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Profile Details
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USD 120 /hr
Hire Dr. Kyongsik Y.
United States
USD 120 /hr

Machine learning technologist & data scientist previously co-founder of two medical device & signal processing companies

Profile Summary
Subject Matter Expertise
Services
Writing Technical Writing
Research Market Research, User Research, Meta-Research, Feasibility Study, Gap Analysis, Gray Literature Search
Consulting Digital Strategy Consulting, Scientific and Technical Consulting, Regulatory Consulting
Data & AI Predictive Modeling, Statistical Analysis, Algorithm Design-Non ML, Data Visualization, Big Data Analytics, Data Processing, Data Insights
Product Development Formulation, Product Evaluation, Prototyping
Work Experience

Technologist

NASA Jet Propulsion Laboratory

2015 - Present

Postdoctoral Scholar

California Institute of Technology

2010 - 2012

Education

PhD (Bioengineering)

Korea Advanced Institute of Science and Technology

2006 - 2010

BS (Bioengineering)

Korea Advanced Institute of Science and Technology

2002 - 2006

Certifications
  • Certification details not provided.
Publications
OTHER
Kyongsik Yun, Kyra H. Kim, Anshuman Pradhan, John Reager, Zhen Liu, Michael Turmon, Alexander Huyen, Thomas Lu, Venkat Chandrasekaran, Andrew Stuart (2021). Filling the gap: Estimation of soil composition using InSAR, groundwater depth, and precipitation data in California’s Central Valley .
JOURNAL ARTICLE
Yun, K., Oh, J., Hong, T.H., Kim, E.Y.(2021). Prediction of Mortality in Surgical Intensive Care Unit Patients Using Machine Learning Algorithms . Frontiers in Medicine. 8.
Yun, K., Bhattacharya, J., Sandkühler, S., Lin, Y.-J., Iwaki, S., Shimojo, S.(2020). Causally linking neural dominance to perceptual dominance in a multisensory conflict . NeuroReport. 31. (13). p. 991-998.
Oh, J., Yun, K., Chae, J.-H., Kim, T.-S.(2020). Association Between Macronutrients Intake and Depression in the United States and South Korea . Frontiers in Psychiatry. 11.
Oh, J., Oh, B.-L., Lee, K.-U., Chae, J.-H., Yun, K.(2020). Identifying Schizophrenia Using Structural MRI With a Deep Learning Algorithm . Frontiers in Psychiatry. 11.
Yun, K., Lee, J.S., Kim, E.Y., Chandra, H., Oh, B.-L., Oh, J.(2020). Severe COVID-19 Illness: Risk Factors and Its Burden on Critical Care Resources . Frontiers in Medicine. 7.
Kyongsik Yun, Jaekyu Choi, In-Uk Song, Yong-An Chung(2019). Smartphone-Based Point-of-Care Cholesterol Blood Test Performance Evaluation Compared with a Clinical Diagnostic Laboratory Method . Applied Sciences. 9. (16). p. 3334. {MDPI} {AG}
Yun, K., Choi, J., Song, I.-U., Chung, Y.-A.(2019). Smartphone-based point-of-care cholesterol blood test performance evaluation compared with a clinical diagnostic laboratory method . Applied Sciences (Switzerland). 9. (16).
Oh, J., Yun, K., Maoz, U., Kim, T.-S., Chae, J.-H.(2019). Identifying depression in the National Health and Nutrition Examination Survey data using a deep learning algorithm . Journal of Affective Disorders. 257. p. 623-631.
Kim, H., Kralik, J.D., Yun, K., Chung, Y.-A., Jeong, J.(2019). Neural Correlates of Public Apology Effectiveness . Frontiers in Human Neuroscience. 13.
Tavakoli, A.V., Yun, K.(2017). Transcranial alternating current stimulation (tACS) mechanisms and protocols . Frontiers in Cellular Neuroscience. 11.
Yun, K., Song, I.-U., Chung, Y.-A.(2016). Changes in cerebral glucose metabolism after 3 weeks of noninvasive electrical stimulation of mild cognitive impairment patients . Alzheimer's Research and Therapy. 8. (1). p. 1-9.
Park, S.A., Yun, K., Jeong, J.(2015). Reappraising abstract paintings after exposure to background information . PLoS ONE. 10. (5).
Song, M., Shin, Y., Yun, K.(2014). Beta-frequency EEG activity increased during transcranial direct current stimulation . NeuroReport. 25. (18). p. 1433-1436.
Lee, J., Yun, K.(2014). Alcohol reduces cross-frequency theta-phase gamma-amplitude coupling in resting electroencephalography . Alcoholism: Clinical and Experimental Research. 38. (3). p. 770-776.
Chung, D., Yun, K., Jeong, J.(2014). Decoding covert motivations of free riding and cooperation from multi-feature pattern analysis of EEG signals . Social Cognitive and Affective Neuroscience. 10. (9). p. 1210-1218.
Yun, K.(2013). On the same wavelength: Face-to-face communication increases interpersonal neural synchronization . Annals of Internal Medicine. 158. (6). p. 5081-5082.
Chib, V.S., Yun, K., Takahashi, H., Shimojo, S.(2013). Noninvasive remote activation of the ventral midbrain by transcranial direct current stimulation of prefrontal cortex . Translational Psychiatry. 3.
Yun, K., Park, H.-K., Kwon, D.-H., Kim, Y.-T., Cho, S.-N., Cho, H.-J., Peterson, B.S., Jeong, J.(2012). Decreased cortical complexity in methamphetamine abusers . Psychiatry Research - Neuroimaging. 201. (3). p. 226-232.
Yun, K., Watanabe, K., Shimojo, S.(2012). Interpersonal body and neural synchronization as a marker of implicit social interaction . Scientific Reports. 2.
Kim, S.-P., Kang, J.-H., Choe, S.-H., Jeong, J.W., Kim, H.T., Yun, K., Jeong, J., Lee, S.-H.(2012). Modulation of theta phase synchronization in the human electroencephalogram during a recognition memory task . NeuroReport. 23. (11). p. 637-641.
K. Yang-Tae, Y. Kyongsik, J. Jaeseung(2011). P.3.a.003 Abnormal local and long-range functional connectivity in schizophrenia during ultimatum game . European Neuropsychopharmacology. 21. p. S454--S455. Elsevier {BV}
Chung, D., Yun, K., Kim, J.H., Jang, B., Jeong, J.(2011). Different gain/loss sensitivity and social adaptation ability in gifted adolescents during a public goods game . PLoS ONE. 6. (2).
Yun, K., Chung, D., Jang, B., Kim, J.H., Jeong, J.(2011). Mathematically gifted adolescents have deficiencies in social valuation and mentalization . PLoS ONE. 6. (4).
CONFERENCE PAPER
Yun, K., Choi, C., Alimo, R., Davis, A., Forster, L., Rahmani, A., Adil, M., Madani, R.(2020). Multi-agent motion planning using deep learning for space applications . Accelerating Space Commerce, Exploration, and New Discovery Conference, ASCEND 2020.
Yun, K., Lu, T., Huyen, A.(2020). Transforming unstructured voice and text data into insight for paramedic emergency service using recurrent and convolutional neural networks . Proceedings of SPIE - The International Society for Optical Engineering. 11400.
Yun, K., Yu, K., Osborne, J., Eldin, S., Nguyen, L., Huyen, A., Lu, T.(2019). Improved visible to IR image transformation using synthetic data augmentation with cycle-consistent adversarial networks . Proceedings of SPIE - The International Society for Optical Engineering. 10995.
Lu, T., Huyen, A., Nguyen, L., Osborne, J., Eldin, S., Yun, K.(2019). Optimized training of deep neural network for image analysis using synthetic objects and augmented reality . Proceedings of SPIE - The International Society for Optical Engineering. 10995.
Yun, K., Nguyen, L., Nguyen, T., Kim, D., Eldin, S., Huyen, A., Lu, T., Chow, E.(2019). Small target detection for search and rescue operations using distributed deep learning and synthetic data generation . Proceedings of SPIE - The International Society for Optical Engineering. 10995.
Yun, K., Osborne, J., Lee, M., Lu, T., Chow, E.(2018). Automatic speech recognition for launch control center communication using recurrent neural networks with data augmentation and custom language model . Proceedings of SPIE - The International Society for Optical Engineering. 10652.
Yun, K., Bustos, J., Lu, T.(2018). Predicting rapid fire growth (flashover) using conditional generative adversarial networks . IS and T International Symposium on Electronic Imaging Science and Technology. p. 2751-2757.
Yun, K., Lu, T., Chow, E.(2018). Occluded object reconstruction for first responders with augmented reality glasses using conditional generative adversarial networks . Proceedings of SPIE - The International Society for Optical Engineering. 10649.
Yun, K., Stoica, A.(2017). Improved target recognition response using collaborative brain-computer interfaces . 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings. p. 2220-2223.
BOOK
Yun, K., Huyen, A., Lu, T.(2018). Deep neural networks for pattern recognition . Advances in Pattern Recognition Research. p. 49-79.