Difference between revisions of "User:Muditdutta"

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==MATLAB Demonstration==  
 
==MATLAB Demonstration==  
The MATLAB demonstrations I find interesting include linear algebra operations such as taking the dot product or cross product of two vectors or taking the transpose of a matrix/vector. Also, more basic operations such as performing addition, subtraction, multiplication, or division on an element by element basis. This is useful when not desiring the real definition of matrix multiplication to be applied. Also, the ability for MATLAB to produce inverses of matrices or selecting particular rows/columns from an matrix in a few lines of code makes programming a very clear and efficient process. Lastly, several functions that permit one to analyze a matrix (such as determining its null space, rank, eigenvectors or trace) are not only useful in solving problems but also are applicable in numerous research undertakings that require plenty of data storage and analyzation.  
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The MATLAB demonstrations I find interesting include linear algebra operations such as taking the dot product or cross product of two vectors or taking the transpose of a matrix/vector. Also, more basic operations such as performing addition, subtraction, multiplication, or division can be executed on an element by element basis. This is useful when not desiring the real definition of matrix multiplication to be applied. Also, the ability for MATLAB to produce inverses of matrices or selecting particular rows/columns from an matrix in a few lines of code makes programming a very clear and efficient process. Lastly, several functions that permit one to analyze a matrix (such as determining its null space, rank, eigenvectors or trace) are not only useful in solving problems but also are applicable in numerous research undertakings that require plenty of data storage and analyzation.  
  
 
== External Links ==
 
== External Links ==
 
*[http://www.jacobsschool.ucsd.edu/news/news_releases/release.sfe?id=735 Nanowires May Boost Solar Cell Efficiency], UCSD Jacobs School of Engineering, updated 2014, accessed September 9, 2014 (Grand Challenge)
 
*[http://www.jacobsschool.ucsd.edu/news/news_releases/release.sfe?id=735 Nanowires May Boost Solar Cell Efficiency], UCSD Jacobs School of Engineering, updated 2014, accessed September 9, 2014 (Grand Challenge)

Revision as of 01:43, 15 September 2014

About me

I am a current freshman at Duke University. I'm enrolled in the Pratt School of Engineering as a prospective BME major. I graduated from Marjory Stoneman Douglas High School in South Florida.

Name Pronunciation

Although my parents pronounce my name differently, the easiest way for others to pronounce my name is the following: "Mud - it" : Consider it literally as two different words, "mud" and "it". Trust me, it saves quite a bit of trouble as opposed to saying my name as "moo-dit" or "mau-dit".

Current Courses

For the fall 2014 semester, I'm in these four classes:

  • EGR103 - Computational Methods in Engineering
  • MAT212 - Multivariable Calculus
  • CHEM201 - Organic Chemistry I
  • PSY103 - Developmental Psychology

Achievements

The only real significant thing I've done in high school is attain a title of semifinalist for the Siemens science fair competition. My lab partner (Sameer Pandhare) and I conducted research at Florida State University for about 6 weeks in a STEM program. We worked under associate professor Akash Gunjan, whose research primarily deals with histone proteins and how they respond to DNA damage.

MATLAB Demonstration

The MATLAB demonstrations I find interesting include linear algebra operations such as taking the dot product or cross product of two vectors or taking the transpose of a matrix/vector. Also, more basic operations such as performing addition, subtraction, multiplication, or division can be executed on an element by element basis. This is useful when not desiring the real definition of matrix multiplication to be applied. Also, the ability for MATLAB to produce inverses of matrices or selecting particular rows/columns from an matrix in a few lines of code makes programming a very clear and efficient process. Lastly, several functions that permit one to analyze a matrix (such as determining its null space, rank, eigenvectors or trace) are not only useful in solving problems but also are applicable in numerous research undertakings that require plenty of data storage and analyzation.

External Links