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Pleasanton 
$9/h
1st lesson free!
Verified profile and diploma
Response Time 14h
Lessons offered by Wanling
  • Individual
The lessons will be held
Taught subjects
  • Computer programming
  • C++
  • Computer languages
  • Python
  • Artificial intelligence
Levels
  • All Levels

Computer vision, machine learning, VLSI expert with teaching experience of 5 years

Methodology

My teaching approach is get students excited about this field by giving a big picture of the field, what can you do with the techniques in this field, then provide the technical details chapter by chapter, accompanied with projects for each chapter to make students gain some hands on experience in the field.

Background

I have experience as computer vision, machine learning, VLSI engineer, I obtained PhD from Purdue University in ECE, and I got MS in EE at University of Southern California. I have been teaching students to do research in various research domain, such as computer vision, machine learning, business intelligence and 3D reconstruction.

Rates

Rate for online lessons : $9/h
Rate for 5 hours of lessons : $8
Rate for 10 hours of lessons : $7
Lessons offered by Wanling
Individual
The lessons will be held
Taught subjects
  • Computer programming
  • C++
  • Computer languages
  • Python
  • Artificial intelligence
Levels
  • All Levels

Wanling's resume

Purdue University (May 2019)
University of Southern California--Viterbi School of Engineering(May 2013)
Dalian University of Technology (DUT) (June 2011)

Internship — Hitachi Automotive Systems Americas, Inc.
Driver drowsiness detection
Extracted features for driver drowsiness detection and currently working on using LSTM network (tensorflow) on classifing the features related to drowsiness detection.
Investigated methods to improve system performance (Jetson TX1 embedded system)

Research
Color halftoning based on Neugebauer Primary Area Coverage (NPAC)
Generated parawacs selection matrix using DBS and analyzed the filter size and scale factor for better quality matrix.
Generate NPAC image set and used NPAC Direct Binary Search (DBS) method to minimize the error metric, this operation is performed iteratively until a local minimum is reached (C/C++), our method generates homogeneous and visually pleasing halftone images based on human visual system model.

Single angle, single frequency, multidrop ink optimized halftoning
Designed halftone cell and hybrid screen using DBS in C language.
Developed a novel color halftoning method with potential for ink saving for large format inkjet printer.

Forensic for counterfeit currency
Using K-means clustering to segment the printed patch into cyan, magenta, and yellow clusters.
Investigated features of printed patches in both spatial and frequency domain to distinguish different printers.
Used machine learning to categorize the printers based on features extracted.

Publications
W. Jiang, W. Xi, U. Sarkar, R. Ulichney, J. Allebach, "Color halftoning based on Neugebauer Primary Area Coverage", Color Imaging: Displaying, Processing, Hardcopy, and Applications Conference, IS&T Electronic Imaging, Feb, 2017.
W. Jiang, A. Veis, R. Ulichney, J. Allebac h, "Single angle, single frequency, multidrop ink optimized halftoning", Color Imaging: Displaying, Processing, Hardcopy, and Applications Conference, IS&T Electronic Imaging, Feb., 2018.
Zhi Li, Wanling Jiang, Daulet Kenzhebalin, Alexander Gokan, Jan Allebach, "Intrinsic signatures for forensic identification of SOHO inkjet printer", Printing for fabrication, IS&T 33rd International Conference on Digital Printing Technologies (NIP), Sept., 2018

Teaching Experience
Teaching assistant for signal processing at Purdue University
Teaching assistant for science class at a junior high school in Lafayette, IN

Undergraduate Research Mentoring
An Overview of Text and Non Text based Business Analysis
2D to 3D Neurovascular Reconstruction from Biplane View via Deep Learning


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