Steven Euijong Whang

Photo by Hector Garcia-Molina

Biography

Steven E. Whang is an Associate Professor of Electrical Engineering at KAIST and jointly affiliated with the Kim Jaechul Graduate School of AI. His research interests include Responsible and Data-centric AI. Previously he was a Research Scientist at Google Research and co-developed the data infrastructure of the TensorFlow Extended (TFX) machine learning platform. Steven earned his PhD in Computer Science in 2012 from Stanford University. He is a Kwon Oh-Hyun Endowed Chair Professor (2020-2023) and received a Google AI Focused Research Award (2018, the first in Asia) and a Google Research Award (2022).

Curriculum Vitae (updated Jan. 2023)

Contact Information

  • Email: swhang {at} kaist {dot} ac {dot} kr

  • Phone: +82-42-350-7443

  • Office: N1-516

  • Lab: N1-519

Education

  • Postdoctoral Associate, Computer Science, Stanford University, Stanford CA, July 2012-Dec. 2012

  • Ph.D., Computer Science, Stanford University, Stanford CA, Sept. 2007-June 2012 (advisor: Prof. Hector Garcia-Molina)

  • M.S., Computer Science, Stanford University, Stanford CA, Sept. 2005-June 2007 (advisor: Prof. Jennifer Widom)

  • B.S., Computer Science, KAIST, Mar. 1999-Feb. 2003

Experience

  • Kwon Oh-Hyun Associate Professor, Electrical Engineering, KAIST, Sept. 2020-Present

  • Kwon Oh-Hyun Assistant Professor, Electrical Engineering, KAIST, Mar. 2020-Aug. 2020

  • Adjunct Professor, Graduate School of AI, KAIST, Nov. 2019-Present

  • Assistant Professor, Electrical Engineering, KAIST, Feb. 2018-Feb. 2020

  • Research Scientist, Google Research, Mountain View, CA, Dec. 2012-Jan. 2018

  • Research Intern, Yahoo! Research, Santa Clara, CA, June 2008-Dec. 2008

  • Research Intern, HP Labs, Palo Alto, CA, Summer 2007

Honors

  • KAIST EE Best Teaching Award, Oct. 2022
    EE477 Database and Big Data Systems, Spring 2022
    Number of
    students: 64, course rating: 4.84/5 (highest among all EE undergrad courses)
    Supported by a Google Cloud Platform (GCP) Education Grant

  • Google Research Award, June 2022
    Proposal: Fairness under correlation shifts

  • Kwon Oh-Hyun Endowed Chair Professor, Mar. 2020-Feb. 2023
    Among 4 in KAIST, 1 in KAIST EE

  • Google AI Focused Research Award, Oct. 2018-Sept. 2021
    First in Asia

  • KAIST EE Best Paper Award, July 2019
    Top-3 citations contributor to university ranking within KAIST EE

  • IEEE Senior Member, Apr. 2019

  • Best Paper Award, WebDB Workshop, May 2015

  • IBM PhD Fellowship, Mar. 2011-Feb. 2012

  • School of Engineering Fellowship, Stanford University, Sept. 2007-June 2008

  • Korea Foundation for Advanced Studies (KFAS) Fellowship, Sept. 2005-June 2007

  • KAIST President's Prize for Academic Excellence at Commencement, Feb. 2003

Professional Service

  • General Co-Chair: Workshop on Data Management for End-to-End Machine Learning (DEEM@ACM SIGMOD) (2021, 2020)
    Max. number of attendees in 2020: 123

  • Co-Chair: Google-KAIST Partnership (2019-2021)

  • PC Vice Chair: IEEE ICDE 2020 (Top-3 Database conference)

  • Tutorial Co-Chair: VLDB 2023 (Top Database conference)

  • Volunteers Co-Chair: ACM FAccT 2022

  • Program Vice Chair: KCC 2020

  • Panel Co-Chair: IEEE BigComp (2020-2022)

  • Demonstrations Co-Chair: AIMLSystems 2021

  • Publication Co-Chair: DASFAA 2020

  • Publicity Co-Chair: PAKDD 2017

  • Associate Editor: Distributed and Parallel Databases (DAPD) Journal (2020-2026)

  • Senior PC Member / Meta-Reviewer

    • IEEE ICDE 2020 (Top-3 Database conference)

    • AAAI 2023 (Top AI conference)

  • PC Member (Data Management):

    • ACM SIGMOD (2024, 2023, 2022, 2020, 2018, 2013-2015) (Top Database conference)

    • VLDB (2023, 2022, 2021, 2018, 2016, 2015) (Top Database conference)

    • IEEE ICDE (2022, 2021, 2017, 2015, 2014) (Top-3 Database conference)

    • TheWebConf (2019-2022) (Top Web conference)

    • EDBT (2022, 2016)

  • PC Member / Reviewer (Machine Learning)

    • ICML (2022) (Top Machine Learning conference)
      Outstanding Reviewer for 2022 (within top 10%)

    • ICLR (2023, 2022) (Top Machine Learning conference)

    • NeurIPS (2022, 2021) (Top Machine Learning conference)

    • IJCAI (Program Committee Board 2022-2024, 2021) (Top AI conference)

  • Journal Reviewer: VLDB Journal, IEEE TKDE, ACM TODS, ACM Computing Surveys, IEEE TOIT, Science Advances, IEEE VIS

Google-KAIST Partnership signing ceremony, July 2019

Fun Fact

I am an alum of KAIST swimming team KAORI

I did opening speeches (in Korean) for the 2018 and 2019 KAIST KAORI swimming competitions and also participated in the 2018 competition to win 3rd prize in the Freestyle relay with students.