SHAOYEN TSENG, PhD

Deep Learning Data Scientist

Cognitive Computing Research, Intel Labs

Santa Clara, California

Hi and welcome!

I am a Deep Learning Data Scientist working in the Cognitive Computing Research group at Intel Labs.

I graduated with a PhD in 2020 from the Electrical and Computer Engineering Department at the University of Southern California where I performed research in the Signal Analysis and Interpretation Laboratory (SAIL) under the advisement of Professors Shrikanth Narayanan and Panayiotis Georgiou.

I received B.S. and M.Sc. degrees in electrical engineering from National Sun Yat-sen University (NSYSU), and National Chiao Tung University (NCTU), Taiwan, in 2008 and 2010, respectively. I also received a MS degree in Computer Science from USC in 2018.

My research interests are

Machine Learning / Deep Learning for :

  • Natural Language Processing

  • Speech and Audio Processing

  • Visual Commonsense Reasoning

  • Affective Computing

Education

University of Southern California, Los Angeles, United States

  • Ph.D. in Electrical Engineering - 2020

  • M.S. in Computer Science - 2018

National Chiao Tung University, Taiwan

  • M.S. in Electronics Engineering

  • Sept. 2008 to Dec. 2010

National Sun Yat-sen University, Taiwan

  • B.S. in Electrical Engineering

  • Sept. 2004 to June 2008

Work Experience

Deep Learning Data Scientist, Intel Labs

  • Feb 2021 to Present

Machine Learning Intern, Apple

  • June 2020 to Aug 2020

Deep Learning Intern in Speech, Samsung Semiconductor, San Diego

  • May 2018 to Aug. 2018

Deep Learning Intern in Audio Analytics, Robert Bosch Research and Technology Center, Pittsburgh

  • May 2017 to Aug. 2017

Advanced Engineer, Faraday Technology Corporation, Hsinchu, Taiwan

  • Feb. 2012 to July 2014

Intern, National Chip Implementation Center, Hsinchu, Taiwan

  • July 2008 to Sept. 2008

Selected coursework at USC

  • Machine Learning from Signals: Foundations and Methods

  • Advanced Natural Language Processing

  • Affective Computing

  • Mathematical Pattern Recognition

  • Foundations of Artificial Intelligence

  • Analysis of Algorithms