(my publications are under both names M. Chung and M. Conrad)

  1. Q. Mu, V. Tavella, J. Kirby, T. Cecere, M. Chung, J. Lee, S. Li, S. Ahmed, C. Reilly, and X. Luo. Antibiotics Ameliorate Lupus-like Symptoms in Mice, (7)1:15675. Scientific Reports, 2017.
  2. S. Karunarathne, M. Chung, and J. A. Ogejo. Compartmental process-based model for estimating ammonia emission from liquid dairy manure storage tank. Proceedings of the 2017 ASABE Annual International Meeting, 2017.
  3. M. Chung, J. Krueger, and M. Pop. Robust Parameter Estimation for Biological Systems: A Study on the Dynamics of Microbial Communities. Mathematical Bioscience, 294:71-84, 2017. [Supplementary Matlab Code]
  4. A. Carracedo Rodriguez, M. Chung, and S. M. Ciupe. Understanding the complex patterns observed during hepatitis B Virus therapy. Viruses, (9)117:1-15, 2017.
  5. J. Chung and M. Chung. Optimal regularized inverse matrices for inverse problems. SIAM Journal on Matrix Analysis and Applications, 38(2):458-477, 2017. [arXiv Preprint]
  6. Robert Smith et al., Population Modelling Working Group, Population Modelling by Examples II, SCSC '16 Proceedings of the Summer Computer Simulation Conference (SummerSim), No. 51, Montreal, Quebec, Canada - July 24 - 27, 2016. Society for Computer Simulation International, 2016.
  7. Y. Zhao, M. Chung, B.A. Johnson, C.S. Moreno, and Q. Long. Hierarchical Feature Selection Incorporating Known and Novel Biological Information: Identifying Genomic Features Related to Prostate Cancer Recurrence. Journal of the American Statistical Association, 111(516):1427-1439, 2016.
  8. J. Chung, M. Chung, and D.P. O’Leary. Optimal regularized low rank inverse approximation. Linear Algebra and its Applications, 468, 260-269, 2015.
  9. J. Chung and M. Chung. An Efficient Approach for Computing Optimal Low-Rank Regularized Inverse Matrices. 30(11), 1-19, Inverse Problems, 2014.
  10. J. Chung and M. Chung. Computing Optimal Low-Rank Matrix Approximations for Image Processing. Published in IEEE Proceedings of the Asilomar Conference on Signals, Systems, and Computers. November 3-6, 2013, Pacific Grove, CA, USA, 2013.
  11. B. Göbel, K.M. Oltmanns, and M. Chung. Linking neuronal activity to the glucose metabolism. Theoretical Biology and Medical Modelling, 10(50), 1-19, 2013.
  12. M. Chung, B.A. Johnson and Q. Long. A Tutorial on Rank-based Coefficient Estimation for Censored Data in Small- and Large-Scale Problems. Statistics and Computing, 23(5), 601-614, 2013. [Supplementary Matlab Code]
  13. S. McClellan, M. Casey, and M. Chung. Coherent Pre-Distortion of Low-Frequency PLC Carriers. The Sixth International Conference on Communication Theory, Reliability, and Quality of Service. Conference Proceedings, 29-34, 2013.
  14. E. Haber, M. Chung, and F. Hermann. An effective method for parameter estimation with PDE constraints with multiple right hand sides. SIAM Journal on Optimization, 22(3), 739–757, 2012.
  15. J. Chung, M. Chung, and D.P. O’Leary. Optimal error filters for image deconvolution with data acquisition errors. Journal of Mathematical Imaging and Vision, 44(3), 336-374, 2012.
  16. M. Chung and E. Haber. Experimental design in biological systems. SIAM Journal on Control and Optimization, 50(1): 471–489, 2012.
  17. M. Chung and B. Göbel. Advances in Systems Biology, chapter Mathematical Modeling of the Human Energy Metabolism based on the Selfish Brain Theory, pages 425–440. Springer, 2012.
  18. B. Göbel, M. Chung, K.M. Oltmanns, A. Peters, and D. Langemann. Robust modeling of appetite regulation. Journal of Theoretical Biology, 291:65–75, 2011.
  19. J. Chung, M. Chung, and D.P. O’Leary. Designing optimal spectral filters for inverse problems. SIAM Journal on Scientific Computing, 33(6):3132–3152, 2011.
  20. M. Chung, B. Göbel, A. Peters, K.M. Oltmanns, and A. Moser. A mathematical model of the brain’s energy sensing. Journal of Biomedical Science and Engineering, 4:136–145, 2011.
  21. Q. Long, M. Chung, C.S. Moreno, and B.A. Johnson. Risk prediction for prostate cancer recurrence through regularized estimation with simultaneous adjustment for nonlinear clinical effects. Annals of Applied Statistics, 5(3):2003–2023, 2011.
  22. B.A. Johnson, Q. Long, and M. Chung. On path restoration for censored outcomes. Biometrics, 67, 2011.
  23. B. Göbel, D. Langemann, K.M. Oltmanns, and M. Chung. Compact energy metabolism model: Brain controlled energy supply. Journal of Theoretical Biology, 264(4): 1214–1224, 2010.
  24. M. Conrad and B. A. Johnson. A quasi-Newton algorithm for efficient computation of Gehan estimates. Technical Report, Emory University, Department of Biostatistics and Bioinformatics, TR-2010-02, 2010.
  25. M. Conrad, C. Hubold, B. Fischer, and A. Peters. Modeling the Hypothalamus-Pituitary-Adrenal system: homeostasis by interacting positive and negative feedback. Journal of Biological Physics, 35:149–162, 2009.
  26. L. Ramrath, J. Levering, M. Conrad, A. Thuemen, H. Fuellgraf, and A. Moser. Mathematical identification of a neuronal network consisting of GABA and DA in striatal slices of the rat brain. Computational and Mathematical Methods in Medicine, 10(4):273–285, 2009.
  27. J. Olesch, N. Papenberg, T. Lange, M. Conrad, and B. Fischer. Matching CT and ultrasound data of the liver by landmark constrained image registration. Proceedings of SPIE (7261) 1: 72610G, 2009.
  28. M. Conrad and N. Papenberg. Iterative adaptive Simpson and Lobatto quadrature in Matlab. Technical Report, Emory University, Department of Mathematics and Computer Science, TR-2008-012, 2008.
  29. A. Peters, M. Conrad, C. Hubold, U. Schweiger, B. Fischer, and H. L. Fehm. The principle of homeostasis in the hypothalamus-pituitary-adrenal system: new insight from positive feedback. American Journal of Physiology: Regulatory, Integrative and Comparative Physiology, 293(1):R83–R98, 2007.
  30. M. Conrad. Modellierung und Parameterschätzung endokriner Systeme (German). PhD thesis, Institute of Mathematics, University of Lübeck, 2006.
  31. M. Conrad, C. Hubold, B. Fischer, U. Schweiger, H.L. Fehm, and A. Peters. The principle of regulation (abstract). Experimental and Clinical Endocrinology & Diabetes, 113:490, 2005.
  32. H. Krüger, C. Hubold, M. Conrad, A. Peters, and H.L. Fehm. Responses of the LHPA-system to CRH stimulation in subjects with type 1 diabetes mellitus and obesity (abstract). Experimental and Clinical Endocrinology & Diabetes, 113:495–496, 2005.
  33. M. Conrad. Multiresolution on the sphere (abstract). In Konstantinos Daniilidis, Reinhard Klette, and Ales Leonardis, Imaging Beyond the Pin-hole Camera. 12th Seminar on Theoretical Foundations of Computer Vision, Number 04251 in Dagstuhl Seminar Proceedings. Internationales Begegnungs- und Forschungszentrum (IBFI), Schloss Dagstuhl, Germany, 2005.
  34. M. Conrad, C. Hubold, B. Fischer, and A. Peters. The selfish brain: A new model of the LHPA-system (abstract). Experimental and Clinical Endocrinology & Diabetes, 112:481–482, 2004.
  35. A. Peters, U. Schweiger, L. Pellerin, C. Hubold, K. M. Oltmanns, M. Conrad, B. Schultes, J. Born, and H.L. Fehm. The selfish brain: competition for energy resources. Neuroscience & Biobehavioral Reviews, 28(2):143–180, 2004.
  36. M. Conrad and J. Prestin. Tutorials on Multiresolution in Geometric Modelling. Chapter Multiresolution on the Sphere, pages 165-202. Springer, New York, 2002.
  37. M. Conrad. Approximation und Multiskalenzerlegung auf der Sphäre (German). Master thesis, Institute of Mathematics, University of Hamburg, 2001.

In progress & submitted

  1. M. Chung, M. Binois, R.B. Gramacy, D.J. Moquin, A.P. Smith, A.M. Smith. Parameter and Uncertainty Estimation for Dynamical Systems Using Surrogate Stochastic Processes. arXiv preprint arXiv:1802.00852, under review at SIAM/ASA UQ, 2018. [arXiv Preprint]
  2. L. Ruthotto, J. Chung, and M. Chung. Optimal Experimental Design for Constrained Inverse Problems. arXiv preprint arXiv:1708.04740, under review at SISC, 2017. [arXiv Preprint]
  3. J. Chung, M. Chung, J. T. Slagel, and L. Tenorio. Stochastic Newton and Quasi-Newton Methods for Large Linear Least-squares Problems. In preparation, 2018. [arXiv Preprint]
  4. S. Karunarathne, J. A. Ogejo, and M. Chung. Process-based Models for Estimating Emissions of Ammonia and Greenhouse Gases from Stored Liquid Dairy Manure: A Critical Review. Submitted to Environmental Science and Technology Journal, 2017.