Haewon Jeong

Ph.D. Candidate,
Carnegie Mellon University

See my work

Work

I'm interested in solving real-world problems using tools from: Information Theory, Coding Theory, Signal Processing, Statistics. These days, I'm focused on speeding up distirbuted/cloud algorithms by applying ideas in Coding Theory [6-11].
I am being advised by Prof. Pulkit Grover.

Publications

  • [13] Haewon Jeong, Yaoqing Yang, and Pulkit Grover "Systematic Matrix Multiplication Codes" (ISIT 2019)
  • [12] Haewon Jeong and Pulkit Grover "Energy-adaptive Error Correcting For Dynamic and Heterogeneous Networks" (Proceedings of the IEEE)
  • [11] Yuk Wong, Yuqiu Zhang, Haewon Jeong, and Pulkit Grover “Robust Molecular Dynamics Simulations Using Coded FFT Algorithm" (To be presented at IEEE ICASSP 2019)
  • [10] Haewon Jeong, Utsav Sheth, Sanghamitra Dutta, Malhar Chaudhari, Yaoqing Yang, Jukka Kohonen, Teemu Roos, and Pulkit grover, “An Application of Storage-Optimal MatDot Codes for Coded Matrix Multiplication: Fast k-Nearest Neighbors Estimation" (IEEE Big Data 2018)
  • [9] Haewon Jeong, Fangwei Ye, and Pulkit grover, “Locally Recoverable Coded Matrix Multiplication", (Allerton 2018)
  • [8] Haewon Jeong, Tze Meng Low, and Pulkit Grover, “Masterless Coded Computing: A Fully-Distributed Coded FFT Algorithm", (Allerton 2018)
  • [7]Sanghamitra Dutta, Ziqian Bai, Haewon Jeong, Tze Meng Low, and Pulkit Grover, “A Unified Coded Deep Neural Network Training Strategy based on Generalized PolyDot codes,” (ISIT 2018, extended version in preparation for Trans.IT)
  • [6] Haewon Jeong, Sanghamitra Dutta, Mohammad Fahim, Farzin Haddadpour, Viveck Cadambe, Pulkit Grover “On the Optimal Recovery Threshold of Coded Matrix Multiplication" (Allerton 2017, extended version submitted to Trans.IT)
  • [5] Haewon Jeong, Chris Blake, and Pulkit Grover, “Energy-Adaptive Polar Codes: Trading off Reliability and Decoding Enegy with Adaptive Polar Coding Circuits”, (ISIT 2017, Full Version)
  • [4]Pulkit Grover, Shawn Kelly, Jeff Weldon, Praveen Venkatesh and Haewon Jeong, “An information theoretic technique for harnessing attenuation of high spatial frequencies to design ultra-highdensity EEG”, Annual Allerton Conference on Communication, Control, and Computing 2015 (Allerton 2015)
  • [3] Haewon Jeong and Pulkit Grover, “Energy-Adaptive Code”, Annual Allerton Conference on Communication, Control, and Computing 2015 (Allerton 2015)
  • [2] EunYoung Jeong, Shinae Woo, Muhammad Jamshed, Haewon Jeong, Sunghwan Ihm, Dongsu Han, and KyoungSoo Park, “mTCP: a Highly Scalable User-level TCP Stack for Multicore Systems”, (NSDI 2014)
  • [1] Haewon Jeong, Si-Hyeon Lee, Sae-Young Chung, “Flashcast”, (APCC 2012)

Teaching

  • Introduction to Machine Learning for Engineers (CMU 18-661, Fall 2018 and Spring 2019)
  • Wireless Communications (CMU 18-758, Fall 2017)
  • Introduction to Programming using Python (KAIST, Fall 2011 and Spring 2012)

Other Projects

  • Spatio-temporal Filtering for Epileptic Focus Localization
    This was course project for Convex Optimization class (Spring 2015, CMU). You can find my final poster here.
  • Dictionary Learning with LDPC codes
    This was course project for Machine Learning class (Spring 2015, CMU) with Yongjune Kim and Mark Whiting. You can find our final presentation pdf and video here: [pdf] [Video]
  • faceScrap: Scrapping useful information from your social media wall
    This is the final product from CS Project course (Fall 2013, KAIST).
  • ICISTS-KAIST: Internatianal Conference for the Integeration of Science, Technology, and Society
    I was an onganizer committee of this awesome conference in 2010 and 2011.

Travel

I like traveling.

Contact Me

haewonj at andrew dot cmu dot edu