Difference between revisions of "Main Page"

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<big> '''Modeling and Identifying Neural Systems''' </big>
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<big>'''Sean G. Carver, Ph. D.'''</big>, Data Scientist, Modeler, and Mentor
  
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'''Instructor:''' <big> [http://limbs.lcsr.jhu.edu/User:Scarver Sean G. Carver, Ph.D.]</big>, Postdoctoral Fellow, Psychological and Brain Sciences, The Johns Hopkins University.
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* Research and Publication Interests
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::''Neuroscience, Sensorimotor Control, Posture Control, Sports Analytics, Precision Agriculture''
  
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'''Semester:''' Spring 2009.
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* [https://scholar.google.com/citations?hl=en&user=khxzFsAAAAAJ '''Peer Reviewed Publications''']
  
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'''Seventy-five Word Description:''' This course introduces the paradigms of computational neuroscience and develops skills for modeling neurons and networks of neurons.  The course teaches recent developments in neural system identification -- providing systematic tools for building models of neurons and networks based on experimental data.  Student's final projects will include original research testing these methods on simulated data.
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* [https://medium.com/@SeanCarverData '''Articles for Lay Audiences''']
  
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'''Background:''' Neural modeling is often pursued in an ad hoc way. Researchers add the mechanisms they know about, but need to wave their hands about the ones they don't.  They necessarily make many simplifying assumptions but often include many details that are not needed to parsimoniously capture the phenomena.  [[Background|'''More...''']]
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* [[Sean G. Carver's Teaching and Course Development|'''Teaching and Course Development''']]  
  
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'''Course Mechanics:''' This class will be a hands on experience.  Pending approval, class will meet twice a week in the Kreiger computer classroom.  Each meeting will last about 1.5 hours.  In addition, there will be three hours per week of supervised computer laboratory time.  Attendence during the laboratory time will be optional.  The purpose of the laboratory time is to allow students, if they choose, to complete computer assignments with the help of the instructor.  An effort will be made to design the weekly homework sets to allow most students to complete most of the homework during the laboratory time.  Grading will be determined 50% by weekly homework and 50% by final projects.  Presently, I am not planning exams.
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::''In Spring 2017, I taught [[Syllabus:_Stat_370_Spring_2017|''Introduction to Statistical Computing and Modeling'']] at American University.''
  
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Textbook, prerequisites and syllabus to be finalized soon.
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::''In Spring 2013, I taught Electronics and Instrumentation at Johns Hopkins.''
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::''In Spring 2009, I developed and taught at Johns Hopkins: [[ID_Course_Johns_Hopkins_Spring_2009|Modeling and Identifying Neurosystems]].''
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* [[Sean G. Carver's Textbook Collaborative Authoring|'''Textbook Collaborative Authoring''']]
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* [[Sean G. Carver's Biography|'''Biography''']]
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::''I received my Ph.D. in Applied Mathematics from Cornell University in 2003.  I later worked for the University of Maryland, Johns Hopkins University, Yale University, and Data Machines Corp.''
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::''I wrote: [[Media:The_Data_Professors_Guide_to_Basic_Statistics.pdf|The Data Professor's Guide to Basic Statistics]].
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* [https://www.linkedin.com/in/seancarverphd/ '''LinkedIn Profile''']
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* [https://github.com/seancarverphd '''GitHub Repo''']

Latest revision as of 01:16, 25 November 2025

Sean G. Carver, Ph. D., Data Scientist, Modeler, and Mentor

  • Research and Publication Interests
Neuroscience, Sensorimotor Control, Posture Control, Sports Analytics, Precision Agriculture
In Spring 2017, I taught Introduction to Statistical Computing and Modeling at American University.
In Spring 2013, I taught Electronics and Instrumentation at Johns Hopkins.
In Spring 2009, I developed and taught at Johns Hopkins: Modeling and Identifying Neurosystems.
I received my Ph.D. in Applied Mathematics from Cornell University in 2003. I later worked for the University of Maryland, Johns Hopkins University, Yale University, and Data Machines Corp.
I wrote: The Data Professor's Guide to Basic Statistics.
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