Biography

I was originally trained as a medical device developer and innovator with expertise in signal processing and machine learning (ML) in the Dept. Biomedical Engineering, Yonsei University, South Korea. I worked on several medical device development projects, including cardiac pacemakers, automated external defibrillators, fetal hypoxia detection systems, wearable ECG monitors, etc. These projects required deep understanding of electrical and electronic engineering, biomedical sensors, computational algorithms, and human physiology. I was recognized for my innovation in this work with a Biennial Best Paper Award by the Korean Institute of Electrical Engineers in 2003 and with a Young Investigator Award by the International Federation for Medical and Biological Engineering in 2005 (Lee et al., 2005). One ML paper we published in 2005 has become the world’s second most cited paper in the area of support vector machine (SVM)-based arrhythmia classification (Song et al., 2005).

After obtaining my Ph.D. in 2006, I continued my research in medical device and ML algorithm development as an independent researcher. In 2006, I joined the Korea Institute of Oriental Medicine (KIOM), where I led a team to develop a robotic 3D-pulse analyzer in collaboration with the startup company DaeyoMedi Co. in Korea. Specifically, my team developed novel 3-D pulse pressure sensors, a robotic arm, and signal processing and ML algorithms and performed clinical trials to evaluate the analyzer and build up its clinical database. In 2009, I opened my first lab as an Assistant Professor in Dept. Biomedical Engineering, Daegu Haany University. From 2011 to 2012, after moving to the Dept. Biomedical Engineering, Yonsei University as a Research Professor, I was involved in a project aiming at developing a continuous positive airway pressure (CPAP) device for sleep apnea patients. During this period, I developed a few novel computational algorithms—one of them was patented and transferred to a medical device start-up, MEZOO in Korea (Lee et al., 2012).

In 2013, I started my career in the U.S. as a postdoc trainee at Johns Hopkins School of Medicine under mentorship of Joseph Finkelstein, M.D., Ph.D. I pursued this training path to expand my research to telemedicine for chronic disease patients. We provided telecare solutions including online patient education, home-healthcare devices, and real-time patient monitoring. In anticipation of the revolution in Artificial Intelligence (AI) and Big Data Analysis, I moved in 2015 to the Dept. Computer Science and Electrical Engineering at University of Maryland, Baltimore County, to study ML algorithms. After a short 5-month postdoc, I was promoted to Assistant Research Scientist (parallel to Assistant Professor). During this period, I developed two seminal computational algorithms, called kernel dictionary learning (DL) and online kernel DL (Lee and Kim, 2015; Lee and Kim, 2016). My kernel DL algorithm was applied to brain tumor segmentation in MR images (Lee and Kim, 2015).

In 2016, I joined the White lab in the Dept. Cell Biology at UT Southwestern Medical Center to contribute to high-throughput cancer drug screening projects, in which multiple institutes collaborated to computationally determine the mechanism of action by natural products in killing cancer cells. We integrated gene expression and image data of treated cells to identify novel cancer drug candidates in natural product libraries. Meanwhile, as a part of the AstraZeneca-Sanger Drug Combination DREAM Consortium, I also developed ML models for predicting cancer drug combination responses based on a patient’s genome (Menden et al., 2019). In 2017, I joined the Bioinformatics Core Facility (BICF) in a Senior Research Associate position. I supported a wide range of projects involving from computational analysis of biological, metabolomics, and NGS data (Wang et al., 2018; Henry et al., 2018; Bhave et al., 2020) to DL model development for clinical outcome predictions (Shah et al., 2020; Hallac et al., 2019). I was promoted to Assistant Professor at Lyda Hill Department of Bioinformatics in December, 2020. With research career focused on adopting ML to the full spectrum of the biomedical field, I have been contributing to BICF’s mission of serving UTSW community with reliable and innovative computational solutions.

Education

Graduate School
Yonsei University (1999), Engineering
Graduate School
Yonsei University (2006), Engineering
Undergraduate
(2016), Biomedical Engineering
Graduate School
(2016), Biomedical Engineering
Graduate School
(2016), Biomedical Engineering

Research Interest

  • Computational methods for multi-modal and multi-omics data analysis
  • Deep Learning model for medical image analysis and clinical outcome prediction
  • Machine Learning based biomarker discovery and outcome prediction
  • Single cell RNA-seq analysis and related computational algorithms

Publications

Featured Publications LegendFeatured Publications

restrains pancreatic neoplasia formation.
Wang SC, Nassour I, Xiao S, Zhang S, Luo X, Lee J, Li L, Sun X, Nguyen LH, Chuang JC, Peng L, Daigle S, Shen J, Zhu H Gut 2018 Oct
Truncated APC Mutation Induces Asef Activated Golgi Fragmentation.
Kim SB, Zhang L, Yoon J, Lee J, Min J, Li W, Grishin NV, Moon YA, Wright WE, Shay JW Mol. Cell. Biol. 2018 Jun
Normative Values of Short-Term Heart Rate Variability Parameters in Koreans and Their Clinical Value for the Prediction of Mortality.
Lee CH, Lee JH, Son JW, Kim U, Park JS, Lee J, Shin DG Heart Lung Circ 2018 May 27 5 576-587
Online kernel dictionary learning on a budget
Jeon Lee, Seung-Jun Kim 50th Asilomar Conference on Signals, Systems and Computers 2016
Brain tumor image segmentation using kernel dictionary learning.
Jeon LeeSeung-Jun KimRong ChenHerskovits EH, Annu Int Conf IEEE Eng Med Biol Soc 2015 Aug 2015 658-61

Books

Featured Books Legend Featured Books

Honors & Awards

  • Silver medal, RSNA Intracranial Hemorrhage Detection
    Kaggle computational challenge (2019)
  • Silver medal, SIIM-ACR Pneumothorax Segmentation
    Kaggle computational challenge (2019)
  • Lyda Hill Award, U-HACK MED 2018
    UTSW biomedical hackathon competition (2018)
  • Contribution Award
    The Institute of Electronics and Information Engineers, Korea (2012)
  • Best Paper Presenter
    BME2008 Hong Kong (2008)
  • Best Researcher Award
    Korea Institute of Oriental Medicine (2008)
  • Young Investigator Award
    International Federation for Medical and Biological Engineering (2005)
  • Biennial Best Paper Award
    Korean Institute of Electrical Engineers (2003)

Professional Associations/Affiliations

  • Senior Member, Institute of Electrical and Electronics Engineers (IEEE) (2015)
  • Member, IEEE Engineering in Medicine and Biology Society (2012)