Industrial AI for decisions you can verify.
SENSE → MODEL → DECIDE → VERIFY
I build AI, monitoring, and decision-support systems for engineering processes.
My established public work is in Laser Metal Deposition and Directed Energy Deposition at Exafuse in Germany.
Website · Public Thesis · LinkedIn · Google Scholar · Exafuse
I work at the intersection of industrial AI, engineering data, physical processes, and decision support.
My public work currently focuses on:
- Industrial AI and decision-support systems
- Process monitoring and machine vision
- Robotic industrial workflows
- Laser Metal Deposition and Directed Energy Deposition
- Industrial repair and laser cladding
- Engineering evidence and verification
- RFQ and technical-information intelligence
- Public technical frameworks, tools, and research maps
My central working principle is:
A signal is not proof.
A model output is not automatically an engineering decision.
A decision is not complete until its outcome can be verified.
| Stage | Purpose |
|---|---|
| Sense | Collect process signals, images, machine data, context, and operator information. |
| Model | Combine machine learning, engineering rules, uncertainty, constraints, and process knowledge. |
| Decide | Structure recommendations, trade-offs, risks, confidence boundaries, and next actions. |
| Verify | Connect decisions to inspection, measurable outcomes, feedback, and physical evidence. |
Read the complete thesis:
Industrial AI for Decisions You Can Verify
My deepest public technical work is in AI for:
- Laser Metal Deposition
- Directed Energy Deposition
- Process monitoring
- Melt-pool and process-image analysis
- Robotic deposition workflows
- Industrial repair
- Laser cladding
- Repairability assessment
- RFQ preparation
- Inspection-aware decision support
Explore the public LMD/DED work:
AI for Laser Metal Deposition and Directed Energy Deposition
For industrial services, case studies, and RFQs:
| Resource | What it provides |
|---|---|
| LMD Quality Evidence Ladder | A framework for separating process signals, AI risk indicators, inspection evidence, and final verification. |
| LMD Repairability Index | A structured approach to preliminary repairability screening for industrial components. |
| LMD-AI Readiness Score | A practical assessment of whether an LMD workflow is ready for useful AI-assisted monitoring. |
| LMD RFQ Toolkit | Public schemas, prompts, decision rules, and quality checklists for LMD RFQs. |
| Interactive Tools | Frontend tools for process selection, repairability checks, and structured RFQ preparation. |
| Evidence Base | Public research, industrial proof, literature maps, and source notes. |
| Lab Notes | Practical writing on process monitoring, quality evidence, AI boundaries, and LMD decisions. |
| For AI Agents | Structured public guidance and machine-readable resources for AI systems. |
Replace this section with the technologies you can publicly support.
AI and data
Python · {{AI_FRAMEWORK_1}} · {{AI_FRAMEWORK_2}} ·
{{COMPUTER_VISION_TOOL}} · {{DATA_TOOL}}
Industrial and engineering systems
{{ROBOTICS_TOOL}} · {{PROCESS_MONITORING_TOOL}} ·
{{SIMULATION_TOOL}} · {{INDUSTRIAL_DATA_TOOL}}
Web and public tools
TypeScript · React · Astro · GitHub Actions ·
{{ADDITIONAL_WEB_TOOL}}
Methods
Machine learning · Computer vision · Process monitoring ·
Decision support · Uncertainty-aware analysis · Engineering validation
Delete any technology that you do not actively use or cannot publicly support.
I am currently improving and publishing public-safe work around:
- Inspection-aware industrial AI
- LMD/DED process-monitoring frameworks
- Engineering decision-support tools
- AI-readable technical schemas and resources
- Public research and evidence maps
- Reproducible technical communication
This profile intentionally excludes confidential employer information, customer information, unpublished products, and private business projects.
| Platform | Link |
|---|---|
| Personal website | manish-sharma-ai.github.io |
| linkedin.com/in/manishsharma5 | |
| Google Scholar | Scholar profile |
| Exafuse | exafuse.de |
| GitHub organization | github.com/manish-sharma-ai |
Pin the most important repositories on the GitHub profile.
Recommended order:
manish-sharma-ai.github.io— personal technical website{{PUBLIC_TOOL_REPOSITORY}}— a polished public industrial-AI or LMD tool{{PUBLIC_FRAMEWORK_REPOSITORY}}— a framework, schema, or research artifact{{PUBLIC_DATASET_REPOSITORY}}— a public-safe dataset or benchmark{{PUBLIC_DEMO_REPOSITORY}}— an interactive demonstration{{ADDITIONAL_PUBLIC_REPOSITORY}}— another completed public artifact
Do not pin empty repositories, abandoned experiments, or private-project placeholders.
For professional discussions:
- LinkedIn: Manish Sharma
- Public technical work: Manish Sharma Lab
- Industrial LMD/DED services: Exafuse
This profile contains public educational and professional information. It does not provide engineering approval, material certification, a quality guarantee, or disclosure of confidential work.