Research

My general research interests lie in machine learning and optimization methods, with various applications areas, such as recommender systems, information retrieval, healthcare, computer vision, data mining, and other industrial applications.

I served as a PC member for ICML, ICLR, NeurIPS, KDD, SIGIR, WWW, WSDM, ACL, CIKM, AAAI. I am a reviewer for Transactions on Machine Learning Research (TMLR), IEEE Transactions on Image Processing (TIP), IEEE Transanctions on Multimedia (TMM), IEEE Transactions on Circuits and Systems for Video Technology (CSVT), IET Computer Vision Journal, Computer Vision and Image Understanding (CVIU), Image and Vision Computing (IVC), Knowledge and Information Systems (KAIS), and International Conference on Image Processing (ICIP). I was an external reviewer for ICDM, SDM.

Publications (My Google Scholar profile is up-to-date.)

Misc

My hometown, Jinan.
How to pronounce Chinese names

Who has been here

Locations of visitors to this page
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