Fengcheng YuM.S. Student in Computer ScienceUniversity of Southern California Los Angeles, California, United States Email: yufc779 [at] gmail.com |
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I am Fengcheng Yu, currently an M.S. student in Computer Science at the University of Southern California (USC), where I began my graduate studies in August 2025. I work with Dr. Yue Wang in the Physical Superintelligence (PSI) Lab on world models and generative modeling, in collaboration with Toyota Research Institute (TRI).
Earlier at USC, I worked with Dr. Ramesh Govindan (Northrop Grumman Chair in Engineering, Professor of Computer Science at the University of Southern California), focusing on mobile systems, particularly real-time mobile sensing and low-latency data processing for in-vehicle perception systems.
Previously, I received my Bachelor of Engineering degree from Sun Yat-sen University in June 2025. From 2022 to 2023, I conducted research in the YCLab led by Dr. Calvin Yu-Chian Chen (陳語謙) (Director of AI for Science (AI4S) at Peking University). From 2024 to 2025, I continued my research training in Dr. Guang Tan (谭光)'s laboratory at Sun Yat-sen University.
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M.S. in Computer Science Computer Science (CS32) August 2025 - May 2027 | University of Southern California     GPA: 3.85/4.0 |
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B.Eng. in Intelligence Science and Technology Intelligence Science and Technology, Computer Science September 2021 - June 2025 | Sun Yat-sen University     GPA: 3.9/4.0, 3.9/5.0. |
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*** Paper Title ACM International Conference on Mobile Computing and Networking (MobiCom'26), 2026. Under Review. Chunyu Xia, Christina Suyong Shin, Fengcheng Yu, Chuan Li, Fan Bai, Harsha V. Madhyastha, Ramesh Govindan Real-time gaze-based target localization for in-vehicle perception systems via multi-camera mobile sensing. |
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Deflickering Vision-Based Occupancy Networks through Lightweight Spatio-Temporal Correlation IEEE Transactions on Image Processing (TIP), 2025. Under Review. Fengcheng Yu, Haoran Xu, Canming Xia, Ziyang Zong, Guang Tan A plug-and-play lightweight spatio-temporal correlation module that suppresses flickering in vision-based occupancy networks. |
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HouseTune: Two-Stage Floorplan Generation with LLM Assistance AAAI Conference on Artificial Intelligence (AAAI'26), 2026. Ziyang Zong, Guanying Chen, Zhaohuan Zhan, Fengcheng Yu, Guang Tan Two-stage floorplan generation that combines large language model guidance with a diffusion model. |
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Parkinson's severity diagnosis explainable model based on 3D multi-head attention residual network Computers in Biology and Medicine (CIBM), 2024. Jiehui Huang, Lishan Lin, Fengcheng Yu, Xuedong He, Wenhui Song, Jiaying Lin, Zhenchao Tang, Kang Yuan, Yucheng Li, Haofan Huang, Zhong Pei, Wenbiao Xian, Calvin Yu-Chian Chen An interpretable 3D multi-head attention residual network for severity diagnosis of Parkinson's disease from facial video. |
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Edge FaaS Cold-Start Mitigation via EWMA + CUSUM Prediction USC CSCI599, Network System for Cloud Computing — Course Project, Dr. Ramesh Govindan A clean-slate, bare-metal C++ FaaS worker targeting cold-start in edge serverless. Uses OS-level Copy-on-Write process primitives to isolate the prediction algorithm from container/KVM noise. Strict Reactor / 64-thread DispatchPool separation; the EWMA + CUSUM predictor runs in O(1) time and memory. |
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HareMQ Simulation implementation of RabbitMQ core functions A C++ message queue inspired by RabbitMQ. Supports direct/topic/header/fan-out exchanges, message persistence, high availability, and multiple concurrent clients. |
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Boost Search Engine A search engine implementation based on the Boost library A specialized search engine over the Boost library documentation. Covers the full pipeline — data preprocessing, inverted index construction, query processing, ranked result presentation — with word-frequency scoring and dynamic index updates. |
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Load-balanced Online Judge System An online algorithm question-solving service, similar to LeetCode A LeetCode-like online coding and evaluation platform — write, submit, and judge code in the browser with instant feedback. Includes Ace editor integration and a custom load balancer over distributed multi-process/multi-thread judges. |
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Google Tcmalloc Simulation Implementation A high-concurrency memory pool replacing native A simulation of Google's tcmalloc — a high-concurrency memory pool replacing native |
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Multi-pattern Logging System A C++ logging system with multi-level logging, sync/async modes, and pluggable output sinks Pluggable sinks (console, file). Thread-safe by design, applying classic OOP patterns throughout. |
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Event-Driven Pipeline Communication System Framework An epoll-based event-driven IPC framework Modular structure for easy integration and extension across different environments. |
| Outstanding Student Scholarship, SYSU — 1st Prize 🥇 | 2022 |
| Outstanding Student Scholarship, SYSU — 2nd Prize 🥈 | 2023 |
| Outstanding Student Scholarship, SYSU — 3rd Prize 🥉 | 2024 |
| Academic Competition Scholarship, SYSU | 2022 |
| Arts and Sports Scholarship, SYSU (awarded consecutively) | 2022–2024 |
| 1st Prize, Asia and Pacific Mathematical Contest in Modeling (national-level) | 2022 |
| 2nd Prize, China University Computer Competition — Group Programming Ladder Competition (Guangdong) | 2023 |
| 2nd Prize, "LanQiao" Cup National Software Competition (C/C++) — Guangdong Division | 2023 |
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Virtualization R&D Engineer Intern Winhong Information Technology Co., Ltd., R&D Department January 2024 - February 2024 | Guangzhou, China Initiated and developed the "virtual machine probe" using Libvmi to monitor KVM architectures effectively. Enhanced VM-to-host interactions through spice-protocol, enabling clipboard sharing and file dragging. Produced detailed documentation on new tools and protocols, significantly improving development and testing efficiency. Established a Confluence workspace for a five-person team. |
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R&D Center Intern Lingzong Technology (Shenzhen) Co., Ltd. July 2024 - September 2024 | Shenzhen, China Conducted in-depth research on advanced occupancy prediction technologies such as SurroundOcc and SelfOcc, focusing on understanding and experimenting with their core functionalities. Researched the mechanism of "multi-head prediction" in occupancy prediction and adjusted the original model structure to enhance accuracy. |
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Backend Development Content Creator CSDN — one of China's largest tech communities October 2021 - Present Selected as a high-quality backend development content creator. Published 150+ technical blogs covering system design, distributed computing, and backend frameworks; received over 420,000 visits; built an engaged community with 8,000+ followers. Selected highly rated columns (Posts in Chinese): |
std::deque following the STL design, including the segmented buffer layout and iterator arithmetic.thread_control core.