Grzegorz Wilczyński

Senior Research Engineer @ IDEAS Research Institute
PhD Student @ Jagiellonian University

I bridge the gap between generative AI and 3D computer vision. Currently focusing on neural rendering, Gaussian Splatting, and structurally coherent 3D reconstruction from disjoint views. With 6+ years of industry experience, I build systems that are theoretically sound and production-ready.

Featured Research

IRIS: Implicit Reconstruction in Space

Under review ECCV 2026

A novel approach to implicit 3D scene representation, focusing on high-fidelity rendering and robust geometric priors for complex environments.

QuantumGS visualization

QuantumGS: Quantum Encoding for 3DGS

Accepted to PPSN 2026 (CORE A)

An innovative framework leveraging quantum encoding techniques to optimize the parameters and memory footprint of Gaussian Splatting representations.

MindTheGap visualization

MindTheGap: Disjoint Views Reconstruction

Submitted to NeurIPS 2026

Bridging the spatial divide in 3D reconstruction by introducing generalized priors to synthesize novel views from strictly non-overlapping images.

MeshSplats visualization

MeshSplats: Hybrid Surface Rendering

Accepted to ICCS 2026

Combining the explicit geometric accuracy of traditional meshing with the photo-realistic, real-time rendering capabilities of Gaussian Splatting.

Other Publications

HuSc3D: Human and Scene 3D Co-reconstruction

Accepted to ICCS 2026

Simultaneous reconstruction of dynamic human subjects and static scenes from monocular video, maintaining robust spatial coherence.

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REdiSplat: Real-time Editing of Gaussian Splats

A lightweight framework for semantic manipulation and geometry editing of pre-trained 3D Gaussian Splatting models.

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Performance Comparison of Edge Computing Devices

Accepted to JCSE 2023

A comprehensive evaluation and benchmarking of various edge devices, focusing on their efficiency and suitability for deploying machine learning models.

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Experience & Fellowships

Senior Research Engineer

IDEAS Research Institute | Present

Focusing purely on core AI research, generative models, and advancing the state-of-the-art in 3D Computer Vision.

Visiting Researcher

University of Cambridge | Cyber-Human Lab

One-month intensive research visit focused on human-computer interaction, spatial computing, and applied 3D rendering systems.

Machine Learning Engineer

BulletProve & BFirst.Tech | 6 Years

Deployed production-grade systems in object detection, keyword spotting, and recommendation engines.

PyTorch CUDA Python