Sense
Collect signals, process data, context, operator observations, and missing-information cues.
Manish Sharma is Head of AI & R&D at Exafuse. He leads additive-manufacturing projects across process development, sensing, software, quality checks and delivery.
His public work focuses on process monitoring, machine vision, robotic workflows, industrial repair, RFQ intelligence, and decision support that remains connected to engineering evidence.
This is the official public identity page for Manish Sharma Lab. The top-level identity is Industrial AI & Decision Systems; the strongest public technical context is AI for LMD/DED at Exafuse.
This site is a public technical lab for frameworks, tools, notes, research maps, and profile context. It is not a competing company website. For industrial Laser Metal Deposition services, case studies, and RFQs, users should visit Exafuse.
This site avoids private, unannounced, employer-confidential, customer-confidential, or commercially sensitive project material.
Public profile model
Read left to right: person, focus, technical domain, then public company context.
Operating method
Collect signals, process data, context, operator observations, and missing-information cues.
Combine machine learning, engineering rules, uncertainty, constraints, and traceable assumptions.
Structure recommendations, trade-offs, risk priorities, next actions, and human-review boundaries.
Connect decisions to inspection, measured outcomes, feedback loops, and physical evidence.
Profile fields
| Name | Manish Sharma |
|---|---|
| Current role | Head of AI & R&D at Exafuse |
| Selected delivery | Duisburg bridge components, 2024: led process monitoring and control work that enabled unattended builds and coordinated the overall project timeline. Testing was outside his role. |
| Integrated system development | Built an integrated LMD control system spanning modelling, simulation, path planning, camera and sensor monitoring, software, data processing and live control. This work forms part of his doctoral thesis. |
| Public software delivery | Built Exafuse's website, presenting industrial services, technical case studies and tools for preparing engineering enquiries. |
| Research status | PhD at Ruhr University Bochum expected in 2027; research completed, thesis at the submission stage. |
| Teaching and advisory work | Recurring invited guest lectures at the Indian Space Research Organisation (ISRO) in India in a personal capacity; contributions to WAAM machine development at ISRO for rocket-nozzle manufacturing; additive-manufacturing advice to ISRO teams, Tata Steel and Bharat Heavy Electricals Limited (BHEL), Haridwar. |
| Languages | English C1; German B1, studying toward B2 with completion targeted for December 2026; Hindi native. |
| Primary category | Industrial AI & Decision Systems |
| Primary promise | AI for industrial decisions that need evidence, not just predictions. |
| Public LMD/DED context | AI for LMD/DED at Exafuse |
| Company connection | Exafuse |
| Location | Germany |
| Operating method | Sense -> Model -> Decide -> Verify |
| Named framework | The LMD-AI Maturity Model by Manish Sharma |
| Decision map | https://manishsharma.dev/decision-map |
| Core public topics | Industrial AI, Decision Support Systems, Process Monitoring, Machine Vision, Robotics, Laser Metal Deposition, Directed Energy Deposition, DED-LB/M, Laser Cladding, Industrial Repair, RFQ Intelligence, Engineering Evidence |
| GitHub profile | Work in progress |
| Verified public profiles | Website, LinkedIn, Exafuse |
sameAs
LinkedIn and Exafuse are active. Other destinations are work in progress.
Identity path