Arman NeyestaniComputer Vision · MeasurementResume

About Arman

A computer vision engineer building systems that measure.

Portrait of Arman Neyestani at a research conference.
Computer vision · measurement science · robotics

I build camera-based vision systems for structural health monitoring and visual measurement. I connect learned perception with camera geometry, calibration and physical reference data so results can be interpreted and checked.

I am a Research Fellow at CeSMA, University of Naples Federico II, where I develop non-contact pipelines for structural displacement and deformation. I completed my Ph.D. in Information Technology for Engineering at the University of Sannio in 2025.

My secondary work includes visual odometry, localization, underwater imaging and environmental sensing. Across these projects I combine image processing, geometric reasoning, machine learning and reference measurements.

I focus on calibration, synchronization, repeatability and failure analysis, and I explain how they affect each measurement.

LinkedIn ↗GitHub ↗

Current role

Research Fellow — Computer Vision for Structural Health Monitoring

CeSMA, University of Naples Federico II · Camera calibration, tracking, physical-unit conversion, temporal alignment, reference-sensor comparison, and uncertainty-aware interpretation.

Arman Neyestani with colleagues at CeSMA, University of Naples Federico II.
Current role - Research collaboration at CeSMA, University of Naples Federico II.

Research focus

Reliable visual systems for imperfect physical environments.

01

Visual measurement

Calibration, reference comparison, repeatability, uncertainty, and failure analysis.

02

Geometric vision

Camera models, PnP, projective geometry, visual odometry, and sensor fusion.

03

Applied machine learning

Detection, segmentation, metric learning, time-series models, and reproducible evaluation.

Field notes

Awards, experiments, talks, and research community.

Chronological archive of awards, talks, and research community moments.

Arman Neyestani holding the MetroXRAINE first-place certificate.
London, 2024 - MetroXRAINE Young Researchers Program, first-place recognition in the classification-accuracy category.
Arman Neyestani and the MetroXRAINE Young Researchers Program award recipients on stage in London.
London, 2024 - On-stage presentation of the first-place classification-accuracy award at the MetroXRAINE Young Researchers Program.
Student Best Paper Award presentation at IEEE I2MTC 2025.
IEEE I2MTC 2025 - Student Best Paper Award presentation for the SUBVO underwater-vision study.
Student contest award presentation at IEEE I2MTC 2025.
IEEE IMS Student Contest, 2025 - Third-place award presentation for the student competition.
Arman Neyestani and a colleague at their student contest demonstration booth.
Germany, 2025 - Student contest demonstration booth and research work shown to the conference community.
Research colleagues together at Metrology for Living Environment 2026.
Metrology for Living Environment, 2026 - Research colleagues gathered during the conference program.
Lecture hall during Arman Neyestani's DeepTag presentation.
Metrology for Living Environment, 2026 - Lecture-hall presentation of the DeepTag structural measurement work.
Arman Neyestani presenting preliminary DeepTag structural testing.
Metrology for Living Environment, 2026 - Close view from the talk on preliminary structural dynamic testing.
Arman Neyestani serving in a conference session at MetroSustainability.
IEEE MetroSustainability - Conference service as session chair, connecting measurement research with the wider program.

Awards

Awards & honors

3rd place · IEEE I2MTC 2025 Student Best Paper Award for SUBVO
Recognized the underwater visual-odometry dataset and benchmark: calibrated pool imagery, measured ground truth, and a reproducible feature-evaluation pipeline.

3rd place · IEEE IMS Student Contest 2025
Awarded for a solar-powered tree-health monitoring concept combining environmental sensors, RGB cameras, edge AI, weather and air-quality sensing, wildlife monitoring, and fire detection.

1st place · IEEE MetroXRAINE 2024 Young Researchers Program, classification accuracy category
Won with the concrete-crack verification project: a triplet-loss ResNet-101 system that learns image embeddings to decide whether two crack images show the same pattern.

Academic service

Selected service

Special Session Convener / Organizer
IMEKO World Congress 2027 · Data-Driven Models for Vision-Based Measurement Systems

Session Chair
IEEE MetroLivEnv 2026 · Metrology for Sustained Quality of Life

Presenter
International IEEE and IMEKO conferences across measurement, AI, structural, and marine sensing.