🎓 AI & Robotics Master's Student at Sapienza University
💻 Generative AI Engineer at Storm Reply
🚀 Passionate about Generative AI, Computer Vision, Neural Network Calibration & Robotics

• Super-Resolution & Neural Rendering: Enhancing image/video quality using generative AI techniques.
• Diffusion Models & AI-Generated Content: Exploring applications in visual media, animation, and special effects.
• Neural Network Calibration & Uncertainty Estimation: Developing novel techniques to improve model reliability in AI applications.
• Autonomous Systems & Reinforcement Learning: Applying ML to real-time decision-making in robotics & simulation.

• Description:Applied Quave as a preprocessing step for super-resolution, with StableSR as the baseline.
• Results: Achieved PSNR improvement of +15% over traditional upscaling methods.
• Paper: Under Review at IJCNN 2025 (preprint available upon request).

• Description: Developed a novel radius-based regularization technique to improve neural network calibration in both hyperbolic & Euclidean spaces.
• Results: Achieved 50% reduction in Expected Calibration Error (ECE)
• Paper: Under Review (preprint available upon request).

• Python | R | C++ | C | Assembly

• PyTorch | TensorFlow | ROS2 | OpenCV
• AWS | Jira | Git | Google Cloud

• Generative AI & Diffusion Models
• Neural Network Calibration & Confidence Estimation
• Super-Resolution & AI-Enhanced Image Processing
• Autonomous Robotics & Reinforcement Learning

• Contribute to AI-driven animation, visual effects, and simulation research.
• Develop AI-based tools for film production, motion synthesis, and virtual characters.
• Pursue a PhD in AI & Robotics, focusing on generative models for media applications.

• LinkedIn: linkedin.com/in/christianbianchiit
• Portfolio: fascetta.github.io

Let's collaborate and bring innovative AI solutions to life!