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National Taiwan University (Electrical Eng)
City University of Hong Kong (Master's)
San Jose State University (Master's)
Currently, I am an adjunct professor at a University teaching Mechanical Dynamics and a Teaching Assistant in Physics Lab 1101.
I have worked in the Electronic Engineering field with Texas Instruments, Philips and Motorola. I have also worked in the Aerospace Engineering field with Ares Corporation for Nasa Johnson Space Center.
I like teaching and tutoring for the advancement of the career path of working students or students who are eager to pursue an engineering or science career.
I have seen students who have taken my courses to excel over a semester across the board. These include students who were failing first but caught on to the scientific methods and pass with flying colors in the end.
My key emphasis for success are: 1. Clear and Concise material; 2. Practice by homework and quizzes; 3. Clear and Detailed examples; 4. Personalized care.
I have taught students of many ethnic backgrounds and with different aptitudes, working or just studying for a certified course. Currently, I am an adjunct professor at a University teaching Mechanical Dynamics and a Teaching Assistant in Physics Lab 1101.
I have worked in the Electronic Engineering field with Texas Instruments, Philips and Motorola. I have also worked in the Aerospace Engineering field
In most cases, tutors gain approval in a subject by passing a proficiency exam. For some subject areas, like music and art, tutors submit written requests to demonstrate their proficiency to potential students. If a tutor is interested but not yet approved in a subject, the subject will appear in non-bold font. Tutors need to be approved in a subject prior to beginning lessons.
Interest and success in mathematics is the first step towards all scientific/engineering endeavors.
Algebra/Geometry is the starting point. It doesn't take long to grasp at the right way and the fastest way to handle algebra. It just takes a little motivation and time to do so. I'll motivate and step you through the processes and make you feel cool to be good at math!
As astronaut Bonnie Dunbar mentioned, as a nation we need to engage in educating our youths in the US, especially inspiring them to study mathematics and science.
I am eager to help adults of all age groups to start studying mathematics early.
Algebra 2 is one of the subjects to master before tackling higher mathematics.
I'm a 3 and a half year PhD student in Biophysics at UH. I have completed all core courses and electives in physics and biology to get up to this point. Biostatistics is a subtopic I took in a biotech elective.
I have been using C all along to different extents in my design, engineering, and teaching jobs. While contracting for Nasa I have been mainly using C++, C# and Java codes for data consolidation and solar array systems operations respectively.
In my Aerospace engineering, Physics and Bioengineering research and development work mostly Fedora and Ubuntu linux gcc and python are used.
I was born in Hong Kong and can speak and write fluent Chinese (Mandarin and Cantonese).
I know of excellent teaching material both written in English and Chinese I can use for teaching, and I can create my own as well.
I'm a US citizen able to teach in fluent English and am successfully teaching Science and Engineering classes at UH.
Computer Science is a vast topic. It is also very useful as most every one owns a computing device of some sort.
No doubt also that it is very useful also in the Sciences and Engineering fields.
My experiences in computer science include all of the years I have worked in various fields: Electronic microchip design using unix-based systems to produce netlists after synthesis and timing closure;
Design verification using various programming languages and in-house tools;
Academically using openmp on fortran and c computing quantum chemistry, molecular dynamics, plasma turbulence;
Have volunteered to teach several sessions at UHCL Computer Science department and am currently a member of the XSEDE community.
Differential Equations play important roles in all scientific disciplines.
Some special types of differential equations apply to different engineering fields, e.g.,
Navier-Stokes (NS) for Fluid Mechanics,
NS and Maxwell Equations for Plasma Physics,
Simultaneous Ordinary Differential Equations (ODE) for Biophysics,
and many others.
I have experiences in all of the above and in teaching some of the material in the classes I have taught at UH.
I have both a BSc and an MSc degree in Electrical Engineering and Electronic Engineering from the University of Taiwan and University of Hong Kong respectively. I have been working in the electronics industry for over 15 years doing microchip design work and also worked as a contractor for NASA on shuttle electronics.
I have been mainly using FORTRAN for some parts of my research, especially in fluid mechanics and nonlinear plasma propulsion physics for turbulence analyses.
In part of my biophysics research, a combination of FORTRAN, c, and python/perl are used for molecular dynamics simulation.
To speed up simulations as mentioned, openmp pragma were used to run fortran/c codes in
Top level codes are usually done in conjunction with matlab.
Geometry is a visualization in mathematics.
For instance, in molecular biology we look at the structure of solids through x-ray crystallography. In physics we look at the quantum aspects in molecular chemistry.
Differential geometric techniqunes study the curvature of space-time essential to multi-dimensional space in Einstein's theory.
Euler's polyhedron formulation F+V-E=2 is both simple and powerful. Anyone can be taught to use it easily.
Linear Algebra no doubt has a special place in bridging the Sciences and Engineering.
It is used everywhere in the use of simultaneous equations in algebra or in differential equations.
I have used it in aerospace navigational problems at Nasa, in the classes I taught in physics and aerospace mechanics. I use it a lot in control engineering.
It is catching on in the field of molecular biology where dynamical instability of protein/gene circuits can be analyzed using eigen values as well.
Matlab and Mathematica are both essential top level tools in all universities.
Matlab excel in the ease of programming but Mathematica excel in symbolic evaluations without the need of a symbolic toolbox as in Matlab.
Matlab is mainly used in colleges to teach algorithms including Runge Kutta for integrating differential equations.
I use Mathematica mostly in heavily formulated physics problems such as molecular spins and fractional calculus where equations are concise but complex.
It is always advisable for a student to be conversant in both languages.
Matlab is the programming language of choice for making top level design work in all aspects of Sciences and Engineering.
The drawback is mainly the pricing but most companies and universities have licenses in matlab.
I used matlab/python for top level RF design work at Philips Microelectronics and a lot of matlab codes at UH and MD Anderson Cancer Center. At Philips RF/Wifi/WirelessLan specifications in 802.11a,b,g,n top levels were written in Matlab.
My optimization codes for protein/gene discovery and gene regulation dynamics are written in Matlab as well.
Trained in Aerospace Engineering and worked for Nasa for over 3 years, I'm proficient in the mechanical engineering field. Currently I'm an Adjunct Professor teaching at the University of Houston college of technology in two courses helping students to design mechanical projects using Creo Parametric and 3D printing technologies.
Perl and Python are scripting software tools used independently or in conjunction to manage software.
Since Perl came before python, it presumably has a larger installed base.
I use perl predominantly on my electronic design and verification work (manipulating codes and netlists) that takes place within a unix/linux environment.
I have been using and teaching physics for many years and in many applications.
I wrote papers concerning thermonuclear propulsion and plasma turbulence.
I'm writing a paper on gene regulation physics.
I have worked for Nasa to determine risk of plasma charging of the space station.
In teaching I have also taught basic physics at UH in the PHYS1101 course.
I have been using calculus to solve real world problems in electronics, aerospace and mechanical industries. I'm also using calculus to solve scientific problems in plasma physics and cancer gene regulation dynamics.
During my teaching at UH as a TA in Physics and then a professor in Dynamics calculus has always been a key part of the programs and I have successfully brought many students up to speed and helped them pass their tests with flying colors.
Perl was an indispensable shell language for many codes written within the unix/linux environment.
However, python has the advantage of readability and being modular in nature.
Python is also welcome in scientific computing.
I use python mainly in working on image processing work where topology, diffeomorphism and normalization play special role in the analysis of photos as well as medical nifty files.
Simple but good use of python can be taught rather easily with just an example in a voting website where a histogram of voter inputs can be constructed.
I have been approved by WyzAnt as qualified to teach SAT.
Currently most applications are written both in the windows and unix/linux environments and it is advisable to be conversant in both operating systems.
As demonstrated by the Android phone plenty of apps (in the hundreds of thousands) have been written.
My experience in unix dated back 20 years from the time I joined Motorola to when I left TI, so mainly in the electronic industry.
I used Redhat Linux in the writing of my thermonuclear propulsion code (modifying the FLASH code by U. of Chicago).
Currently I'm using mainly Fedora Linux to work on image processing and bioinformatics code developments.
Teaching unix/linux is easier these days with many liveusb installation apps in place and the default geditor and xmgrace plotters.
A student can be up and running within half an hour including installing a full linux system and running a short script.
The rest will take more time but can be systematically introduced with a preset syllabus, the right material and some patience.
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