Changho Suh

Changho Suh 

Associate Professor
School of Electrical Engineering
Korea Advanced Institute of Science and Technology

Room 912, N1 building
291 Daehak-ro, Yuseong-gu
Daejeon, South Korea, 34141

+82-42-350-7429
chsuh@kaist.ac.kr
Google Scholar Profile

Schedule

Teaching schedule for Fall 2020: EE424 Introduction to Optimization, Tuesdays and Thursdays 14:30 – 15:45
Office hours: Tuesdays and Thursdays 16:00 – 17:00 (during academic periods)

News

(Nov. 2020) Media exposure:

(Nov. 2020) Editor for the IEEE Information Theory Newsletter.

(Nov. 2020) Inspirational talk at KAIST:

  • Three stories for freshmen (youtube)

(Oct. 2020) My recent research featured in a media

(Oct. 2020) YKAST-ians featured in a media

(Oct. 2020) Won the Department Teaching Award:

  • EE321: Communication Engineering (Spring 2020, evaluation score: 4.88/5.0, review quotes).

(Oct. 2020) Won the Department TA Awards:

  • Minguen Kang: EE321 Communication Engineering (Spring 2020)

  • Jaewoong Cho: EE623 Information Theory (Fall 2019)

(Sep. 2020) Two papers accepted in NeurIPS 2020:

  • J. Cho, G. Hwang and C. Suh, ‘‘A fair classifier using kernel density estimation’’

  • A. Elmahdy, J. Ahn, C. Suh and S. Mohajer, ‘‘Binary matrix completion with hierarchical graph side information’’

(Sep. 2020) Delivered an invited talk at Edtech Korea Forum

(2020) Recognition

(2020) AI and Machine Learning Courses

  • June ~ Nov: SK-Hynix Machine Learning Course (16 days)

  • Dec: Hyundai Motor Machine Learning Course (10 days)

  • Oct: LG Display AI Course (1 day)

  • Oct: Hyundai Motor Machine Learning Course (10 days)

  • Aug: Seongnam-KAIST Machine Learning Course (2 days)

  • July: AI Camp for middle/high school teachers (1 day)

  • May: Seongnam-KAIST Machine Learning Course (2 days)

(2020) Talks

  • July: Invited talk at SPCOM (“FR-Train: Fair and robust training via information theory”)

  • Mar: Invited talk at University of Minnesota ECE (“Fundamental limits and efficient algorithms for machine learning”)

  • Feb: Invited talk at UC Irvine EECS (“Matrix completion with graph side information”)

  • Feb: Invited talk at ITA (“A fair classifier using mutual information”)

(2020) Papers

(2019) Recognition

(2019) Papers

(2019) Talks

  • Sep: Two-day lectures for Samsung Machine Learning Course

  • July: Three-day lectures for SK-Hynix Machine Learning Course

  • June: Invited talk at NUS (“Learn to identify dangerous vehicle using a computer game”)

  • June: Invited talk at NUS (“Matrix completion with graph side information”)

  • May: Invited talk at LSIT (video) ("Matrix completion with graph side information)

  • Mar: Invited talk at Samsung Medical Center (“Search engine for medical images”)

  • Mar: Invited talk at AFOSR (“Interpretable collision avoidance systems for autonomous driving”)

  • Feb: Invited talk at ITA (“Match prediction from group-wise comparisons”)

Acknowledgments

Selected publications

  1. Y. Roh, K. Lee, S. Whang and C. Suh, “FR-Train: A mutual information-based approach to fair and robust training”, ICML, Vienna, Austria, July 2020.

  2. H. Kim, K. Lee, G. Hwang and C. Suh, “Crash to not crash: Learn to identify dangerous vehicles using a simulator”, AAAI, Honolulu, USA, Jan. 2019 (oral presentation, website, article).

  3. K. Ahn, K. Lee, H. Cha and C. Suh, “Binary rating estimation with graph side information”, NeurIPS, Montreal, Canada, Dec. 2018.

  4. C. Suh, J. Cho and D. Tse, “Two-way interference channel capacity: How to have the cake and eat it too”, IEEE Transactions on Information Theory, vol. 64, no. 6, pp. 4259–4281, June 2018.

  5. S. Mohajer, C. Suh and A. Elmahdy, “Active learning for top-K rank aggregation from noisy comparisons”, ICML, Sydney, Australia, Aug. 2017.

  6. Y. Chen, G. Kamath, C. Suh and D. Tse, “Community recovery in graphs with locality”, ICML, New York, USA, June 2016.

  7. Y. Chen and C. Suh, “Spectral MLE: Top-K rank aggregation from pairwise comparisons”, ICML, Lille, France, July 2015 (Bell Labs Prize finalist).

  8. C. Suh, M. Ho and D. Tse, “Downlink interference alignment”, IEEE Transactions on Communications, vol. 59, no. 9, pp. 2616–2626, Sep. 2011 (IEEE Communications Society Stephen O. Rice Prize in 2013).

  9. C. Suh and D. Tse, “Feedback capacity of the Gaussian interference channel to within 2 bits”, IEEE Transactions on Information Theory, vol. 57, no. 5, pp. 2667–2685, May 2011 (IEEE ISIT Best Student Paper Award).

  10. C. Suh and K. Ramchandran, “Exact-repair MDS code construction using interference alignment”, IEEE Transactions on Information Theory, vol. 57, no. 3, pp. 1425–1442, Mar. 2011 (IEEE ISIT Best Student Paper Award finalist).