Curriculum Vitae

[CV] Haoxiang Zhang

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Skills

Programming

[ C++, C, Python, Makefile, CMakeLists, Bash ]

Libraries and Tools

[ Git, CUDA, Linux, OpenCV, Docker, Parallel Programming, Deep Learning ]

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Work Experience

Firmware Engineer @ TenaFe Inc.

Campbell, CA

02/2024 - present

[ C++, Makefile, Bash, GTEST, Python, subprocess ]

• Developed a tool for the SSD controller event‑driven simulation to collect and track processing timing data, which greatly
  reduced the time required for debugging and performance analysis.
• Modified the simulation workflow to make the simulation behavior more close to the actual.
• Built a sweep tool to run the controller simulator with varying config values, streamlining performance testing.
• Built a tool for convertering different SSD product configuration files, enhancing efficiency.
• Tested and covered test cases of Search/Sort Module with the specification documents and the signal process waveforms.
• Analyzed the performance data and modified the workflow of the SSD controller simulator project, and optimized configu‑
  ration data for the design and other teams.

Research Associate (DIC Lab) @ University of Missouri

Columbia, MO

03/2023 - 12/2023

[ C++, Math, Java, SOAP, RESTful ]

• Developed a ray tracing project producing high‑quality and realistic images through the ray‑sphere intersection, surface
  shading, and enhanced features like anti‑aliasing and metal reflections.
• Implemented web services based on Spring Boot.

Graduate Research Assistant (CIVA Lab) @ University of Missouri

Columbia, MO

12/2020 - 12/2022

[ C++, Python, Unity, HoloLens, C# ]

• Analyzed various meshing algorithms on city‑scale point clouds, enhancing the quality of 3D mesh models. This involved
  detailed comparative analysis to identify the most efficient algorithm for accurate 3D modeling.
• Utilized the CVAT annotation tool within a Docker environment for labeling cells in biomedical images, significantly boosting
  30% accuracy of a Deep Learning‑Based Cell Detection and Extraction project.
• Configured and tested VR project compatibility across multiple platforms, including MiddleVR and UniCAVE Unity plugins.
• Resolved complex issues with VR headset and scene orientation, leading to notable improvements in user experience.

Undergraduate Research Program Mentor @ University of Missouri

Columbia, MO

05/2022 ‑ 07/2022
[ Leadership, VR ]

• Mentored and guided undergraduates to test and analyze advanced meshing algorithms.
• Supervised and directed undergraduates in the successful implementation of a multiplayer Unity project.
• Achieved academic recognition by co‑authoring and publishing a research paper at the prestigious IEEE CCNC conference.

Software Engineer Intern @ eConage Software

Hangzhou, China

06/2018 ‑ 07/2018

[ Linux, Java ]

• Acquired expertise in Logstash configuration rules, streamlining log consolidation through custom filter editing.
• Enhanced log analysis in Kibana by defining specific log information labels for data‑driven decisions.

Teaching Assistant @ Early Childhood Develop Center

Crookston, MN 09/2016 ‑ 12/2018

[ Cooperation ]

• Helped facilitate enriching indoor/outdoor activities for the class size of 18 preschool children.
• Prepared meals for lunch and snacks for toddlers and preschool

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Projects

Accelerating Algorithm via Parallel Programming

[ CUDA, C++, OpenCV, Boost, Multi-threading, Multi-processing ]

• Achieved impressive speed improvement in the SuperPixels algorithm using different C++ APIs and language extensions,
  such as multi‑processing with Unix IPC mechanisms and multi‑threading with Boost Threads
• Accelerated the SuperPixels algorithm on a multi‑node architecture using C++ and OpenMPI
• Utilized CUDA C++ to significantly accelerate the runtime of an image median‑filtering algorithm from 19,976 ms to 67 ms

Interactive K-Means Clustering Tool App

[ QT, C++ ]

• Developed a user‑friendly K‑Means algorithm 2D/3D data visualization application using the QT framework and C++
• Designed an intuitive GUI with features such as a data visualization panel, parameter edit boxes, and view‑move buttons
• Enabled step‑by‑step data visualization of the K‑Means algorithm, enhancing user understanding and analysis

Realistic Ray Tracing

[ C++, Math ]

• Developed ray tracing project following Peter Shirley’s book to produce high‑quality images with realistic indirect lighting
• Implemented ray‑sphere intersection, surface shading with normals, and support for multiple objects in the scene
• Enhanced accurate light modeling with features like anti‑aliasing, diffuse materials, metal reflections, and dielectric

Real‑time Embedded Projects with Auxiliary Board and Raspberry Pi

[ C, Embedded ]

• Implemented a traffic light simulating a real‑time event around a crosswalk using C. The priority scheduler for controlling
  traffic lights using multi‑threading
• Implemented a music keyboard on the auxiliary board using C. The master device broadcasts the message to the child de‑
  vices through Wi‑Fi using UDP socket to play different frequencies of the sound

Maze Navigator ‑ Reinforcement Learning

[ Python, Pandas, NumPy, Tkinter ]

• Constructed an interactive maze environment with Tkinter, enabling real‑time visualization of autonomous agent navigation
  and environment interaction
• Implemented a simulation for a maze‑solving agent employing Q‑Learning and SARSA reinforcement learning algorithms

FASHION‑MNIST Classification with CNN

[ Python, PyTorch, CNN ]

• Developed and trained CNN models using PyTorch for the FASHION‑MNIST dataset
• Conducted data preprocessing, including splitting data into training, validation, and test sets
• Evaluated model performance using precision and recall scores to ensure effective fashion item classification

Retinal Vessel Segmentation

[ MATLAB, Image Processing, CNN ]

• Segmented the blood vessels in the fundus image with a supervised approach with a teammate
• Applied pre‑processing methods such as CVR removal and tophat transform
• Implemented a network architecture and made a related network architecture diagram
• Made masks for the dataset and trained the model with the dataset.

Smart Luggage Project ‑ Two People Project

[ Python, OpenCV ]

• Designed and implemented a smart luggage robot that tracks and follows the target person
• Implemented the people detecting future using YOLO
• Implemented the robot control using breezycreate2 library and the communication between PC and micro‑controller with
  the socket

RESTful Web Services Development for a Social Media Application

[ Java, Web Service, RESTful ]

• Developed RESTful web services for a social media application using Java and Spring Boot framework
• Implemented features such as versioning, exception handling, and basic authentication (Spring Security) with HATEOAS
  and filtering
• Documented the web services using Swagger and monitored them using Spring Boot Actuator
• Engaged in learning and exploring Kubernetes, gaining valuable knowledge in container orchestration and management

SOAP Web Service Development for a Course Management Application

[ Java, Web, SOAP ]

• Successfully implemented SOAP web services using Java, Spring Boot, and Spring Security
• Followed best practices in defining XSD and implementing exception handling and basic security with WS Security
• Used Wizdler SOAP Services Chrome Plugin to test and verify the functionality of the SOAP web services

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Publication

Calvin Davis, Jaired Collins, Joshua Fraser, Haoxiang Zhang, Shizeng Yao, Emily Lattanzio, Bimal Balakrishnan, Ye Duan,
Prasad Calyam, Kannappan Palaniappan, “CAVE‑VR and Unity Game Engine for Visualizing City Scale 3D Meshes,” in 2022
IEEE 19th Annual Consumer Communications & Networking Conference (CCNC)

B. Hall, J. Kessler, O. Edo‑Ohanba, J. Collins, H. Zhang, N. Allegreti, Y. Duan, S. Wang, K. Palaniappan, P. Calyam ”Networked
and Multimodal 3D Modeling of Cities for Collaborative Virtual Environments,” 2022 IEEE/ACM International Conference on
Big Data Computing, Applications and Technologies (BDCAT), Vancouver, WA, USA, 2022, pp. 204‑212

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Education

Master of Science in Computer Science

• University of Missouri Columbia
• GPA: 3.73 / 4.0
• 12 / 2022

Bachelor of Science in Software Engineering

• University of Minnesota - Crookston
• GPA: 3.8 / 4.0
• 12 / 2018

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Courses

Self-Instruct

University of Missouri

• Intro to Computational Intelligence
  • Fall 2019
  • ECE 7870
• Digital Image Processing
  • Fall 2019
  • ECE 7655
• Real‑time Embedded Computing
  • Fall 2019
  • ECE 7220
• Digital Image Compression
  • Spring 2020
  • ECE 7675
• Neural Networks
  • Spring 2020
  • ECE 8890
• Intro to Machine Learning
  • Spring 2020
  • ECE 7720
• Unsupervised Learning
  • Fall 2020
  • ECE 8735
• Biomedical Image Processing
  • Fall 2020
  • CMP_SC 8675
• Machine Learning Method for Biomedical Informatics
  • Fall 2020
  • CMP_SC 8180
• Vision Computing
  • Spring 2021
  • CMP_SC 8001
• Cloud Computing
  • Spring 2021
  • CMP_SC 7530,
• High Performance Computing
  • Fall 2021
  • CMP_SC 7080