Projects

Selected technical projects.

Intelligent Sanitation Robot Implementation Based on Deep Learning

Time: Jul 2025
Note: Main practical assignment for the NUS SoC Summer Workshop Program.

  • Applied transfer learning on YOLOv7 for multi-object detection: trash (paper and bottles), cigarettes, violent behavior, and human falls.
  • Built a crane-style structure with servo-controlled grabbing arms and launching mechanism on a robot car.
  • Integrated Arduino and Raspberry Pi for hardware control.

Real-time Facial Emotion Analysis System on Jetson Nano

Time: Dec 2025
Note: Main practical assignment for the Deep Learning course.

  • Fine-tuned a lightweight face detection model (CNN with RFB modules) on a custom emotion dataset.
  • Deployed models on the Jetson Nano edge computing platform.

Modeling and Optimization of Voting Mechanisms in Dancing with the Stars

Time: Feb 2026
Note: Achievement of 2026 MCM.

  • Addressed voting controversies using Bayesian inverse estimation, counterfactual simulations, and XGBoost with the CPISeq framework.
  • Proposed a Four-Strike Rank Fusion voting rule for fairness in high-conflict scenarios.

Pipelined RISC-V CPU Design and Implementation Based on Verilog

Time: May 2025
Note: Main practical assignment for the Computer Organization course.

  • Implemented a five-stage pipelined CPU (RISC-V 32I) on the EGO1 FPGA board.
  • Added UART communication, branch prediction, and a Python GUI for real-time register and pipeline visualization.

Performance Comparison and Evaluation of openGauss vs. PostgreSQL

Time: Dec 2024
Note: Main practical assignment for the Principles of Database Systems (H) course.

  • Compared openGauss and PostgreSQL via pgbench across query performance, concurrency, connection efficiency, import speed, resource utilization, and security.

Java Swing-Based Match-3 Puzzle Game

Time: Dec 2023
Note: Main practical assignment for the Introduction to Computer Programming A (H) course.

  • Designed and implemented a Match-3 game with multi-level progression, score and move limits, and both manual and auto-play modes.
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