Experience

Education, technical interests, project experience, skills, and honors.

Education

Beijing Forestry University, School of Engineering — B.Eng. candidate in Automation, September 2024–June 2028 (expected)

  • Weighted average: 91.69/100, ranked 8/84 in the major
  • CET-6: 622

Technical Interests

  • Robotics and embodied intelligence
  • Robotic-arm control and state-machine design
  • Computer vision and RGB-D perception
  • Bayesian inference, MCMC, and data-driven decision-making

Available for an on-site internship 3–4 days per week.

Research and Project Experience

Embodied Robotic Collaboration for Precision Assembly — 2026

  • Used a multimodal model to parse task cards into structured assembly steps, followed by deterministic whitelist, sequence, and range validation before execution.
  • Triggered VisionMaster processes over TCP and waited for measured coordinate messages before entering the motion stage, preserving vision–motion sequencing.
  • Mapped visual coordinates to robot coordinates and executed MoveJ/MoveL commands through the AUBO ARCS SDK/RPC interface.
  • Organized grasping, placement, reset, and exception handling with a state machine while retaining state, timestamp, and execution logs.

Blueberry Maturity Detection and RGB-D Data Management — 2026

  • Trained a YOLO model to identify unripe, semi-ripe, and ripe blueberries and built an application with confidence adjustment, dashboards, and CSV export.
  • Integrated Intel RealSense D435i/D405 cameras for single-frame and continuous acquisition, session metadata, dataset indexing, and integrity auditing.
  • Computed valid-depth ratio, center depth, median depth, and related quality metrics to generate standardized acquisition reports for 3D localization and model training.

OpenMV and STM32F407 Intelligent Rescue Vehicle — April 2026

  • Used an OpenMV4 H7 Plus for color thresholding, blob filtering, and target localization, including horizontal-offset estimation for multiple target categories.
  • Implemented mecanum-wheel inverse kinematics on the STM32F407 and drove four motors through TB6612 PWM outputs, using encoder feedback and PID at an approximately 10 ms update period.
  • Organized search, tracking, approach, grasp/transport, and return behaviors with a task state machine.

Bayesian Inference and Dynamic Scoring in Voting Systems — 2026

  • Received Finalist (F Award) in the 2026 MCM/ICM; the related paper was accepted by Axioms, with me as the third author.
  • Built a Bayesian model under hierarchical constraints, using a Dirichlet prior and Metropolis–Hastings MCMC to infer latent audience votes.
  • Compared ranking, percentage, and judges’ intervention mechanisms and used Lasso to analyze influential factors.
  • Proposed an uncertainty-aware Expert–Public Fusion framework and evaluated it on 34 seasons and 2,777 observations, achieving 0.9655 reconstruction accuracy.

Publication

Constrained Bayesian Reconstruction of Latent Public Preferences under Dynamic Elimination Rules: An Uncertainty-Aware Expert–Public Fusion Framework — Axioms, accepted, 2026; third author. Volume, issue, pages, and DOI will be added after online publication.

Skills

  • Programming: Python, C, Git, LaTeX
  • Robotics and control: AUBO ARCS, STM32 HAL, PID motion control
  • Vision and perception: YOLO model training, VisionMaster, Intel RealSense D435i/D405, OpenMV4 H7 Plus

Honors

  • National Scholarship, 2024–2025 academic year
  • Finalist (F Award), Mathematical Contest in Modeling / Interdisciplinary Contest in Modeling, 2026
  • First Prize and Advancement, Beijing–Tianjin–Hebei Regional Embodied Intelligence Precision Assembly Competition, 2026
  • Second Prize, Beijing, China Undergraduate Mathematical Contest in Modeling, September 2025
  • Third Prize, Beijing, National Undergraduate Electronics Design Contest, August 2026
  • Second Prize, University Level, Intelligent Rescue Track, Engineering Practice and Innovation Competition, April 2026