External Research Collaborator @ Meta
Nonstop Consulting, Zurich, Switzerland (Remote)
- Part-time role to continue my work alongside the Monaco rendering team at Meta, working on real-time physically based rendering.
I am a PhD Student on Computer Graphics at IDSIA-USI (Lugano, Switzerland) under the supervision of Piotr Didyk. My research focuses on leveraging inverse graphics to improve applications in vision, real-time rendering and fabrication. During my PhD I had the opportunity to intern at Meta Reality Labs and work alongside the talented Monaco Rendering Team, working on accelerating physically-based volume rendering for photorealistic avatars, under the supervision of Christophe Hery and Adrián Jarabo. I'm also an avid photographer and I love trekking in my spare time.
ArXiv [May'24]
Banking on the popularity of rasterized 3D Gaussian Splatting methods, we formalize the ray-tracing of volumes composed of kernel mixture models (Gaussian or otherwise). Our physically-based, path-traced formulation allows us to render and optimize both scattering and emissive volumes, as well as radiance fields, in an extremely efficient and compact manner. We also introduce the Epanechnikov kernel as an efficient alternative for the Gaussian kernel in radiance field rendering, and showcase the advantages of a ray-traced framework, while maintaining real-time performance.
Proceedings of SIGGRAPH [SIGG'23]
We measure, model and correct perceived color shifts in 3D printed objects with different levels of gloss. To formulate the correction we conduct novel perceptual experiments and propose an optimization procedure solved using differentiable rendering.
Eurographics Symposium on Rendering [EGSR'22]
An efficient method for rendering complex luminaires using a high quality octree-based representation of the luminaire emission modelled through Neural Radiance Fields, achieving up to x100 speedups over explicit modelling
Computer Graphics Forum, presented at Eurographics 2022 [CGF'21]
An image-based editing method that allows to modify the material appearance of an object by increasing or decreasing high-level perceptual attributes, using a single image as input.
Jornada Jóvenes Investigadores I3A 2021, Poster Session [JJI-I3A'21]
We apply recent advancements in generative neural networks and an untapped dataset to the problem of volume estimation from a single RGB input and train a model that performs the task efficiently, ready to deploy in other vision and computer graphics pipelines
Development of assignments and exams, grading, onsite teaching of exercise lectures, student tutoring on BSc and MSc courses on digital image and video processing and computer graphics
USI Lugano, Switzerland
USI Lugano, Switzerland
Reinforcement Learning for Importance Sampling of Neural Radiance Fields
Perceptually-Driven Neural Inpainting for Seamless 3D Reconstructions
Development of an IoT device based on LoRA and ESP32 for plant health monitoring and control with highschool students as part of their Maturity Projects (Lavoro di Maturità or LaM).
PhD Candidate on Computer Graphics under the supervision of Prof. Piotr Didyk. My research focuses on leveraging inverse graphics to improve applications in vision, graphics and fabrication.
Highly competitive Master with a strong research focus. Took courses on Deep Learning, Computer Graphics, VR, Computer Vision, SLAM and Robotics. Obtained Honors in Modelling and Simulation of Appearance (Computer Graphics course), where I developed a path tracer based on Nori (educational Mitsuba) and implemented many features including a full volumetric path tracer for both homogeneous and heterogeneous media and fur rendering. Got Honorable Mention (second prize) in the Rendering Contest judged by Marcos Fajardo, Matt Chiang, and Wojciech Jarosz (check my submission here )
University is Ranked #1 in Spain in Computer Graphics, Robotics and Computer Vision (edurank)
Took Master-level courses in the fields of AI, electronics design and robotics, working in a highly cooperative and diverse environment
Top 7% of my promotion. Special interest in digital and analog electronics, robotics and machine learning. Class delegate for several years. Obtained Honors in Digital Electronics, Thermodynamics, Chemistry and Fundamentals of Electronics