Implicit Signal Mining for Personalized Decision Systems
Chika Komari
A unified track across structural, semantic, and psychological signal mining
I focus on implicit signal mining in complex information networks for risk-aware and personalized decision systems. Current orbit — O1-KR1 (due June 30, 2026): critical node identification on multi-layer heterogeneous networks
Observe
从复杂网络中听见微弱但可行动的信号
结构、语义与心理信号并不是三座孤岛;它们共同指向更可靠、更个性化的决策系统。
- Publications / Preprint
- 3
- 1 under review · 1 accepted · 1 NeurIPS poster preprint
- GPA / Rank
- 4.04/5.00 · 15/154
- Sun Yat-sen University (School of Intelligent Systems Engineering)
- Kaggle Models Views / Downloads
- 2.7K+ / 1.0K+
- CSIRO Biomass Prediction Model Series
- Kaggle Tier
- Notebooks Expert
- Kaggle Progression tier (2025-Present)
- Internship
- Evolution Asset Management
- AI Intern (Apr 2025 - Present)
- GitHub Contributions
- 800+
- Public contribution activity across projects
Structure
将研究路线组织成一张可追踪的星图
每条轨道都连接问题、阶段、证据与下一步,而不是只展示一个抽象进度数字。
Psychological Signal Mining
Psychological Signal Mining (Personalized Decision and Interaction) · 1 roots / 3 nodes
Semantic Signal Mining
Semantic Signal Mining (Financial Knowledge Graphs) · 1 roots / 3 nodes
Structural Signal Mining
Structural Signal Mining (Critical Nodes in Complex Networks) · 1 roots / 3 nodes
Orchestrate
让模型、数据、Agent 与证据形成可复用的工作流
成果不是孤立的展示柜,而是可以回到研究路径中继续运转的仪器。
Embodiment
一个能随主题重组、却始终保持同一身份的观测员
深色与浅色形态共享六组分节动作:旧姿态先缩小隐去,新姿态再放大显现;转身、迈步、回望与手势由清晰轮廓交接。她不是装饰性吉祥物,而是研究、编程与个人兴趣之间的可视化接口。
- Role
- Signal Observer
- Mode
- Void / Moon Paper
- Method
- Structure → Evidence → Decision
- Temper
- Precise · Tender · Curious
Archive / Afterlight
研究归档之后,仍有乐队、日常与相遇留下的余辉
这里保留最近写作,也保留塑造审美与情绪节奏的记忆信号。
Public telemetry
持续工作的轨迹,也是一种可验证信号
当外部数据源不可用时,这一模块会保留清晰的降级状态,并始终提供 GitHub 原始入口。