Brandon Wong

Education

TU Eindhoven
Eindhoven University of Technology

Eindhoven, the Netherlands

Sep. 2024 -

Research Honors Master of Science in Computer Science and Engineering

Current GPA   8.3/10.0

NWAFU
Northwest A&F University

Yangling, China

Sep. 2019 - Jul. 2024

Bachelor of Engineering in Software Engineering

Major GPA   3.82/4.0

Graduation Thesis Research and Implementation of Skeleton Extraction Method for Incomplete Tree Trunk Point Clouds [Abstract]

Research

Topology-aware Temporal Matching of River Channel Networks

Feb. 2025 - Aug. 2025 @ Eindhoven University of Technology

  • One of two student researchers working on temporal matching of braided river evolution across multiple decades.
  • Built upon Kleinhans et al.’s δ-network construction using descending quasi Morse–Smale complexes on riverbed terrains.
  • Proposed a new hierarchical graph-based representation of braided river networks, enabling flow-consistent direction annotation of river segments.
  • Integrated both geometric and topological context into segment matching, applying Dynamic Time Warping (DTW) to align river fragments across time.
  • Refined DTW results with topology-aware correction, yielding more robust and interpretable temporal correspondences between river networks.
AbstractCode
Context-Enriched Abstract Syntax Tree Construction for Code Representation

Apr. 2025 - Jul. 2025 @ Eindhoven University of Technology

  • Designed a multi-stage pipeline to transform raw C++ and Python source code into enriched Abstract Syntax Trees (ASTs) with unified structural semantics.
  • Implemented type annotation extraction, variable reference resolution, and statement-order encoding to capture both syntactic and semantic program contexts.
  • Developed language-specific enrichment strategies using ClangAST for C++ and astroid/astypes for Python, harmonizing heterogeneous AST formats.
  • Introduced virtual edges for execution sequence and reference links to enable static validation of variable usage and control-flow consistency.
  • Achieved high structural coverage and semantic completeness on large-scale datasets, producing ASTs suitable for structure-aware generative model training and cross-language analysis.
Paper (Core Sections)Code
Automatic Stem Reconstruction from Incomplete 3D Point Cloud

Sep. 2022 - Jun. 2024 @ Northwest A&F University

  • Designed and implemented a full pipeline for tree trunk modeling from incomplete LiDAR point clouds, including segmentation, skeleton extraction, optimization and reconstruction.
  • Proposed an improved L1-medial skeleton method with RANSAC-based local cylinder fitting and global continuity correction, significantly enhancing robustness under occlusions.
  • Developed a circle-constrained B-spline reconstruction model, enabling accurate and realistic stem surface recovery from incomplete cross-sections.
  • Conducted quantitative and qualitative experiments on synthetic and real-world data, achieving up to 74.9% accuracy improvement in extreme missing-data scenarios.
  • Contributed a practical solution for precision forestry, advancing reliable trunk modeling and measurement under challenging field conditions.
3D Animation of Simulated Butterfly Swarm Flight Based on Gesture Control

Oct. 2022 - May. 2024 @ Northwest A&F University

  • Developed a graph-based control framework for swarm flight animation, preserving structural relations among individuals while following user-specified paths.
  • Implemented path generation algorithms from both continuous curves and discrete gesture points, ensuring smooth swarm trajectories via Frenet–Serret frames and Catmull–Rom splines.
  • Designed a tree-based hierarchical representation of swarm interior patterns, enabling pattern preservation and topological consistency during motion propagation.
  • Proposed multiple motion propagation strategies (observation-based, latency-compensated, communication-based) and analyzed their trade-offs in accuracy, naturalness, and computational efficiency.
  • Demonstrated that the framework balances biological realism and precise coordination, offering applications in computer animation, swarm robotics, and interactive VR environments.
Feature Point Extraction from 3D Point Clouds of Power Pylons

Sep. 2021 - Apr. 2023 @ Northwest A&F University

  • Proposed a genetic algorithm–based axis correction method to normalize inclined pylon point clouds.
  • Applied statistical segmentation to divide pylons into head, body, and base for segment-specific feature extraction.
  • Combined geometric algorithms (Delaunay triangulation, Douglas–Peucker, RANSAC, Hough transform) with AI-inspired methods to improve robustness under noise and missing data.
  • Achieved more complete and detailed 3D reconstruction of lattice structures compared to manual or purely model-driven approaches.

Publication

Graph-based control framework for motion propagation and pattern preservation in swarm flight simulations

May 2024

Authors: Feixiang Qi, Bojian Wang, Meili Wang

Computer Animation and Virtual Worlds, Volume 35, Issue 3
Abstractdoi:10.1002/cav.2276