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Sr. Research Software Engineer Resume

Clovis, CA

Objective

  • To look for a full time position to which I can contribute my expertise and knowledge in image processing, computer vision, machine learning, and embedded systems.

Highlights of Qualifications

  • 10+ years of successful experience in software development, electrical and computer engineering.
  • Strong experience and expertise of algorithms design in computer vision, image and signal processing, machine learning.
  • Excellent hands-on skills in design and development of real-time embedded software.
  • Proven expertise in design and development of image processing and embedded systems.
  • Comprehensive research methodology and fast software development.
  • Strong mathematical skills and problem solving skills.
  • Self-motivated and results-driven professional with outstanding credentials and keen team spirit.
  • Committed individual always willing to take on new challenges.

Education

  • Ph.D.,Pattern Analysis and Machine Intelligence,
  • M.Sc., Computer Vision and Pattern Recognition,
  • B.Sc.,Electrical and Electronic Engineering,

Work Experience

Sr. Research Software Engineer,October 2007 –present
Confidential, Clovis, California, USA

  • Design video analytics algorithms for video surveillance applications that involve video content extraction, event detection, metadata generation (MPEG-7 and ONVIF compliant) and management, video indexing, video content retrieval, etc.
  • Develop market-proven software of video analytics for PC platforms and edge devices (e.g., video encoders and smart IP cameras based on TI DaVinci and Equator Bsp) to provide key features (e.g., analytics engines) for Pelco’s intelligent video security solutions and systems, including development of analytic codecs (using C, intrinsic instructions, and DMA) in DSP, plug-ins in ARM processor, and libraries in PC-based server.
  • List of projects:
    • Kinect-based 3D Gesture Recognition for Video Surveillance Applications
    • Configuration Free Motion Detection and Object Tracking for Fixed Cameras
    • Object Tracking for Moving Cameras
    • Clustering-based Visual Object Classification
    • Automated Camera Calibration
    • Camera Tampering Detection
    • Face Detection and Tracking
    • Inference Engine for Visual Event Detection and Object Search
    • Cameras’ Scene Activity Analysis and Automated Semantic Feature Extraction
    • Video Coding based on Tracked Objects
    • Image Enhancement and Denoising, etc.

Sr. Computer Vision and Embedded Systems Software Engineer, July 2005 –September 2007
Confidential.,

  • Designed computer vision algorithms for variant intelligent video surveillance applications, including: Object/Motion Tracking, Left /Removal Item Detection, People Counting, Tunnel Security and Subway Safety Surveillance, Bank Machine Card-Skimmer Detection.
  • Developed real-time embedded software (in C and assembly and using DMA, software pipelining, loop unrolling, and parallel computing) for TI DM642 based video encoders/servers, including Ateme VSIP, Axis IV, and Bosch VIPX1.
  • Developed video analytic engines to provide real-time visual content analysis to Aimetis’s intelligent video management software for Windows machines.

Sr. Computer Vision and Embedded Systems Software Design Engineer, June 2004 – June 2005
Confidential.

  • Designed computer vision algorithm to classify vehicle occupants through processing camera video output for intelligent airbag deployment.
  • Developed advanced signal processing algorithm and real-time software (in C and assembly on TI DSP) to calculate occupant head’s 3D location by analyzing capacitive sensor data for intelligent airbag deployment.
  • Developed driver drowsiness detection and alarming system by processing drivers’ steering grip information.

Research Assistant and Teaching Assistant, 2001– 2004
Confidential,

  • Proposed novel data fusion schemes using neural-fuzzy embedded evidential reasoning techniques.
  • Developed advanced image processing algorithms to accurately segment human brain tissues and detect multiple sclerosis lesions based on multi-modality magnetic resonance images.
  • Developed advanced data fusion algorithm to robustly classify multi-channel remote sensing images.
  • Developed new watershed transform-based image segmentation algorithms for human knee’s structure extraction used for MRI-based knee diseases diagnosis.
  • Developed an adaptive image denoising algorithm using fuzzy set technology that effectively removed image noise while preserving image details.
  • Answered questions, presented tutorials, led lab sessions, and graded assignments and exams for undergraduate courses.

Image Processing Software Engineer, Embedded Systems Design Engineer,1991– 2000
Confidential

  • Developed machine vision system for auto-guidance of unmanned vehicle with real-time software implemented in C and assembly language on multi-DSPs (TMS 320C30) platform.
  • Developed computer vision system for vision guided balancing control of inverted pendulum.
  • Developed multi-TI DSPs-based real-time image processing system to automatically analyze railroad track sleepers\' quality.
  • Developed infrared ray image-based vehicle classification system for highway electronic toll collection.
  • Developed compact video surveillance device for real-time intrusion detection.
  • Designed and implemented (using FPGA and TMS320C30) high-speed decoding system to locate moving vehicles via wireless signals.
  • Developed real-time data acquisition and analysis system for tobacco industry, used by many large cigarette manufacturing companies in China.
  • Developed advanced stage lighting control system for lighting dimming, chasing, and color changing, mass-produced by two companies in Changsha.

Technical Skills

  • Programming language: C, C++, Matlab, Assembly (e.g. x86, IA-32, MMX, SSE, SSE2, SSE3, TI DSPs and Microchip MCUs), Java, JavaScript, Visual Basic.
  • Library: OpenCV, OpenGL, OpenSURF, OpenNI, libfreenect, Intel IPP, VLIB, MFC, libxml, etc.
  • Image processing and computer vision: 3D vision, SHIFT, KLT, image enhancement, denoising, segmentation, etc.
  • Machine learning: neural networks, boosting, support vector machines, etc.
  • Development tool: Microsoft Visual Studio, GCC, G++, Eclipse, TI DVSDK, TI Code Composer Studio.
  • Video compression: JPEG, MPEG-1, MPEG-2, MPEG-4, H.261, H.263, H.264.
  • Medical imaging tool: MRIcro, imageJ, FMRIB's Software Library (FSL)
  • DSP and microprocessor: TI DaVinci/DM642, TMS320C25/C30/C31/LF24xx, Microchip PIC12F6xx/16Cxx, Intel MCS8031/51/96/98, Intel80188/186/286, Zilog Z8/80.
  • Data communications and networking: TCP, UDP, RTP, RS232/485/422, Controller Area Network.
  • Software tool: SVN (Subversion), PuTTY, VNC (Virtual Network Computing), U-Boot, GNU Make, CMake, VLD (Visual Leak Detector), etc.

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