馃憢 Hey there! I鈥檓 Zhe Fan! You can call me Jeff.
馃帗 I鈥檓 currently studying Electrical and Computer Engineering at Duke University.
馃尡 I鈥檓 on track of Software Engineering for learning System Design, Back-End Engineering and Algorithms.
鉁嶏笍 I鈥檓 also self-learning Machine Learning in Computer Vision, Game Development and 3D modeling.
馃挕 I like to explore new technologies and wish to be a Software Architect in the long future.
鉁堬笍 In my free time, I pursue traveling, animation and workout as hobbies.
馃挰 Feel free to reach out to me for suitable NG position, or just for some interesting discussion.
鉁夛笍 You can shoot me an email at zf70@duke.edu! I鈥檒l try to respond as soon as I can.
Jeff鈥檚 Experience
Jun 2023 - Present | Software Engineer Internship
Duke University
- Implemented report generation for Data-driven Hypothesis web app, enabling users to generate detailed reports.
- Built AWS infrastructure (SQS, Lambda, SES) for automated report generation, email delivery, and user database management, enhancing user experience.
- Integrated AWS Cognito for user authentication, enabling private report access, and preferences management.
- Collaborated with the development team to ensure seamless integration of the report generation feature, improving usability and facilitating data-driven biological discovery.
Sep 2021 - May 2022 | Research Assistant
University of Shanghai for Science and Technology
- Responsible for the practical & experiment.
- Applied CNN in training pre-processed visual features, and examined the accuracy.
- Conducted comparative experiment between AI-based methods and traditional (PCA+SVM) methods for analyzing differences between different approaches.
Doi: 10.1016/j.ins.2022.05.045
May 2021 - Oct 2021 | Research Assistant
Fudan University
Focus on 2D Hip pressure analysis
- Led the research group aiming to develop an intelligent system for identifying unhealthy sitting posture.
- Applied traditional and CNN methods respectively in analyzing data retrieved from the pressure sensor.
Doi: 10.1016/j.bspc.2021.103432
Skills: Scientific Papers 路 Anomaly Detection 路 Deep Learning
Jun 2020 - Aug 2022 | Co-Founder and Head of AI and Robotics Maker-Space
University of Shanghai for Science and Technology
- Lead the team to develop from a 10-person studio to a professional organization of 100 people.
- Once cooperating with Volkswagen, mainly to provide technical support related to defect detection.
- Responsible for Projects on Industrial Vision Inspection and Detection.
Skills: Project Management 路 Anomaly Detection 路 Computer Vision
Sep 2019 - Jun 2020 | Founder and Head of Digital Media Studio Department
University of Shanghai for Science and Technology
- Created the department and recruited team members, forming team of 10.
- Responsible for Project - Game Development and Campus 3D Modeling.
Skills: Team Management 路 Project Planning 路 Unity3D 路 Game 路 Blender
Jeff鈥檚 Education
Aug 2022 - May 2024 | Duke University
Master of Science in Electrical and Computer Engineering | GPA: 3.73
FOCUS AREA: Software Engineering
Courses taken:
- ECE 550D. Fundamentals of Computer Systems and Engineering.
- ECE 551D: Prog, Data Struc & Algo in C++
- ECE 590: Advanced topics in ECE
- ECE 568: Engineering Robust Server Soft
- ECE 650: Systems Program & Engineering
- ECE 651: Software Engineering
- GAMEDSGN 530: Critical Analysis Video Game
- ECE 560: Computer & Info Security
- ECE 563: Human-Centered Computing
- ECE 590: Towards More Reliable Software
Sep 2018 - Jun 2022 | University of Shanghai for Science and Technology
Bachelor of Engineering in Electrical and Information Engineering | GPA:3.94/4.5 (3.86/4.0)
2nd Prize of China Instrument and Control Society Scholarship in 2022 (A total of 38 across the country)
Graduation with honor: College Graduate Excellence Award of Shanghai
Jeff鈥檚 Projects
Mar 2023 - May 2023 | Mini Amazon
Tech Stack: Java, Protocol, TCP, PostgreSQL, Django, Hibernate
- Developed a full-stack web APP and completed the pairing of the shopping system with the warehouse and logistics delivery system.
- Based on gRPC, our team and the logistics platform development team developed the proto2 protocol for purchase-shipment-receipt, and communicated regularly to ensure correct processing of transactions and data consistency. In order to ensure efficiency and simplicity, subsequent changes were upgraded to the proto3 protocol. .
- I implemented functions such as product browsing, classification, shopping, and logistics address update for the web app based on Django.
- I complete the communication between the backend and the web App through Sockets based on Java, and implement basic functions such as packaging packages, notifications and collections, and updating logistics information of the logistics delivery system through protobuf. I assist teammates in building Hibernate mapping to establish objects with Django models and PostgreSQL relationship mapping.
Mar 2023 - Apr 2023 | Exchange Matching for Scalability
Tech Stack: C++, TCP, PostgreSQL, Concurrency
- Developed a trading system which will match buy and sell orders for a stock/commodities market.
- Used the pugixml library to parse large XML files and extracts order information, which is then passed on to the order matching engine.
- Using a row-level locking strategy, where each row in the orders table is locked when it is being modified to ensure that changes are made in the correct order.
- Analyzed the impact of the number of different orders of magnitude requests from multiple users on trading system and database operations.
Mar 2023 - May 2023 | Risk Game: Harry Potter style strategy game
Tech Stack: Java, JavaFX, TCP, Muti-Thread, JSON, CI/CD, Docker
- Developed a game which enables users to attack territories and obtain resources, move and upgrade soldiers, chat and ally with other players.
- Added concurrency to deal with multiple players. Use TCP socket and JSON for Server-Client communication.
- Based on JavaFX and Robot for UI Design and Testing.
- Applied Agile methodology, carried out issue tracking and CI/CD pipeline, drew UML diagram and prototype
Feb 2023 - Mar 2023 | HTTP Caching Proxy Server
Tech Stack: C++, Network, TCP Socket, Muti-Thread, Docker
- Established a HTTP caching proxy server which can handle GET, POST, CONNECT requests.
- Used C++ 11 to implement RAII technique and modeled class with strong exception safety guarantee.
- Added concurrency to handle requests from different endpoints. Used TCP sockets to send and receive packets.
- Improved efficiency by caching responses according to validation and expiration rules in RFC7234.
Jan 2023 - Feb 2023 | Web APP: Riding Sharing Service
Tech Stack: Python, Django, Docker, PostgreSQL
- Developed a full-stack web application Uber system with Django and PostgreSQL.
- Enable users to login/logout, request/search/select/drive for/join in rides, change/view order status.
- Build web-page with CSS, HTML and Bootstrap Library, and used Docker for web-app development.
Sep 2021 - Apr 2022 | Deep-Learning-Based 3D Reconstruction for Indoor Scene
Tech Stack: Python, Django, Docker, PostgreSQL
- Applied a deep-learning-based 3D reconstruction method based on Python for indoors using only RGB images as input, which can reconstruct the complete scene with better effect.
- Based on SFM and SIFT for feature extraction and RANSAC for key points matching, use Homography Matrix to calculate extrinsic parameter matrix and get the average camera intrinsic parameter error (3.9%).
Publications (Welcome to cite!)
[1] Zhe Fan, Xing Hu, Wen-Ming Chen, Da-Wei Zhang, & Xin Ma (2022). A deep learning based 2-dimensional hip pressure signals analysis method for sitting posture recognition. Biomedical Signal Processing and Control, 73, 103432. https://doi.org/10.1016/j.bspc.2021.103432
[2] Xing Hu, Zhe Fan, Linhua Jiang, Jiawei Xu, Guoqiang Li, Wenming Chen, Xinhua Zeng, Genke Yang, & Dawei Zhang (2022). TOP-ALCM: A novel video analysis method for violence detection in crowded scenes. Information Sciences, 606, 313-327.https://doi.org/10.1016/j.ins.2022.05.045
[3] Hu, X.; Xie, C.; Fan, Z.; Duan, Q.; Zhang, D.; Jiang, L.; Wei, X.; Hong, D.; Li, G.; Zeng, X.; Chen, W.; Wu, D.; Chanussot, J. Hyperspectral Anomaly Detection Using Deep Learning: A Review. Remote Sens. 2022, 14, 1973. https://doi.org/10.3390/rs14091973
