Home
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.

O1-KR1 (due June 30, 2026): critical node identification on multi-layer heterogeneous networks O1-KR2 (due September 30, 2026): scalable financial knowledge-graph infrastructure and signal mining automation O2-KR1 (due December 31, 2026): personalized multi-device AI companion based on Airi

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

GitHub Commit Activity

Open GitHub

Last 12 months

Syncing GitHub profile contributions...

Source: GitHub profile graph

Live contributions are fetched from your public GitHub profile graph.

Roadmap Snapshot

View Full Roadmap

Psychological Signal Mining

Avg. progress 11.1% · 1 roots / 3 nodes
Planned Psychological Signal Mining (Personalized Decision and Interaction)

Semantic Signal Mining

Avg. progress 11.1% · 1 roots / 3 nodes
Ongoing Semantic Signal Mining (Financial Knowledge Graphs)

Structural Signal Mining

Avg. progress 11.1% · 1 roots / 3 nodes
Ongoing Structural Signal Mining (Critical Nodes in Complex Networks)

Featured Artifacts

Browse All Artifacts
Alignment Between the Minds (ICML 2026 Submission)

Alignment Between the Minds (ICML 2026 Submission)

研究具身体在多轮指令交互中对用户潜在偏好的持续推断、维护与利用，聚焦高维心理信号挖掘。

paper Latent Preference DiscoveryEmbodied Agent
Identifying Critical Nodes with Deep Learning and Reinforcement Learning

Identifying Critical Nodes with Deep Learning and Reinforcement Learning

研究城市路网场景下的关键节点识别与影响力传播建模，属于低维结构信号挖掘方向的核心成果。

paper Complex NetworkCritical Node Identification
AIRI LocalGUI Task Agent (Open Source; In Progress)

AIRI LocalGUI Task Agent (Open Source; In Progress)

把自然语言指令转换为可执行桌面任务计划，支持自动校验、自动修复与多工具协同执行。

project Desktop AutomationPlanner-Executor

Latest Updates

Open Blog
本体工程：本体论 (Ontology Engineering: Ontology)

本体工程：本体论 (Ontology Engineering: Ontology)

本体工程（Ontology Engineering）是知识表示与本体构建的系统化方法论，主要关注如何在人工智能和语义网领域中设计、实现和维护高质量的本体。它涉及多种技术与理论，包括一阶逻辑、描述逻辑、统计关系学习等，用于建立领域知识的结构化表示。

2026/07/20 logic
本体工程：初识本体的构建 (Ontology Engineering: First Time View of Ontology building)

本体工程：初识本体的构建 (Ontology Engineering: First Time View of Ontology building)

Palantir 本体是该组织的一个操作层。该本体位于集成到 Palantir 平台中的各种数字资产之上（如数据集、虚拟表、模型等），并将这些资产与现实世界中的实体进行连接——从物理资产如工厂、设备、产品，到概念如客户订单或金融交易等。在许多场景中，该本体充当了组…

2026/07/20 logic
Google 软件工程-风格指南与规则

Google 软件工程-风格指南与规则

在进行软件开发的流程中，设置和持续维护一套风格指南与规则，用于指导开发至关重要。

2026/03/18 software_engineering
Google 软件工程-团队领导与生产力度量

Google 软件工程-团队领导与生产力度量

在进行多人协作的过程中，需要发挥良好的团队领导才能并合理度量生产力，尽可能地用合理的方式解决问题。

2026/03/11 software_engineering
Google 软件工程-团队合作与知识管理

Google 软件工程-团队合作与知识管理

在进行项目时，如何更好地参与团队合作与进行知识管理，是一个值得思考的问题。

2026/03/04 software_engineering
  • Jan 2026: submitted first-author ICML 2026 paper on latent preference discovery
  • 2025: accepted at GBCESC 2025 and received Best Paper Award
  • Since Apr 2025: building financial knowledge-graph infrastructure at Evolution Asset Management