List of key methodologies and skills for each category of experience
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List of key methodologies and skills for each category of experience Mathematical modeling of the moth's olfactory Neuro-network Methodologies Computational methods of data analysis for realistic dynamical systems Data driven mathematical modeling of large, dynamical systems Using the computational model to predict the results in real life (In this case, how moth will respond to different types of odors) Skills Proficiency in MATLAB Ability to work with different types of programming languages: Python, Java…etc Very strong proficiency in different types of data analysis techniques such as PCA, RPCA, DMD…etc Solid Mathematical background Computational Methods of Data Analysis Projects (MATLAB Implementation) Methodologies Developing the algorithms for analyzing realistic set of data such as Noise filtering and reduction for different types of noisy data Time frequency analysis for time varying signals such as sound Algorithms for image enhancement Simplification of a large, multivariate data by reducing down its dimensions Recognition algorithm (e.g. Music Genre Recognition, Face recognition, Moving object recognition...) Video Foreground/Background separation for surveillance application Skills Strong proficiency with MATLAB and Mathematics Ability to implement theoretical frameworks into MATLAB codes Writing a professionally written paper for each project with analysis and results (Microsoft Word or Latex)
Transcript of List of key methodologies and skills for each category of experience
List of key methodologies and skills for each category of experience
Mathematical modeling of the moth's olfactory Neuro-network
Methodologies
Computational methods of data analysis for realistic dynamical systems
Data driven mathematical modeling of large, dynamical systems
Using the computational model to predict the results in real life (In this case, how moth
will respond to different types of odors)
Skills
Proficiency in MATLAB
Ability to work with different types of programming languages: Python, Java…etc
Very strong proficiency in different types of data analysis techniques such as PCA,
RPCA, DMD…etc
Solid Mathematical background
Computational Methods of Data Analysis Projects (MATLAB Implementation)
Methodologies
Developing the algorithms for analyzing realistic set of data such as
Noise filtering and reduction for different types of noisy data
Time frequency analysis for time varying signals such as sound
Algorithms for image enhancement
Simplification of a large, multivariate data by reducing down its dimensions
Recognition algorithm (e.g. Music Genre Recognition, Face recognition, Moving
object recognition...)
Video Foreground/Background separation for surveillance application
Skills
Strong proficiency with MATLAB and Mathematics
Ability to implement theoretical frameworks into MATLAB codes
Writing a professionally written paper for each project with analysis and results
(Microsoft Word or Latex)
DAQ Software development for ATLAS Pixel Detector Upgrade
Methodology
Development of new, robust FPGA DAQ software for future detector using the UW Pixel
DAQ System
Simulating the input signals and analyzing the output signals processed with new DAQ
FPGA firmware
Developing a firmware for new Readout Driver so that it is compatible with the old pixel
modules
Simulating the entire DAQ process with realistic hardware and CERN software
Skills
Solid understanding of DAQ system
Solid understanding of DAQ software
Solid understanding of digital signal processing and signal analysis
Able to make professional presentations and reports for UW research groups and
collaborators around the world (CERN, Berkeley Lab, SLAC at Stanford University…)
Teamwork and communication to distribute the workload and meet the deadline
Development of UW VME Pixel DAQ System
Methodology
Setting up both software/hardware components of the entire DAQ system at local
environment
Establishing the local DAQ software configurations for UW local lab
Resolving any error occurring during the local software integration and adaptation
Establishing the proper communication between the VME and PC interface as well as
testing the functionalities of all data transmission hardware
Skills
Proficiency with CERN DAQ software
Solid understanding of entire DAQ system architecture both hardware/software wise
Solid understanding of Linux environment
Solid understanding of communication between different interfaces (VME and PC)
Proficiency with C++ scripts to modify them according to local environment
Ability to identify and fix the bugs within the C++ scripts of software in Linux
Strong computation skill in general and logical problem solving skill
Professional weekly presentations and reports for UW research groups and collaborators
Teamwork and communication to distribute the workload and meet the deadline
Documenting the hardware/software installation and operation for the colleagues
Ability to reach out and research independently for general troubleshooting
ATLAS Pixel Detector DAQ Project: Pixel Calibration of Current/Next Gen
Pixel Chip
Methodology
Statistical analysis on the pixel calibration data by using modular DAQ system and
software
Analyzing each calibration algorithm and developing the algorithm sequence that
achieves the best operational setting for both current and next gen pixel chip
Skills
Proficiency with modular DAQ system and software
Solid understanding in both Linux and Windows environment
Solid understanding in software algorithms for calibration
Solid understanding in the architecture and the working principles of particle detection
chips
Professional weekly presentations and reports for UW research groups and collaborators
Teamwork and communication to distribute the workload and meet the deadline
Documenting the software operation for the colleagues
