Dorukhan Sergin

Dorukhan Sergin

Machine Learning Engineer/Scientist

Biography

Hi! I’m so glad you found this website! I hope you find interesting stuff in here. My name is Dorukhan and I build machine learning products for a living. After getting my PhD in Industrial Engineering at Arizona State University (with a focus on Machine Learning), I decided to move onto the industry to be more hands-on with building machine learning-driven products.

This blog is meant to serve two purposes: (1) my public journal of ideas and opinions, (2) a collection of my learnings that I want to share publicly. If there are topics that you think I might be the right person to cover, please reach me out through LinkedIn or email.

Here are the stuff that I’m currently reading, thinking, pondering, wasting time about:

  • How can we expand from the scientific consensus on climate change and turn it into a global metanarrative so that we can start addressing it at a global scale?
  • What can we learn from the history about growing income inequality to make sure we make a smooth transition into a more equitable society?
  • Is there free will? (Yes, I’m still not over that topic.)
  • Machine Learning System Design best practices.
  • Opportunities for sailing in NYC!

Education

  • Ph.D. in Industrial Engineering, 2021 (Expected)

    Arizona State University

  • M.S. in Industrial Engineering, 2017

    Bogazici University

  • B.S. in Industrial Engineering, 2015

    Bogazici University

Experience

 
 
 
 
 

Research Scientist (Machine Learning)

Meta

Jan 2022 – Present New York, NY
 
 
 
 
 

Machine Learning Engineer

Landing AI

Aug 2021 – Jan 2022 Palo Alto, CA
 
 
 
 
 

Machine Learning Engineer Intern

Apple Inc.

Jun 2020 – Dec 2020 Cupertino, CA
 
 
 
 
 

Graduate Research Assistant

Arizona State University

Aug 2017 – Jun 2020 Tempe, AZ
 
 
 
 
 

Graduate Research Assistant

Bogazici University

Oct 2015 – Nov 2016 Istanbul/Turkey

Accomplish­ments

Deep Learning Specialization

See certificate

Recent Publications

(2021). Toward a Better Monitoring Statistic for Profile Monitoring via Variational Autoencoders. JQT Special Issue – Artificial Intelligence & Statistics for Quality Technology.

PDF

(2020). Tensor Completion for Weakly-Dependent Data on Graph for Metro Passenger Flow Prediction. AAAI.

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(2019). Image-based Process Monitoring via Adversarial Autoencoder with Applications to Rolling Defect Detection. IEEE CASE 2019.

PDF

Contact