I am a doctoral researcher at the Photogrammetry and Remote Sensing Lab, ETH Zürich, specializing in 3D Computer Vision, 3D Reconstruction, and Diffusion Models. My journey spans academia, teaching, cutting-edge research, and industry experience, including roles in both established organizations and innovative startups. I am deeply passionate about advancing Deep Learning and Artificial Intelligence while exploring their practical applications in the real world.
Doctoral studies at Photogrammetry and Remote Sensing group at ETHZ, projects revolving around Computer Vision, 3D Vision and Deep Learning. Currently working on a projects in 3D Mesh Simplification and Optimization, and Diffusion Models.
Deployed and improved on state-of-the-art Monocular Depth Estimation models for reconstruction of 3D scenes in Stereo Conversion procedures, enabling simple 2D scenes and movies for 3D technology and VR experience.
Automated the complex and demanding process of brand and product curation and refinement in the context of e-commerce business. Developed the cloud functions in Google Cloud Platform which interacted with Google Firestore and Storage. Designed complex pipelines for data processing and comprehension using Generative AI by exploiting the power of Firebase Genkit plugins and prompt engineering. Developed and maintained the Google Genkit plugins for OpenAI, Groq, AnthropicAI, MistralAI...
Master thesis project done during the stay at Disney Research was published at the prestigious ACM SIGGRsAPH24 conference. The work exploits huge pre-trained text-to-image Diffusion Models for the task of image and video colorization. It achieves high-quality, State-of-the-Art results, along with highly controllable, efficient, and customizable colorization.
Involved in courses Probabilistic Artificial Intelligence and Introduction to Machine Learning. Worked on design of ML and AI student projects, and development of automatic submission and evaluation interface. Implemented creative and challenging coding projects, where students engaged in implementation of newest methods in field of Probabilistic AI. Improved cross-platform automatic evaluation interface using Docker, enhancing user experience and streamlining results submission process
Actively contributed to the research and development of specialized PTZ camera head for video production automation. Focused on the design of automated tracking algorithms for precise control of PTZ and PTU camera heads, ensuring highquality and stable camera operation, in scope of Bachelor thesis. Implemented gyro-stabilization control algorithm using IMU device, enhancing camera head stability across diverse scenarios. Projects spanned from low-level microcontroller programming to high-level deep learning-based tracking algorithms.
GPA: 5.6/6.0
GPA: 9.8/10.0