Hyun-Myung Woo

Assistant Professor

Department of Biomedical & Robotics

Incheon National University

Educations

Ph.D. in Electrical & Computer Engineering, Texas A&M University (2022)

MS in Computer Science, Yonsei University (2010)

BA of Engineering, Yonsei University (2008)

Experience

Assistant Professor, Incheon National University Mar. 2023 - present

Research Associate, Brookhaven National Laboratory Sep. 2022 - Feb. 2023

Research Assistant, Texas A&M University Sep. 2017 - Dec. 2017 and Sep. 2019 - Aug 2022

Teaching Assistant, Texas A&M University Sep. 2015 - May 2016 and Sep. 2018 - May 2019

Research Engineer, LG Electronics Sep. 2016 - Mar. 2017

Lecturer, Yonsei University Mar. 2014 - Jun. 2014

Research Engineer, IDIS Jan. 2010 - Apr. 2014

Teaching Assistant, Yonsei University Mar. 2008 - Feb. 2010

Honor

2023 Academic Research Award, Incheon National University Mar. 2024

2023 Fall Excellence in Teaching Award, Incheon National University Mar. 2024

The Grand Prize, IDIS and ETNEWS Science and Technology & IT paper contest Dec. 2009

The Best Paper Award, KIIECT Fall Conference Oct. 2009

Summa Cum Laude, Yonsei University Feb. 2008

An Honor Prize for Academic Excellence, Yonsei University Fall 2005, and Spring 2006 and 2007

Scholarship for Academic Excellence for Academic Excellence, Yonsei University Fall 2005 - 2007

Openings

Our Computational Science Laboratory is currently accepting applications for Ph.D., MS, and Undergraduate research positions. These opportunities involve conducting cutting-edge research in mathematical optimization and machine/deep learning to address complex scientific and engineering challenges in fields such as bioinformatics, computational materials science, and applied mathematics. Interested candidates are encouraged to reach out via the contact page for further information.

Undergraduate Students

Taeyeong Jang

Jiho Han

Yoonsang Park

Accelerating Optimal Experimental Design using Deep Learning


Optimal Computational Screening Campaign for Science


Publications


Journals

[13] Hyun-Myung Woo, Xiaoning Qian, Li Tan, Shantenu Jha, Francis J. Alexander, Edward R. Dougherty, Byung-Jun Yoon, "Optimal Decision Making in High-Throughput Virtual Screening Pipelines," Patterns (2023).

[12] Qihua Chen, Xuejin Chen, Hyun-Myung Woo, and Byung-Jun Yoon, "Neural Message passing for Optimal Experimental Design in Complex Uncertain Systems," Engineering Applications of Artificial Intelligence 123 (2023): 106171.

[11] Hyun-Myung Woo¶, Omar Allam¶, Junhe Chen, Seung Soon Jang, and Byung-Jun Yoon, "Optimal high-throughput virtual screening pipeline for efficient selection of redox-active organic materials," iScience, 105735. (¶: Equally contributed author)

[10] Woo Seok Kim¶, M. Ibrahim Khot¶, Hyun-Myung Woo¶, Sungcheol Hong, Dong-Hyun Baek, Thomas Maisey, Brandon Daniels, Patricia Coletta, Byung-Jun Yoon, David Jayne, and Sung Il Park, "AI-enabled, implantable, multichannel wireless telemetry for photodynamic therapy," Nature Communications, 13, 2178 (2022). https://doi.org/10.1038/s41467-022-29878-1.(¶: Equally contributed author)

[9] Hyun-Myung Woo, Youngjoon Hong, Bongsuk Kwon, and Byung-Jun Yoon, "Accelerating Optimal Experimental Design for Robust Synchronization of Uncertain Kuramoto Oscillator Model Using Machine Learning," IEEE Transactions on Signal Processing, doi: 10.1109/TSP.2021.3130967.

[8] Hyun-Myung Woo and Byung-Jun Yoon, "MONACO: accurate biological network alignment through optimal neighborhood matching between focal nodes," Bioinformatics, btaa962.

[7] Minyu Gu, Daniel Vorobiev, Woo Seok Kim, Hung-Ta Chien, Hyun-Myung Woo, Sung Cheol Hong, and Sung Il Park. "A novel approach using an inductive loading to lower the resonant frequency of a mushroom-shaped high impedance surface," Progress In Electromagnetics Research M 90 (2020): 19-26. doi:10.2528/pierm19110607.

[6] Hyun-Myung Woo¶, Hyundoo Jeong¶, and Byung-Jun Yoon, "NAPAbench 2: A network synthesis algorithm for generating realistic protein-protein interaction (PPI) network families," Journal Article published 27 Jan 2020 in PLOS ONE volume 15 issue 1 on page e0227598. (¶: Equally contributed author)

[5] Hyun-Myung Woo, Jaekwon Kim, Joo-Hyun Yi, and Yong-Soo Cho, "Reduced complexity ML signal detection for spatially multiplexed signal transmission over MIMO systems with two transmit antennas," IEEE Trans. Veh. Tech., vol. 59, no. 2, pp. 1036-1041, February 2010.

[4] Hyun-Myung Woo, Jaekwon Kim, Joo-Hyun Yi, S. Y. Choi, and Yong-Soo Cho, "A Computationally Efficient ML Signal Detection Technique for MIMO Systems with Two Spatial Streams," SK Telecommun. Review Vol. 19-3, pp. 439-454, June 2009.

[3] Hoon Hur, Hyun-Myung Woo, Won-Young Yang, Seungjae Bahng, Youn-Ok Park, and Jaekwon Kim, "A computationally efficient search space for QRM-MLD signal detection," IEICE Trans. Commun. Vol. E92-B, no. 3, pp. 1045-1048, March 2009.

[2] Hoon Hur, Hyun-Myung Woo, S. J. Bahng, Y. O. Park, and Jaekwon Kim, "A Novel Soft Output Generation Method for Spatially Multiplexed MIMO Systems," KICS Journal Vol. 33-4, pp. 394-402, April 2008.

[1] Hoon Hur, Hyun-Myung Woo, W. Y. Yang, S. J. Bahng, Y. O. Park, and Jaekwon Kim, "An Improved Search Space for QRM-MLD Signal Detection," KICS Journal Vol. 33-4, pp. 403-410, April 2008.

Conferences

[9] Woo Seok Kim, Hyun-Myung Woo, M. Ibrahim Khot, Sungcheol Hong, David G. Jayne, Byung-Jun Yoon, and Sung Il Park, "AI-Enabled High-Throughput Wireless Telemetry for Effective Photodynamic Therapy," In 2021 55th Asilomar Conference on Signals, Systems, and Computers, pp. 811-815. IEEE.

[8] Hyun-Myung Woo and Byung-Jun Yoon, "Network-Based RNA Structural Alignment Through Optimal Local Neighborhood Matching," Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, Nov. 1-4, 2020.

[7] Hyun-Myung Woo, Woo Seok Kim, Sungcheol Hong, Vivekanand Jeevakumar, Clay M. Smithhart, Theodore J. Price, Byung-Jun Yoon, and Sung Il Park, "Machine Learning Enabled Adaptive Wireless Power Transmission System for Neuroscience Study," Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, Nov. 1-4, 2020.

[6] Hyun-Myung Woo, Hyundoo Jeong, and Byung-Jun Yoon, "Comprehensive Updates in Network Synthesis Models to Create An Improved Benchmark for Network Alignment Algorithms," Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics - BCB 2018.

[5] Hyun-Myung Woo, and Jaekwon Kim, "Reduced complexity ML signal detection for spatially multiplexed signal transmission over MIMO systems with two transmit antennas," KIIECT Fall Conference, Gumi-si, October 24, 2009.

[4] Hyun-Myung Woo, and Jaekwon Kim, "Reduced complexity ML signal detection for spatially multiplexed signal transmission over MIMO systems with two transmit antennas," KIISE, Gangwon Branch Conference, Wonju-si, June 12, 2009.

[3] Hyun-Myung Woo, Jaekwon Kim, J. H. Yi, and Yong-Soo Cho, "Reduced complexity ML signal detection for spatially multiplexed signal transmission over MIMO systems with two transmit antennas," JCCI, Gwangju, April 15 - 17, 2009.

[2] Hyun-Myung Woo, and Jaekwon Kim, "A Comparative Studies of Channel Shortening Techniques for OFDM System," KIIECT Summer conference, Kwandong Univ., Gangneung-si, June 13 - 14, 2008.

[1] Hoon Hur, Hyun-Myung Woo, W. Y. Yang, S. J. Bahng, Y. O. Park, and Jaekwon Kim, "An Improved Search Space for QRM-MLD Signal Detection," JCCI, Jeju-si, April 23 - 25, 2008.

Current Projects


Reinforcement Learning-based Optimal Decision Making in High-Throughput Virtual Screening (HTVS) Pipelines. The National Research Foundation of Korea (NRF) (2023~2025)

Knowledge Discovery using Machine Learning for the Objective-based Optimal Experimental Design. Incheon National University (2024~2025)

Previous Projects


Accelerating the Objective-based Optimal Experimental Design using Machine Learning. Incheon National University (2023~2024)

talks


[6] "Accelerating Objective-Driven Optimal Experimental Design using Machine Learning," @ Yonsei University Mirae Campus, Oct, 30, 2023.

[5] "Accelerating Objective-Driven Optimal Experimental Design using Machine Learning," @ Sungkyunkwan University, Apr, 24, 2023.

[4] "Optimal Decision Making in High-Throughput Virtual Screening Pipelines," BioSeminar @ Texas A\&M University, Apr, 29, 2022.

[3] "Optimal decision making for accelerating scientific discovery," Computational Science Initiative Seminar @ Brookhaven National Laboratory, Mar, 25, 2022.

[2] "Machine Learning Enabled Adaptive Wireless Power Transmission System for Neuroscience Study," BioSeminar @ Texas A&M University, Oct, 23, 2020.

[1] "Accurate biological network alignment through an iterative optimal mapping between neighborhood sets of focal nodes," BioSeminar @ Texas A&M University, Oct, 4, 2019.

Let's Get In Touch!


Please contact me if you may have any questions! :D