Changho Suh

Changho Suh 

Associate Professor
School of Electrical Engineering
KAIST

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 2021:

  • EE424 Introduction to Optimization, Tuesday and Thursday 14:30 – 15:45

  • KAIST Life Academy, Friday 14:00 – 18:00

  • HSS090 Happy College Life, Thursday 19:00 – 21:00

Office hours: Tuesday and Thursday 16:00 – 17:00 (during academic periods)

News (archive)

(Oct. 2021) YTN Science:

(Oct. 2021) Sisajournal:

(Oct. 2021) Guest Editor of the IEEE Journal on Selected Areas in Information Theory (JSAIT):

(Oct. 2021) Call for Contributions for IEEE Information Theory Newsletter

  • Deadline: October 31st

  • Share any ideas, initiatives, or potential contributions you may have in mind

  • Send contributions to the Newsletter Editor, Changho Suh <chsuh@kaist.ac.kr>

(Oct. 2021) Delivered an invited talk at KAST round table:

(Oct. 2021) A paper accepted in NeurIPS:

  • Y. Ro, K. Lee, S. E. Whang and C. Suh, ‘‘Sample selection for fair and robust training’’

(Sep. 2021) IEEE Information Theory Newsletter September Issue

(Sep. 2021) Launched KAIST Life Academy

(Sep. 2021) Delivered an invited talk at 2021 Halla Forum:

(Aug. 2021) Delivered an ILP lecture at KAIST:

(Aug. 2021) A paper accepted in RecSys (ComplexRec):

  • S. Kim, M. Jang and C. Suh, ‘‘Group match prediction via neural networks’’

(Aug. 2021) Delivered a 3-hour long tutorial at CSCIT

  • Fair machine learning

  • Slides: 1, 2, 3

  • Notes: 1, 2, 3

(Aug. 2021) Delivered an invited talk at KICS AI-Communication Workshop

  • Fair machine learning (slides)

(Aug. 2021) Delivered a 6-hour long tutorial at the Inaugural IEEE East Asian School of Information Theory

(Aug. 2021) General Chair of the Inaugural IEEE East Asian School of Information Theory (flyer)

  • 250 registered participants

Selected funding agencies

Selected publications

  1. J. Cho, G. Hwang and C. Suh, “A fair classifier using kernel density estimation,” NeurIPS, Dec. 2020 (Top 10 KAIST Research Achievements).

  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, media).

  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, IEIE Haedong Young Engineer Award).

  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).