Vai al contenuto principale
Cesare Davide Pace

Cesare Davide Pace

AI Research Engineer | Computer Vision & Intelligent Systems

Talento
CassinoMembro dal 4 settembre 2026
Computer visionDeep learningObject detectionVision TransformersUncertainty estimationPyTorchTrainingBenchmarkingAblation studiesPythonTestingDeploymentEarth ObservationEnvironmental monitoringBiomechanicsIntelligent sensing
·

Assumi questa persona

Invia una proposta di lavoro direttamente a questo candidato

Computer visionDeep learningObject detectionVision TransformersUncertainty estimation

Info

AI research engineer and Industrial PhD candidate specialising in computer vision, deep learning, and the development of data-driven systems from research question to deployment.

Designed

Poseidon, a multi-frame Vision Transformer for video pose estimation, and developed applied AI solutions for geospatial detection, clinical movement analysis, predictive environmental monitoring, and privacy-aware video processing. Author of 11 scientific publications, including 5 as first author, with public Python repositories and experience collaborating with researchers, clinicians, engineers, and domain specialists. Interested in contributing to Leonardo across applied AI, Space and Earth Observation, intelligent sensing, and autonomous or decision-support systems.

Esperienza

Industrial PhD Researcher – AI, Computer Vision & Human-Centred Systems at University of Cassino and Southern Lazio, Italy (2023-01 – 2026-06)

  • Designed Poseidon, a multi-frame Vision Transformer with adaptive temporal weighting and multi-scale feature fusion for robust pose estimation from video.
  • Built end-to-end pipelines covering data acquisition, dataset construction, PyTorch training, ablation studies, quantitative evaluation, explainability, uncertainty estimation, and validation on real cohorts.
  • Developed uncertainty-aware mapping from 3D keypoints to anatomical landmarks, adding frame-level confidence and automated quality control to markerless perception pipelines.
  • Published and presented results while coordinating work across computer vision, engineering, biomechanics, and clinical domains.

AI Engineer – Geospatial Computer Vision & Predictive Analytics at MapSat S.r.l. and Clepsydra (2025-01 – 2026-06)

  • Developed a transformer-based YOLO workflow for asbestos-roof detection on high-resolution orthophotos, including data preparation, model evaluation, and large-scale inference; the research was published at ICIAP.
  • Built predictive components for an environmental monitoring platform producing automated daily forecasts and scheduled retraining across European stations.
  • Translated operational requirements from domain experts into repeatable software and ML workflows with version control and data-quality checks.

Visiting Researcher – AI-Based Movement and Biomechanics at LUNEX University, Luxembourg (2024-01 – 2024-12)

Six-month research visit

  • Integrated pose and motion estimation with OpenSim musculoskeletal models, connecting learned visual representations to physics- and anatomy-based models.

Software & Mobile Developer at Unicas2Go and Freelance Projects (2021-01 – 2026-06)

Full-stack services, mobile applications, and custom software

  • Delivered systems from stakeholder requirements and architecture through implementation, testing, deployment, and maintenance, including an iOS/Android university carpooling service.

Formazione

Industrial PhD in Methods, Models & Technologies for Engineering – University of Cassino and Southern Lazio (2023-01 – 2026-06)

MSc in Computer Engineering – University of Cassino and Southern Lazio (2021-01 – 2023-12)

BSc in Computer and Telecommunications Engineering – University of Cassino and Southern Lazio (2017-01 – 2020-12)

Competenze

AI Research EngineerComputer Vision & Intelligent Systems

Recensioni