新万博体育下载_万博体育app【投注官网】

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Professur für Informatik in der 新万博体育下载_万博体育app【投注官网】izintechnik

  1. Universit?t
  2. Fakult?ten
  3. Fakult?t für Angewandte Informatik
  4. Institut für Informatik
  5. Lehrstühle und Professuren der Informatik
  6. Informatik in der 新万博体育下载_万博体育app【投注官网】izintechnik
  7. Muthuraman Muthuraman

Muthuraman Muthuraman

Prof.Dr.-Ing Muthuraman Muthuraman
Leitung
Professur für Informatik in der 新万博体育下载_万博体育app【投注官网】izintechnik
  • Raum F 2 116 (Geb?ude Standort "Alte Universit?t")
Kontakt (.vcf)

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Muthuraman Muthuraman was born in Chennai, India, in 1980. He received the B.E. degree in electronics and communication engineering from the 新万博体育下载_万博体育app【投注官网】 of Madras, Madras, India, in 2002, and the MS in digital communications in Christian Albrecht’s 新万博体育下载_万博体育app【投注官网】, Kiel, Germany in 2006. Ph.D. degree in biomedical engineering from the technical faculty and Department of Neurology of Christian Albrecht’s 新万博体育下载_万博体育app【投注官网】, Kiel, Germany, in 2010. In 2010, he joined the Department of Neurology, 新万博体育下载_万博体育app【投注官网】 of Kiel, as a Post-doc, and in 2013 became a senior post-doc. Since December 2016, he has been with the Department of Neurology, Johannes Gutenberg 新万博体育下载_万博体育app【投注官网】 Mainz, where he is an Assistant Professor, and the head of the department biomedical statistics and multimodal signal processing unit. Currently from 2024 he is heading the group Informatics for 新万博体育下载_万博体育app【投注官网】ical Technology (IMT) in Augsburg as an associate professor and second affiliation to Julius Maximilian university of Würzburg in the department of Neurology and head of the group Neural Engineering with Signal Analytics and Artificial Intelligence (NESA-AI). His current research interests include mathematical methods for time series analysis and source analysis on oscillatory signals, sleep, function of oscillatory activity in central motor systems, biomedical statistics, connectivity analyses, multimodal signal processing and analyses of EEG, MEG, fMRI and EMG, structural and network analyses on anatomical MRI and DTI, functional network analyses on PET imaging, machine learning and deep learning, network analyses on proteomic and genomic data, RNA, mRNA and Spatial transcriptomics.

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Selected publications (Peer reviewed)

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Google Scholar link for full list of publications:? https://scholar.google.de/citations?user=jNEENNkAAAAJ&hl=en

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Pubmed link for full list of publications:?https://pubmed.ncbi.nlm.nih.gov/?term=Muthuraman+M&sort=date

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  1. Fleischer V, Ciolac D, Gonzalez-Escamilla G, Grothe M, Strauss S, Galindo LSM, …, Wiendl H, Gold R, Bittner S, Zipp F, Groppa S* and Muthuraman M* and on behalf of the German Competence Network Multiple Sclerosis (KKNMS). Subcortical volumes as early predictors of fatigue development in multiple sclerosis. Ann Neurol. 2022 Feb;91(2):192-202. doi: 10.1002/ana.26290. Epub 2022 Jan 10.
  2. Bitar L?, Uphaus T?, Thalman C?, Muthuraman M, Gyr L, Ji H, Domingues M, Endle H, Groppa S, … Nitsch R?, Zipp F?*, Vogt J?*. Inhibition of the enzyme autotaxin rebalances overexcitation in stroke. Science Translational 新万博体育下载_万博体育app【投注官网】icine. 2022 In press.
  3. Muthuraman M, Ciolac D, Chirumamilla, VC. Translation of Functional Domain Abnormalities from Human to Mouse Motor System. Chapter III, Translational methods for multiple sclerosis research. Springer, Neuromethods 166 2021 doi.org/10.1007/978-1-0716-1213-2. Book Chapter.
  4. Fleischer V, Gonzalez-Escamilla G, Ciolac D, Albrecht P, Küry P, Gruchot J, Dietrich M, Hecker C, Müntefering T, Bock S, Oshaghi M, Radetz A, Cerina M, Kr?mer J, Wachsmuth L, Faber C, Lassmann H, Ruck T, Meuth SG*,?Muthuraman M*, Groppa S*. Translational value of choroid plexus imaging for tracking neuroinflammation in mice and humans.?Proc Natl Acad Sci U S A. 2021 Sep 7;118(36): e2025000118. doi: 10.1073/pnas.2025000118.
  5. Muthuraman, M, Bange M, Koirala N, Ciolac D, Pintea B, Glaser M, Tinkhauser G, Brown P, Deuschl G, Groppa S. Cross-frequency coupling between gamma oscillations and deep brain stimulation frequency in cortico-subcortical networks in Parkinson’s disease patients. Brain, 2020 Nov 5: awaa297. doi: 10.1093/brain/awaa297
  6. Muthuraman M, Fleischer V, Kroth J, Ciolac D, Radetz A, Koirala N, Gonzalez-Escamilla G, Wiendl H, Meuth SG, Zipp F, Groppa S. Covarying patterns of white matter lesions and cortical atrophy predict progression in early MS.?Neurol Neuroimmunol Neuroinflamm. 2020 Feb 5;7(3):e681.
  7. McMackin R, Muthuraman M, Groppa S, Babiloni C, Taylor J-P, Kiernan MC, Nasseroleslami B, Hardiman O. Measuring network disruption in neurodegenerative diseases: New approaches using signal analysis. Journal of Neurology, Neurosurgery and Psychiatry 2019: jnnp-2018-319581.
  8. Muthuraman M, Raethjen J, Koirala N, Anwar A, Mideksa K, Elble R, Groppa S, Deuschl G. Cerebello-cortical network fingerprints differ among essential, Parkinson and mimicked tremors. Brain 2018 Jun 1;141(6):1770-1781. (Selected as editor’s choice article for the issue)
  9. Anwar AR, Muthalib M, Perrey S, Galka A, Granert O, Wolff S, Heute U, Deuschl G, Raethjen J, Muthuraman M. Effective Connectivity of Cortical Sensorimotor Networks During Finger Movement Tasks: A Simultaneous fNIRS, fMRI, EEG Study. Brain Topogr 2016; 29(5): 645-60. (Awarded as the best paper of the year in brain topography)
  10. Muthuraman M, Deuschl G, Anwar AR, Mideksa KG, von Helmolt F, Schneider SA. Essential and aging-related tremor: Differences of central control. Mov Disord : official journal of the Movement Disorder Society 2015;30(12):1673-1680.

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