Applied Artificial Intelligence • Data Science • Rare Event Analytics • Independent AI & Data Analytics Project Developer(Open-Source Research)
This complex visual identity combines the 'Nexus of Data' and 'Bridge Builder' motifs to represent the centralization of data inputs and the AI-augmented synthesis used to bridge the gap between simulation and real-world insight.
I am an independent applied AI developer specializing in rare-event modeling, focusing on the synthesis, injection, detection, and rigorous evaluation of low-frequency, high-impact phenomena in visual and analytical data.
- Research-driven approach to applied AI systems
- Focus on rare events, adversarial environments, and uncertainty-aware modeling
- Experience designing end-to-end AI pipelines from data generation to decision support
- Interest in collaborations spanning academia, industry, and public sector
Based in Canada • English & French bilingual
My technical work is grounded in the following research areas:
- Cyber Threat Intelligence & Attack Simulation
- Generative AI for Synthetic Data Generation
- Anomaly Detection & Rare Event Modeling
- Digital Twins for Risk & Operations
- AI-Driven Decision Support Systems
- Statistical learning and probabilistic modeling
- Supervised and unsupervised ML for anomaly detection
- Hybrid pipelines combining LLMs + classical ML
- Explainability, robustness, and evaluation under real-world constraints
- Languages: Python, SQL, JavaScript
- ML & Data: Pandas, NumPy, Scikit-Learn
- Visualization: Power BI, Plotly, Dash, Tableau
- MLOps: Docker, GitHub Actions, Google Colab
Generative AI for Anomalous Behavior Detection in Cybersecurity
An end-to-end platform for simulating, detecting, and analyzing cyber threats.
Impact:
- Synthetic attack generation for ML benchmarking
- Threat scoring and risk classification
- SOC dashboards and executive-level reporting
- Reduced dependency on sensitive real-world data
🔗 https://github.com/atsuvovor/CyberThreat-Insight
- Synthetic cyber event generation
- Explanatory Data Analysi
- Feature engineering & labeling
- ML / AI threat detection models
- Model Performance Details
- CyberAttack-Insight Simulation
- SOC dashboards & executive reports
AI-Driven Cybersecurity & Operations Intelligence Platform
CyberThreat-Insight is an enterprise-grade platform providing simulation, analytics, and decision-support tools for cybersecurity and operational workflows. It integrates three core products:
CyberThreat-Insight/
├── README.md # Main project README
├── DT-Ops/
│ ├── README.md # DT-Ops module README
│ └── demo_app.py # Sample app or notebook
├── A2I-Insights/
│ ├── README.md # A2I-Insights module README
│ └── dashboards_demo.py
├── A2I-Copilot/
│ ├── README.md # A2I-Copilot module README
│ └── copilot_demo.py
├── docs/
│ └── high_level_cyber_threat_architecture.png
├── LICENSE
└── .gitignore
- Simulates operational and security scenarios
- Risk and outcome modeling
- AI-driven optimization layer
- Decision visualization Explore DT-Ops →
- Executive dashboards & KPI visualization
- Automated reporting
- Data-driven decision insights Explore A2I-Insights →
- RAG-based reasoning
- Contextual analysis of enterprise datasets
- Conversational data-exploration assistant Explore A2I-Copilot →
This research project focuses on Computer Vision–driven analytics for detecting, simulating, and analyzing rare, high-impact visual events in images and video streams. The goal is to bridge the gap between visual perception models and decision-level analytics, enabling reproducible research and real-world deployment.
The platform combines synthetic data generation, deep learning–based vision models, and downstream analytics dashboards to study events that are difficult to capture in real life due to rarity, cost, or safety constraints.
- CyberThreat-Insight - Generative AI for cybersecurity analytics
- DT-Ops - Digital twin for operational risk
- A2I-Insights - Executive AI analytics
- A2I-Copilot
Ongoing development, experimentation, and deployment of applied AI systems
with a focus on rare-event modeling, computer vision, and production-ready pipelines.
I am open to:
- Academic research collaborations
- Applied AI pilots and partnerships
- Grants, accelerators, and early-stage ventures
Atsu Vovor
Consultant, Data & Analytics
✉️ atsu.vovor@bell.net
🔗 LinkedIn | GitHub | Tableau Portfolio
📍 Mississauga ON
Thank you for visiting!🙏
Building AI systems that combine scientific rigor with real-world impact.