AI Neuroscience Research Framework
Systematic research agenda based on amygdala hijacking experiments and neuroscience-inspired AI systems
Phenomena Level
Discover and quantify neuron-like phenomena in AI
Structural Level
Understand architectural components' impact
Dynamics Level
Study temporal evolution and dynamic properties
Statistical Level
Establish universal laws and distributions
Defense Level
Develop neuroscience-based safety mechanisms
Module 1: AI Emotion Modeling & Hijacking
- Induced hijacking critical thresholds
- Spontaneous hijacking noise-memory phase diagrams
- Gating thresholds and feedforward inhibition
- Emotional attractor dynamics
- Power-law duration distributions
Module 2: AI Inhibition Mechanisms
- Feedforward inhibition design
- Feedback inhibition mechanisms
- Network stability enhancement
- Adaptive inhibition regulation
Module 3: AI Memory & Consolidation
- Dual-stage memory architecture
- SPW-R inspired replay mechanisms
- Selective memory consolidation
- Energy-constrained memory systems
Module 4: Learning & Plasticity Dynamics
- Bidirectional plasticity rules (LTP/LTD)
- Adaptive learning rate mechanisms
- Anomalous learning pattern detection
- Bias propagation dynamics
Module 5: Sequence Modeling & Structure
- θ-γ coupling simulation
- Hierarchical temporal modeling
- Neural grammar constraints
- Oscillatory hierarchical structures
Featured Projects
AgentForest.one
Multi-Agent SaaS PlatformBuilt a multi-agent SaaS platform orchestrating domain agents via shared Model Context Protocol (MCP) with full-stack deployment.
MedGPT.co
Medical AI PlatformAI-based medical toolset with 3,000+ organic users, integrating Hugging Face, OpenAI APIs, and Med-PaLM models for comprehensive medical solutions.
P-adic Machine Learning
Mathematical AI ResearchNovel approach to machine learning using p-adic number theory for enhanced numerical stability and pattern recognition.
ESR-GNN
Graph Neural NetworksEnhanced spectral residual graph neural networks for improved representation learning and node classification tasks.
Professional Experience
Founder & Principal Engineer
Leading end-to-end architecture & implementation of multi-tenant SaaS platform with MCP-based shared context and agent orchestration. Implemented AI serving with OpenAI/LLaMA APIs, RAG pipelines, and dynamic model routing.
Founder & Lead Engineer
Led technical architecture of MedGPT.co with 3,000+ organic users. Managed development of Android version and AI talking doctor platform using Flutter 3.7 and Python.
Cloud Engineer
Standardized IaC (Terraform) and container delivery (Docker/K8s) across GCP/Azure/AWS environments. Implemented CI/CD with versioning, canary deployments, and comprehensive monitoring.
Founder & Project Supervisor
Developed unified payment platform supporting major payment systems across Southeast Asia, Middle East, Europe, and North America with one-click enterprise access.
Achievements & Recognition
Patent Application
Type/No: Invention 1/2023/050166
Title: GPT-based Automated Medical Care System
Software Copyrights
12 Registered Copyrights
Including MedGPT AI Doctor, MedCloud.PH Platform, and various medical AI systems
Education
Bachelor's in ML & AI
Goldsmiths, University of London (2021-2024)
User Impact
3,000+ Users
Organic growth of MedGPT platform with 100+ daily new users
Research Publications & Roadmap
Planned Publication Strategy
Focus: Induced hijacking thresholds, spontaneous hijacking phase diagrams, gating mechanisms, emotional attractor dynamics
Focus: Power-law duration analysis, information bottleneck β-phase transitions
Focus: MEGA component causal analysis, defense mechanism minimal sets
Focus: Deep research based on five research modules