S O F T W A R E E N G I N E E R

I r v i ne, CA, USA 92617 +1-949-***-**** l i j adxe3o@r.postjobfree.com

L I - J U C H E N

P R O F I L E S U M M A R Y

Highly motivated student specializing in computer vision, deep learning, and IoT applications. Experienced in developing and implementing computer vision algorithms for indoor drones, focusing on tracking and image processing. Proficient in optimizing algorithm performance through parallel computing, GPU acceleration, and algorithmic enhancements. C O M P U T E R L A N G U A G E S

C/C++, Python, SQL, PHP, Java, HTML/CSS, C#, Matlab, Javascript, JSON E D U C A T I O N

University of California - Irvine/ MS, Computer Engineering 09.2022 - 12.2023

National Taiwan University/ MS, Electrical Engineering And Computer Sciences 09.2015 - 06.2018

R E L E V A N C E C O U R S E S

Computer Vision, Machine Learning, Deep Learning, Cyber-physical Systems, Embedded System, Sensors, Actuators and Sensor Networks, Security & Privacy, Control Systems, Artificial Intelligence, Data Structure, Operation Systems, Digital Logic Design, 3D Computer Game, Compilers, Computer Graphics, Autonomous Systems, Assembly Language, Electronic Circuits, Network, Database National Taiwan Ocean University/ BS, Computer Science And Engineering 09.2011 - 06.2015

h t t ps:/ /www.l i n k edin.com/i n / l i - j u - chen-9337321b6/ S K I L L / L I B R A R Y

OpenCV, OpenCL, Arm Neon, OpenGL, Tensor-flowm Fastcv,Web, OpenMp, Unity, Pytorch, Kears, Node.js, Docker, Linux, Firebase, NodeRed, ESP8266, NodeMCU, Arduino, RaspberryPi, Android.

P R O J E C T

Fast Computer Vision Algorithm on Embedded Systems. Developed C++ implementation of the Canny Edge Algorithm for image edge detection. Optimized computer vision algorithms by implementing pipeline and parallelization using IEEE SystemC.

Achieved a 10x performance improvement on Raspberry Pi. 09, 20212- 11,2022

IOT Communication and Data Management.

Experienced in IoT and proficient in light sensor integration, data transmission via UDP, and web visualization using Node-Red.

Completed an IoT project utilizing photoresistor (light sensors) integrated with Arduino to collect environment light intensity.

Implemented data transmission to a Raspberry Pi for further analysis and processing. Analyzed and displayed the collected data on a website hosted by Node-Red. 09, 2022- 11,2022

Windows Desktop Widget (Java).

Developed and designed custom desktop widgets for Windows platform, including a Notepad and a Painter application.

Created intuitive user interfaces and layouts for seamless user interaction. 08, 2013- 07,2014

3-Dimensional Reconstruction System for Handheld Device. Reconstructed 3D point clouds using feature extraction(Sift) techniques on Rgb images and matching frames with K-nearest neighbors.

Skilled in camera calibration and utilizing the Kinect camera for collecting depth and Rgb data. 08, 2013- 09,2014

W O R K E X P E R I E N C E

Computer Vision Engineer, RogersAI

Built an automatic indoor drone system using Robot Operating System for simulating autonomous algorithms, resulting in improved efficiency and functionality. (Java and C++) Collected Tof and Rgb image from Qualcomm Snapdragon platform on Android. Optimized localization algorithms for limited computing resource hardware, enhancing performance by factor of 4 and responsiveness.

Implemented a filter on TOF images to achieve a 3% increase in accuracy for face recognition.

(using C++)

Overview: Developed a localization (SLAM) algorithm in C++ and optimized its performance through GPU and Arm Neon.

03, 2021 - 09,2022

Research Assistant, Academia Sinica 09, 2019 - 02,2021 Implemented a privacy-preserving mechanism using Deep Learning and Differential Privacy, resulting in improved facial image quality by 22% with the same level of security. Co-authored a paper titled "Perceptual Indistinguishability-Net (PI-Net): Facial Image Obfuscation with Manipulable Semantics," presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.

Overview: Implemented privacy-preserving techniques in Deep Learning and co-authored a paper on facial image obfuscation.

R&D Engineer, Foxconn Technology Group 07, 2018 - 05,2019 Improved factory productivity by at least 5% through the utilization of edge detection algorithm and de-noise filters.

Developed an object recognition system using CNN, enhancing non-contact measuring efficiency. Contributed to camera calibration and depth measurement. (using C++) Overview: Improved factory productivity by 5% through edge detection and object recognition using CNN.

R E S E A R C H E X P E R I E N C E

Co-first Author of "Perceptual Indistinguishability-Net (PI-Net): Facial Image Obfuscation with Manipulable Semantics," presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.

Technical Support Intern, LINE Pay 06, 2016 - 12,2017 Integrated LINE Pay API with websites of various programming languages (PHP, Java, Ruby, etc.).

Building tools in Java, Excel, SQL, and Python to efficiently analyze business data in databases. Maintained databases and dashboards to support operators in executing risk avoidance and marketing strategies.

Overview: Integrated LINE Pay API across multiple programming languages, developed data analysis tools, and maintained databases.

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