This document provides a summary of Jinjin Li's technical skills, professional experience, education, and references. Li has over 7 years of experience in algorithm design and programming in MATLAB and C++ with a focus on 3D machine vision, stereo vision, and image/video processing. Notable professional projects include developing automated inspection systems for Intel using stereo vision and proposing algorithms for 3D reconstruction from video frames. Li has a PhD in Electrical Engineering from Arizona State University and has published papers in conferences and journals on topics related to depth estimation, stereo matching, and 3D modeling.

1. JINJIN LI
1975 E University Dr. APT 267 | Tempe AZ 85281 | jinjinli@asu.edu | 602-638-7693
TECHNICAL SKILLS AND ABILITIES
- Solid understanding of 3D machine vision, Stereo Vision, Image/Video Processing
- 5 years’ experience of research in coordination with Industrial companies (Intel Corporation)
- Over 7 years’ algorithm design and programming experience in MATLAB and C++
- Deeply experienced in imaging setup including cameras, illumination and hardware integration
- Strong Mathematical and Analytical Skills. Good Communication and teamwork skills.
- Self-motivated and highly organized to multitask efficiently under pressure
- Specialties:
3D Machine Vision Stereo Vision and 3D Modeling Digital Image and Video Processing
Computer Vision Camera Calibration (pin-hole and fisheye) Time-Frequency Signal Process
Machine Learning Algorithm Developing and Programming Data Organizing and Analysis
- Programming Languages: Visual C++, FPGA, VHDL, Assembly, JAVA
- Software: MATLAB, MS Visual Studio C++, OPENCV, JMP, LaTex, Eclipse IDE, Weka, Cadence,
CodeWarrior (Motorola), Code Composer Studio (TI), MS office, Photoshop
PROFESSIONAL EXPERIENCE
Industrial Research and Internship
3D Reconstruction for Industrial Product (BGA) Inspection
Sponsored by Intel Corporation, Chandler AZ (Sep.2010-Dec.2013)
Ø Proposed an automatic stereo vision based solder ball height and substrate coplanarity detection
method with less-complex algorithm, faster speed and higher accuracy, which outperforms many
major techniques
Ø Proposed an iso-contour based segmentation algorithm for featureless images
Ø Implemented a automated camera calibration system
Ø Assembled high resolution camera, optics, lighting, and movement hardware into final tool
Ø Filed a US patent based on this original and novel method
3D Depth Estimation for Automobile Surveillance and Detection System
Sponsored by Intel Corporation, Chandler AZ (Aug.2013–May. 2014)
Ø Proposed a 3D reconstruction system based on fisheye video frames, to detect the distance of
objects around the vehicle and send out alarm when stops are needed
Ø Implemented a fisheye un-distortion and multi-view reconstruction method using MATLAB and
OpenCV (C++)
Emotion Detection and Classification on Mobile Phone System
Internship at InterDigital Inc., San Diego CA (May.2014-Aug.2014)
Ø Investigated existing mobile device sensing applications on user information
Ø Developed an Android-based app for user attention detection using mobile sensors and machine
learning algorithms
Relevant Projects
Stereo Matching System of Rectified Stereo Images based on Sparse Locally
Adaptive Cost Aggregation (Sep.2014-Dec.2015)
Ø Proposed a stereo matching system using both MATLAB and OpenCV to generate dense disparity
map from stereo images with improved overall accuracy and reduced computation redundancy
Ø Proposed a sparse locally adaptive cost aggregation method using adaptive guided filter
Ø Proposed an improved adaptive support region method for support region detection

2. 3D Modeling and Depth Estimation using Multiple View Images and Videos
(Sep.2009-Aug.2010)
Ø Constructed a 3D multi-view reconstruction system combining various techniques including
feature detection (SIFT, BRISK and FAST), RANSAC, Triangulation, Bundle Adjustment and Metric
Upgrade
Ø Developed a Euclidean reconstruction algorithm from metric 3D frame
Ø Analyzed algorithm performance in aspects of profiling speed, accuracy and video capability
Velocity and Flow Rate Estimation of Blood Vessels in Biomedical Images
(Nov.2011)
Ø Implemented a motion estimation algorithm to estimate the flow rate and velocity in blood vessels
videos using Phase-Correlation Motion Estimation techniques in MATLAB
Muscle Fiber Classification using Biomedical image processing (Oct.2011)
Ø Implemented a classification algorithm to classify healthy muscle fibers and unhealthy ones using
techniques of minimum-distance classifier, image segmentation and morphological operations
Survey of Major Data Mining and Machine Learning Techniques
(Sep.2010-Dec.2010)
Ø Implemented machine learning algorithms including decision trees, Bayesian classifiers, neural
networks, support vector machines (SVM), etc. using Weka
Real-time Digital Signal and Image Processing using fixed-point DSP boards
(Feb.2009-May.2015)
Ø Instructed, designed and debugged real-time DSP labs including signal filtering, histogram
equalization and musical tone synthesis on DSP56858EVM and TMS320c55x DSP boards
Elimination of Blocking and Ringing Artifacts from Transform Domain Images
(April.2009)
Ø Designed an image deringing and deblocking filter using OPENCV and C++
PUBLICATIONS
l Sparse Depth Estimation using Multi-view 3D Modeling
IEEE International Conference on Emerging Signal Processing Applications (ESPA),
2012
l Stereo Vision Based Automated Solder Ball Height Detection
IPC Printed Circuit Expo, APEX & Designer Summit Proceedings, 2014
l Sparse Depth Calculation Using Real-Time Key-Point Detection and Structure
from Motion for Advanced Driver Assist Systems
Advances in Visual Computing, 2014
l Automated BGA Solder Ball Height and Coplanarity Detection based on Stereo
Vision Method
IEEE Transactions on Automation Science and Engineering, March 2015
l Sparse Locally Adaptive Cost Aggregation For Stereo Matching
To be submitted to IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016
PATENTS AND INVENTION DISCLOSURES
l Automated Warpage and Solder Ball Height Measurement and Inspection for
Semi-Conductor Units
Provisional Patent filed March 2014; AzTE Invention Disclosure, September 2013. AzTE Case
Number M14-056P

3. FELLOWSHIPS AND AWARDS
l Nomination for ASU Faculty Women’s Association Awards for Distinguished Graduate
Students (March.2014)
l Member of Mathematical Modeling team in nationwide Mathematical Modeling
competition (Aug.2006)
l Member of the “Elite Class” for top 3 of students from each department in Hebei
University of Technology
l Best Director of Student Associate Union (Oct.2004-Sep.2006)
EDUCATION
PhD in Electrical Engineering
Arizona State University, Tempe AZ USA
Jan.2011- Aug.2016 (expected)
GPA: 4.0 / 4.0
MS in Electrical Engineering
Arizona State University, Tempe AZ USA
Aug.2008-Dec.2010
GPA: 4.0 / 4.0
BS in Electrical Engineering
Hebei University of Technology, TianJin China
Oct.2004-July.2008
GPA: 3.85 / 4.0
MAJOR COURSES & GRADES
Digital Image and Video Processing (A) Biomedical Image Processing (A)
Digital Signal Processing
(A)
Multidimensional Signal Processing (A+) Stat. Learning for Data Mining (A) Real Time DSP (A+)
Digital Spectral Analysis (A+) Detection/Estimation Theory (A) Random Signal Theory (A)
REFERENCE CONTACT
l Lina Karam, Professor, Image, Video and Usability Lab, Arizona State University,
Tempe AZ
Email: karam@asu.edu Tel: (480)965-3694
l Bonnie Bennett, Research Technologist, Intel Corporation, Chandler AZ
Email: bbnett@comcast.net
l Nital Patel, Principal Engineer, Intel Corporation, Chandler AZ
Email: nital.s.patel@intel.com