About / CV


I am currently an MD PhD student at Mount Sinai's Medical Scientist Training Program (MSTP) and a postdoctoral fellow at NYU School of Medicine. I got my bachelor and master of science in engineering at the University of Pennsylvania before coming to New York. I was born in Seoul, South Korea and grew up in Toronto, Canada and Auburn, Alabama.

My goal is to become an academic radiologist and improve accessibility of machine learning and imaging techniques. I have research experiences in molecular imaging, radiation physics, computer vision, and artificial intelligence. I have been published in NeurIPS Proceedings (PMLR), Radiology: Artificial Intelligence (cover article Volume 3 Issue 2), Nature Medicine, Pediatrics, and more.

Clinically, I have worked as a certified EMT and a senior clinician in a student run, physician supervised clinic at Mount Sinai. Working with underserved communities inspired me to research methods to expand availability of radiology resources to all patients.

I fell in love with radiology, an exceptional intersection of technology and medicine, during a signals course lecture given by Andrew Maidment at The University of Pennsylvania. I completed my senior design project with him and developed methods to quantify and incorporate super resolution in digital breast tomosynthesis. I completed my master's thesis with Marni Falk at The Children's Hospital of Philadelphia and developed a technique to automate quantitation of fluorescent markers of mitochondrial physiology.

During my PhD training with Anthony Costa and Eric Oermann at Mount Sinai, I focused on developing an objective, quantitative metric to evaluate diagnostic utility of generative ML algorithms. I was part of an international federated learning project to improve the generalizability of a COVID-19 prognostication algorithm. I am continuing to work with Eric as a postdoc at the NYU OLAB to build standardized radiology datasets and create additional federated learning collaborations.

Young Joon Kwon CV.pdf


Cover Article of Radiology: Artificial Intelligence

April 2021 | Radiological Society of North America

Excellence in Teaching Award

May 2020 | Icahn School of Medicine at Mount Sinai
  • Award given to a student who has displayed outstanding teaching skills and has selflessly devoted significant time and energy to enhancing students' learning, generally through engagement in review sessions, labs, and tutoring.

RSNA Medical Student Research Grant

Apr 2020 | Radiological Society of North America
  • $6,000 grant that gives medical students the opportunity to gain research experience in medical imaging and a chance to consider academic radiology as a future career option.

Society of Interventional Radiology Medical Student Scholarship

Mar 2018 | Society of Interventional Radiology
  • Selected scholars attend the SIR Annual Scientific Meeting -- an experience that includes dedicated educational programming, presentations from leaders in the field of interventional radiology, and networking opportunities with IRs from across the world.

Bioengineering Senior Design Award

Apr 2016 | University of Pennsylvania
  • Award given to a graduating senior team who, in the conduct of its senior project, has best demonstrated originality and creativity in the application of engineering principles to the solution of a biomedical problem.

Herman P. Schwan Bioengineering Award

Apr 2016 | University of Pennsylvania
  • Award given to a graduating senior who, in the opinion of the faculty, has demonstrated the highest standards of scholarship and academic achievement.

SIMD Travel Award

Apr 2016 | Society of Inherited Metabolic Disorders


These manuscripts are categorized by fields of research on the publications page.

  1. Hu Y; Ko JP; Chen B; Knoll F; Alpert J; Brusca-Auguello G; Mason D; Wickstrom M; Kwon YJ; Babb J; Liang Z; Moore WH, Azour L.
    “Deep-Learning Denoising of Low-Dose CT Chest Images: Quantitative and Qualitative Image Analysis,”
    Clinical Imaging, 2022; Pub Status: Submitted.

  2. Cheung ATM, Nasir-Moin M, Kwon YJ, Guan J, Liu C, Jiang L, Raimondo C, Chotai S, Chambless L, Ahmad HS, Chauhan D, Yoon JW, Hollon T, Buch V, Kondziolka D, Chen D, Al-Aswad L, Aphinyanaphongs Y, Oermann EK.
    "Methods and Impact for using Federated Learning to Collaborate on Clinical Research,"
    Neurosurgery, 2022; Pub Status: Submitted.

  3. Valliani AA, Link KE, Costa AB, Kwon YJ, Lui YW, Kondziolka D, Oermann EK.
    "Medical Federated Learning Models Trained on Real-world Data Are Vulnerable to Attack and Human Error,"
    Sci Adv, 2022; Pub Status: Submitted.

  4. Valliani AA, Gulamali FF, Kwon YJ, Martini ML, Wang C, Kondziolka D, Chen VJ, Wang W, Costa AB, Oermann EK.
    "Deploying Deep Learning Models on Unseen Medical Imaging Using Adversarial Domain Adaptation,"
    PLOS ONE 2022; Pub Status: In Press.

  5. The EXAM Consortium*.
    "Federated Learning Used for Predicting Outcomes in SARS-COV-2 Patients,"
    Nature Medicine, 2021; Online ahead of print. Cited in PubMed; PMID: 34526699. Pub Status: Published.
    *Institutional team contributors: Costa AB, Kwon YJ, Oermann EK, Glicksberg BS.

  6. Guha S, Mathew ND, Konkwo C, Ostrovsky J, Kwon YJ, Polyak E, Seiler C, Bennett M, Xiao R, Zhang Z, Nakamaru-Ogiso E, Falk MJ.
    "Combinatorial glucose, nicotinic acid, and N-acetylcysteine therapy has synergistic effect in preclinical C. elegans and zebrafish models of mitochondrial complex I disease,"
    Hum Mol Genet, 2021; 30(7):536-551. Cited in PubMed; PMID: 33640978. Pub Status: Published.

  7. Kwon YJ, Toussie D, Finkelstein M, Cedillo MA, Maron SZ, Manna S, Voutsinas N, Eber C, Jacobi A, Bernheim A, Gupta YS, Chung MS, Fayad ZA, Glicksberg BS, Oermann EK, Costa AB.
    "Combining Initial Radiographs and Clinical Variables Improves Deep Learning Prognostication of Patients with COVID-19 from the Emergency Department,"
    Radiol Artif Intell, 2020; 3(2). Cited in PubMed; PMID: 33928257. Pub Status: Published.

  8. Vaid A, Jaladanki S, Xu J, Teng S, Kumar A, Lee S, Somani S, Paranjpe I, De Freitas JK, Wanyan T, Johnson KW, Bicak M, Klang E, Kwon YJ, Costa A, Zhao S, Miotto R, Charney AW, Bottinger E, Fayad ZA, Nadkarni GN, Wang F, Glicksberg BS.
    "Federated Learning of Electronic Health Records Improves Mortality Prediction in Patients Hospitalized with COVID-19,"
    JMIR Med Inform, 2020; 9(1):e24207. Cited in Pubmed; PMID: 33400679. Pub Status: Published.

  9. Kwon YJ, Toussie D, Azour L, Concepcion J, Eber C, Reina GA, Tang P, Doshi AH, Oermann EK, Costa AB.
    "Appropriate Evaluation of Diagnostic Utility of Machine Learning Algorithm Generated Images,"
    Proc Mach Learn Res, 2020; 136:179-193. Pub Status: Published.

  10. Kwon YJ, Toussie D, Reina GA, Tang P, Doshi AH, Oermann EK, Costa AB.
    "Multi-Level Vector Quantized Variational AutoEncoder as a Lightweight, Generalizable Medical Imaging Compression Algorithm,"
    Medical Imaging Meets NeurIPS, 2020; 27. Pub Status: Published.

  11. Mahmoudi K, Kwon YJ, Kihira S, Goldstein Y, Platt S, Garvey KL, Belani P, Rigney B, Naidich T, Costa AB, Doshi AH.
    "Body Mass Index Correlates with Skin to Spinal Canal Distance: A Large Retrospective Single-Center Study,"
    J Neuroimaging, 2020; 30(6):896-900. Cited in Pubmed; PMID: 32639650. Pub Status: Published.

  12. Grinberg D, Pozzi M, Bordet M, Nouhou KA, Kwon YJ, Obadia JF, Vola M.
    "Minithoracotomy and Beating Heart Strategy for Mitral Surgery in Secondary Mitral Regurgitation,"
    Thorac Cardiovasc Surg, 2019; 68(6):462-469. Cited in PubMed; PMID: 31242521. Pub Status: Published.

  13. Grinberg D, Le MQ, Kwon YJ, Fernandez MA, Audigier D, Ganet F, Capsal JF, Obadia JF, Cottinet PJ.
    "Mitral Valve Repair Based on Intraoperative Objective Measurement,"
    Sci Rep, 2019; 18;9(1):4677. Cited in PubMed; PMID: 30886234. Pub Status: Published.

  14. Guha S, Konkwo C, Lavorato M, Mathew ND, Peng M, Ostrovsky J, Kwon YJ, Polyak E, Lightfoot R, Seiler C, Xiao R, Bennett M, Zhang Z, Nakamaru-Ogiso E, Falk MJ.
    "Pre-clinical evaluation of cysteamine bitartrate as a therapeutic agent for mitochondrial respiratory chain disease,"
    Hum Mol Genet, 2019; 28(11):1837–1852. Cited in PubMed; PMID: 30668749. Pub Status: Published.

  15. Polyak E, Ostrovsky J, Peng M, Dingley SD, Tsukikawa M, Kwon YJ, McCormack SE, Bennett M, Xiao R, Seiler C, Zhang Z, Falk MJ.
    "N-acetylcysteine and vitamin E rescue animal longevity and cellular oxidative stress in pre-clinical models of mitochondrial complex I disease,"
    Mol Genet Metab, 2018; 123(4):449-462. Cited in PubMed; PMID: 29526616. Pub Status: Published.

  16. Kwon YJ, Guha S, Tuluc F, Falk MJ.
    "High-Throughput Biosorter Quantification of Relative Mitochondrial Mass and Membrane Potential in living C. elegans,"
    Mitochondrion, 2018; 40:42-50. Cited in PubMed; PMID: 28986305. Pub Status: Published.

  17. Kong J, Peng M, Ostrovsky J, Kwon YJ, Oretsky O, McCormick EM, He M, Argon Y, Falk MJ.
    "Mitochondrial function requires NGLY1,"
    Mitochondrion, 2018; 38:6-16. Cited in PubMed; PMID: 28750948. Pub Status: Published.

  18. Kwon YJ, Falk MJ, Bennett M.
    "Flunarizine Rescues Reduced Lifespan in CLN3 Triple Knock-Out Caenorhabditis elegans Model of Batten Disease,"
    J Inherit Metab Dis, 2017; 40(2):291-296. Cited in PubMed; PMID: 27766444. Pub Status: Published.

  19. Kwon YJ, Allen JL, Liu GT, McCormack SE.
    "Presumed pseudotumor cerebri syndrome after withdrawal of inhaled glucocorticoids,"
    Pediatrics, 2016; 137(6). Cited in PubMed; PMID: 27244842. Pub Status: Published.

  20. Lau KC, Kwon YJ, Aziz MK, Maidment AD.
    "Estimating breast thickness for dual-energy subtraction in contrast-enhanced digital mammography using calibration phantoms,"
    The International Society for Optics and Photonics, 2016; Paper 9783-11. doi: https://doi.org/10.1117/12.2214748. Pub Status: Published.

  21. Vent TL, Acciavatti RJ, Kwon YJ, Maidment AD.
    "Quantification of resolution in multiplanar reconstructions for digital breast tomosynthesis,"
    The International Society for Optics and Photonics, 2016; Paper 9783-1. doi: https://doi.org/10.1117/12.2216260. Pub Status: Published.

  22. Sheldon CA, Kwon YJ, Liu GT, McCormack SE.
    "An integrated mechanism of pediatric pseudotumor cerebri syndrome: Evidence of bioenergetic and hormonal regulation of cerebrospinal fluid dynamics,"
    Pediatr Res, 2015; 77(2): 282-9. Cited in PubMed; PMID: 25420176. Pub Status: Published.

  23. Peng M, Ostrovsky J, Kwon YJ, Polyak E, Licata J, Tsukikawa M, Marty E, Thomas J, Felix CA, Xiao R, Zhang Z, Gasser D, Argon Y, Falk MJ.
    "Inhibiting cytosolic translation and autophagy improves health in mitochondrial disease,"
    Hum Mol Genet, 2015; 24(17): 4829-47. Cited in PubMed; PMID: 26041819. Pub Status: Published.

  24. McCormack S, Polyak E, Ostrovsky J, Dingley S, Rao M, Kwon YJ, Xiao R, Zhang Z, Nakamaru-Ogiso E, Falk MJ.
    "Pharmacologic targeting of disordered NAD+ metabolism improves longevity in Caenorhabditis elegans mitochondrialcomplex I mutants,"
    Mitochondrion, 2015; 22: 45-59. Cited in PubMed; PMID: 25744875. Pub Status: Published.

  25. Dingley S, Polyak E, Ostrovsky J, Srinivasan S, Lee I, Rosenfeld A, Tsukikawa M, Xiao R, Selak M, Coon J, Hebert A, Grimsrud P, Kwon YJ, Pagliarini D, Gai X, Schurr T, Huttemann M, Nakamaru-Ogiso E, Falk M.
    "Mitochondrial DNA variant in COX1 subunit significantly alters energy metabolism of geographically divergent wild isolates in Caenorhabditis elegans,"
    J Mol Biol, 2014; 426(11):2199-216. Cited in PubMed; PMID: 24534730. Pub Status: Published.