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Niher Halder

Niher Halder

Engineer–Strategist for Critical Infrastructure Risk & Resilience in Power & Industrial Systems

Vision

To strengthen the safety, resilience, and trustworthiness of critical power and industrial systems by bridging real-world engineering experience with explainable, process-aware OT/ICS cybersecurity.

Mission

  • Apply deep understanding of safety-critical infrastructure to identify and mitigate system-level risks in power and industrial environments.
  • Develop and promote process-aware, explainable security approaches that align with how industrial systems actually operate.
  • Integrate risk engineering, resilience thinking, and OT/ICS cybersecurity to support secure and reliable critical energy systems.
  • Share practical insight through research, writing, and engineering-led security practice to contribute to safer critical infrastructure worldwide.

Current focus: AI-driven cybersecurity for industrial systems — integrating automation and data-driven analysis to support anomaly detection and threat modeling in power and energy environments. My long-term direction is to bridge engineering reality, cybersecurity, and intelligent automation for critical infrastructure in ways that remain practical, explainable, and operationally safe.

Welcome to My Work

My website is structured around three pillars: field experience, focused writing, and target-aligned projects.

📷 Field Experience Gallery

A visual record of my work in safety-critical infrastructure—showing the environments where reliability, safety, and operational constraints matter.

Safety-critical On-site reality Engineering rigor
Open Gallery

✍️ OT/ICS Security Blog

Articles on AI-driven cybersecurity in gas & power—anomaly detection, process-aware defense, and practical thinking for operators and engineers.

Gas & Power Anomaly Detection Threat Modeling
Read Blog

🧪 Target-Aligned Projects

A curated set of projects showing strength in AI, programming, automation, and security-thinking—built with clear documentation.

AI/ML Automation Explainability
Explore Projects

Field Experience (Preview)

These photos highlight the environments and constraints that shape my approach to cybersecurity: safety, uptime, process integrity, and real-world tradeoffs.

View Full Gallery

Latest Writing (Preview)

Short, structured posts focused on OT/ICS security + AI for gas and power systems. (Start with 3 posts and grow steadily.)

Why IT Security Models Fail in Power & Gas Plants

What changes when uptime and safety are non-negotiable—and how defenders should adapt.

Category: OT/ICS Fundamentals • 6–8 min read
Anomaly Detection Needs Process Context

Reducing false positives by connecting signals to operations and process states.

Category: AI for OT • 7–10 min read
Threat Modeling in OT: Start With Consequence

Map cyber events to physical impact and prioritize mitigations that won’t disrupt operations.

Category: Threat Modeling • 6–9 min read
See All Posts

Featured Projects (Preview)

A small set of deeply documented projects. Fewer projects, higher quality.

🏠 House Price Prediction (XGBoost)

ML workflow practice: feature engineering, validation, tuning, and deployment mindset.

  • CV RMSE: 0.1229 (log-space)
  • Kaggle Score: 0.12826
  • Status: ✅ Completed

🔗 GitHub Repo  |  📄 Summary PDF

🧠 Facial Keypoints Detection (CNN)

Deep learning practice: architecture, training stability, evaluation discipline.

  • Val RMSE: 0.0230
  • Val MAE: 0.0163
  • Status: ✅ Completed

🔗 GitHub Repo  |  📄 Summary PDF

Next (OT/ICS Project Roadmap)

Planned: OT/ICS anomaly detection (time-series telemetry + operationally meaningful alerts). Will include baselines, model comparison, false-positive control strategy, and an architecture diagram.

Go to Projects