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Research Statement




         By: Fang, Can 方灿
         mrfunder@hotmail.com,
         fangc2@upmc.edu
Academic Background
   B.S of Electrical Engineering (Xi’An
    JiaoTong University, China)
    ◦ Dissertation: “DS1302 Chip Coding and Encrypting
      Study in Contact-less IC Card System”
   PhD of Computer Science (Nanyang
    Technological University, Singapore)
    ◦ Dissertation: “Graph-Theoretic and Geometric
      Optimizations in Communication Networks”
Technical Skill Highlights
   Computer Science
    ◦ Mathematical modeling, optimization and simulations
    ◦ Algorithm prototyping, code developing
   Optics
    ◦ Device design, setup and alignment
    ◦ Monte Carlo simulation
   Good knowledge in broad range of general
    science and technology
PhD Researches
   My PhD research work is composed of four
    projects:
    a. Optimal Wavelength Converter with Guaranteed Wavelength Usage
    b. Load-Balanced Clustering in Wireless Sensor Networks (WSNs)
    c. Worst-case and Best-case k-coverage Problem in WSNs
    d. Generalized Study on Movement-assisted Sensor deployment problem

   These four projects can be classified by
    approaches used:
    ◦ Graph-theoretic approach
    ◦ Geometric approach
Graph-Theoretic VS Geometric
            Optimizations

Graph-theoretic approach       Geometric approach
Formulate the original         Study the measurable properties
problem into “graphs” (tree,   of figures (size, shape, angle,
path, star, ring, etc)         position, etc)
A graph is composed of edges   Deals with problems of
and vertices (nodes)           computing geometric objects
Graph-Theoretic VS Geometric
         Optimizations (cont’)
Project A:        Project C:
                    ·I

                                P
                                    F
                                    ·
Project B:
                   Project D:
Current Work
                                                As team player:
       As lead player:
                                                        Spectrum-scanning
                                                        microscope




                               Tissue light
Multi-spectral optical probe   scattering
                               fingerprinting
                               system
Light Scattering Fingerprinting
            System
Data Acquired
   Raw data:
    ◦ CCD arm: two dimensional scattering
      intensity distribution;
    ◦ Spectrometer arm: scattering angle/
      wavelength distribution
   Parameters (markers) after processed:
    ◦ LEBS peak height, width, correlation, spectral
      slope, etc
Data Example

                                        processed LEBS peak
scattering angle




                                                         wavelength
                                    scattering angle
                       wavelength
Spectrum-Scanning Microscope


                                                 objective
                    splitter

 Xe                                             interchangeable
                                                splitter



      telescopic
      objective
                                  commercial
                                  microscope
                   slit
                               scanning stage
                               and CCD
Data Acquired
   Raw data:
    ◦ Three dimensional data cube, reflected
      intensity R(x, y, λ), where λ is the spectrum
      from 400nm to 700nm.
   After processed:
    ◦ Refractive index distribution within the cell
1

Example
Cervix cells(cancer)


                           2




                           3
       1        2


                       3
Multi-Spectral Optical Probe

                                           spectrometer




                                                            fiber switch



     Xe       fiber switch




405nm laser                                    probe head

                         coupling optics
Data Acquired
   Raw data:
    ◦ Depth-selective spectrum of back scattered
      light
   Proceesed:
    ◦ Scattering feature: slope
    ◦ Absorption feature: concentration of
      absorbers (Hb, HbO2, Beta-carotene, etc)
Data example




Hemoglobin phantom measurement
(Hb increased from 1g/L to 15g/L)

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Research Statement Summary for Fang Can

  • 1. Research Statement By: Fang, Can 方灿 mrfunder@hotmail.com, fangc2@upmc.edu
  • 2. Academic Background  B.S of Electrical Engineering (Xi’An JiaoTong University, China) ◦ Dissertation: “DS1302 Chip Coding and Encrypting Study in Contact-less IC Card System”  PhD of Computer Science (Nanyang Technological University, Singapore) ◦ Dissertation: “Graph-Theoretic and Geometric Optimizations in Communication Networks”
  • 3. Technical Skill Highlights  Computer Science ◦ Mathematical modeling, optimization and simulations ◦ Algorithm prototyping, code developing  Optics ◦ Device design, setup and alignment ◦ Monte Carlo simulation  Good knowledge in broad range of general science and technology
  • 4. PhD Researches  My PhD research work is composed of four projects: a. Optimal Wavelength Converter with Guaranteed Wavelength Usage b. Load-Balanced Clustering in Wireless Sensor Networks (WSNs) c. Worst-case and Best-case k-coverage Problem in WSNs d. Generalized Study on Movement-assisted Sensor deployment problem  These four projects can be classified by approaches used: ◦ Graph-theoretic approach ◦ Geometric approach
  • 5. Graph-Theoretic VS Geometric Optimizations Graph-theoretic approach Geometric approach Formulate the original Study the measurable properties problem into “graphs” (tree, of figures (size, shape, angle, path, star, ring, etc) position, etc) A graph is composed of edges Deals with problems of and vertices (nodes) computing geometric objects
  • 6. Graph-Theoretic VS Geometric Optimizations (cont’) Project A: Project C: ·I P F · Project B: Project D:
  • 7. Current Work As team player: As lead player: Spectrum-scanning microscope Tissue light Multi-spectral optical probe scattering fingerprinting system
  • 9. Data Acquired  Raw data: ◦ CCD arm: two dimensional scattering intensity distribution; ◦ Spectrometer arm: scattering angle/ wavelength distribution  Parameters (markers) after processed: ◦ LEBS peak height, width, correlation, spectral slope, etc
  • 10. Data Example processed LEBS peak scattering angle wavelength scattering angle wavelength
  • 11. Spectrum-Scanning Microscope objective splitter Xe interchangeable splitter telescopic objective commercial microscope slit scanning stage and CCD
  • 12. Data Acquired  Raw data: ◦ Three dimensional data cube, reflected intensity R(x, y, λ), where λ is the spectrum from 400nm to 700nm.  After processed: ◦ Refractive index distribution within the cell
  • 14. Multi-Spectral Optical Probe spectrometer fiber switch Xe fiber switch 405nm laser probe head coupling optics
  • 15. Data Acquired  Raw data: ◦ Depth-selective spectrum of back scattered light  Proceesed: ◦ Scattering feature: slope ◦ Absorption feature: concentration of absorbers (Hb, HbO2, Beta-carotene, etc)
  • 16. Data example Hemoglobin phantom measurement (Hb increased from 1g/L to 15g/L)