Salvatore Esposito
Researcher & Engineer
University of Edinburgh
Researcher & Engineer specializing in autonomous robotic navigation systems, 3D reconstruction and generative AI. I've contributed to Microsoft's HoloLens and Teams Avatars initiatives, translating complex technical concepts into user-centered AR/VR experiences. My strength lies in bridging research innovation with practical applications, effectively collaborating across engineering, design, and business teams. I combine academic rigor with hands-on development to align technical possibilities with product vision, while fostering collaborative environments that accelerate R&D and drive strategic growth.
Interests
- Robotics and Navigation
- Systems Integration & Roadmapping
- Generative AI & Computer Graphics
- Data Engineering & Feature Pipelines
Education
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PhD candidate in Geometric Deep Learning (Biomedical AI CDT) University of Edinburgh
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MRes in Artificial Intelligence University of Edinburgh
Professional Experience
Postdoctoral Research Fellow
University of Edinburgh
2025 – Present
Edinburgh
Postdoctoral Research Fellow in Autonomous Robotics Surgery
- Developing novel navigation algorithms for robotic systems for minimally invasive procedures to enhance surgical precision and safety
- Leading interdisciplinary research team in creating AI-powered navigation solutions for autonomous surgical interventions
Research & Development
Microsoft
2022 – 2024
Zurich & Cambridge
Visiting Researcher, Zurich (2022–2024)
- Led the enhancement of the HMR 2.0 multimodal transformer pipeline for avatars
- Improved motion & audio prediction for more realistic avatar interactions
Research Intern, Cambridge (2022)
- Built GAN- and NeRF-based generative models with enhanced surface fidelity
- Proposed a neural rendering architecture for high-quality facial mesh extraction
Research Intern
Huawei
2023
Edinburgh
Systems Infrastructure Research
- Time-series forecasting for CPU utilization in virtual machines
- Designed predictive resource-management solutions
Research Intern, Cambridge (2022)
- Integrated NeRFs with caching for improved rendering quality
Quantitative Researcher
American Express
2022
London
Quantitative Analysis
- Applied ML/AI & statistical methods for financial modelling
- Optimized HPC & cloud pipelines for large-scale data analysis
Publications
Awards
CDT Doctoral Scholarship in Biomedical AI
UKRI
2020