Ali Naderi Bakhtiyari, Ph.D. — mechanical engineer and researcher delivering AI-driven process optimization, monitoring, and control for high-power laser systems, from peer-reviewed research to features deployed on production machines.
I translate factory problems into deployed intelligent systems — and publish the science behind them. As Senior Algorithm Engineer in the R&D department of Bodor Laser, a leading laser cutting machine manufacturer, I develop and lead technology programs for AI-assisted parameter optimization, defect analysis, real-time process monitoring, and closed-loop control of 20/30 kW fiber-laser cutting.
My path runs from mechanical design and project engineering in Iran, through a Ph.D. in AI-based advanced manufacturing at Shandong University of Technology, to industrial algorithm leadership today. That combination — mechanical systems, laser-material physics, machine learning, and project execution — lets me carry a technology from research concept through experimental validation to a feature running on production machines.
I bring deep working experience inside the Chinese manufacturing ecosystem, international research collaborations, and English-language technical communication — a bridge between China's industrial scale, global academia, and the worldwide engineering community. Whether you're a recruiter, an industry partner, or a fellow researcher, you'll find both tracks of my work documented here.
| Current role | Senior Algorithm Engineer, R&D |
| Organization | Bodor Laser Co. |
| Location | Jinan, Shandong, China |
| Recognition | RAEng Global Talent (UK) |
| Work permit | China Tier A talent |
| Mobility | Available for global travel and relocation |
| Last updated | September 2026 |
Leading AI-enabled process optimization, monitoring, and control technologies for high-power fiber-laser cutting. Translating factory and customer process challenges into algorithm requirements, test matrices, validation criteria, and deployable software — while scouting cameras, sensors, and edge-computing hardware, and coordinating across algorithm, process, software, machine, application, and testing teams. Preparing schedules, milestone plans, and risk reviews covering sensor acquisition, hardware integration, data collection, and machine validation.
Designed ultrasonic transducers and mechanical components for industrial welding and cleaning equipment using CATIA, SolidWorks, and CAE simulation (Abaqus) — from customer requirements to 3D models, manufacturing drawings, prototype builds, supplier coordination, and reliability testing.
Coordinated design, manufacture, supplier follow-up, installation, and commissioning of ultrasonic homogenizer systems — tracking schedules, component quality, and site activities across technical, cost, and manufacturability constraints.
Developed ANN-based predictive models for thermal conductivity and viscosity of nanofluids using experimental datasets; results published in high-impact ISI journals.
Gained hands-on understanding of the technology and mechanical components of industrial casting processes at one of the region's leading steel manufacturers.
AI-assisted parameter optimization platform for 20/30 kW fiber-laser cutting. Automated recommendation across material, gas, thickness, pressure, speed, and focus — with safe process ranges, calibration logic, defect-driven feedback, adaptive optimization, and traceable rollback. Replacing manual trial-and-error on the factory floor, with expansion underway to tube and profile cutting.
Real-time process sensing built on coaxial vision, photodiode/pyrometer, acoustic emission, thermal imaging, and machine-head data. Analytics for melt-pool behaviour, piercing breakthrough, incomplete cutting, dross, and spatter — phased toward edge inference and reinforcement-learning-based adaptive control of pressure, speed, and focus.
Image-processing workflows for quality assessment and dimensional measurement — segmentation, feature extraction, calibration, robustness testing, and Cython acceleration — with camera resolution, NIR sensitivity, frame-rate, and latency trade-offs evaluated for shop-floor conditions. Includes 3D visualization of cut quality via Blender scripting and integration with the BodorThinker platform.
Compact CNN-GRU / CNN-TCN models for remaining-useful-life prediction evaluated under pruning and quantization for error, model size, CPU latency, and edge deployability (published in Machines, 2026). A companion auditable, deployment-aware multi-agent framework for automated RUL prediction and maintenance decision support on NASA C-MAPSS data is currently under review at Journal of Intelligent Manufacturing.
Thesis Research in nanosecond laser machining of sapphire with the aid of modeling and optimization methods
Supervisor Prof. Hongyu Zheng
Developed AI-based models (ANN, SVR) and multi-objective optimization techniques for nanosecond laser machining of sapphire — exploring laser-material interaction, laser-induced plasma behaviour, and surface functionalization through micro/nano-scale texturing for tailored wettability, friction, and optical properties. Produced 7 first-author and 9 co-authored ISI journal papers, 2 international conference papers, and collaborations with researchers in Saudi Arabia and Vietnam.
CSC Full ScholarshipOutstanding Ph.D. StudentThesis Mechanical properties and microstructure of equal channel angular rolled Al5083 and Al6061 samples, modelled with artificial neural networks
Supervisor Dr. Masoud Mahmoodi
Investigated the relationship between ECAR-induced microstructural changes and mechanical properties of aluminum alloys, developing ANN and nonlinear-regression models to predict tensile strength, hardness, and ductility from microstructural features.
Thesis Designing and manufacturing an ultrasonic digitizer
Supervisor Dr. Mohammad Amini
Designed and built an ultrasonic digitizer converting analog ultrasonic signals to digital form for medical imaging, non-destructive testing, and industrial automation applications.
Outstanding B.Sc. StudentPeer-reviewed work spanning AI-assisted manufacturing, laser processing, materials modelling, predictive maintenance, and process optimization — 26 journal papers and 4 conference papers published to date, plus one first-author manuscript under review. Selected first-author publications:
Endorsed under the Exceptional Promise criteria of the UK Global Talent route.
Classified as highly qualified foreign talent under China's tiered work-permit system.
A method for predicting laser cutting parameters and optimizing quality characteristics — No. 25-1-1226d.
American Society of Mechanical Engineers, Institution of Engineering and Technology, Society of Manufacturing Engineers, Institution of Mechanical Engineers.
Trained in Agile project delivery and non-destructive evaluation to ASME Boiler & Pressure Vessel Code Section V.
Guest Editor for the Special Issue on Intelligent Fault Diagnosis and Predictive Maintenance Systems; reviewer for Optics & Laser Technology, Optik, Heliyon, and Case Studies in Thermal Engineering.
Head of Research Core directing interdisciplinary smart-manufacturing initiatives; Teaching Assistant for the Press Die and Jig Design course.
Full China Scholarship Council doctoral scholarship; Outstanding Ph.D. Student and Outstanding B.Sc. Student awards.
Open to technology leadership opportunities, industrial collaboration, and research partnerships worldwide — whether you're hiring, building, or publishing. Have a quick question? My AI assistant can answer instantly, 24/7.
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