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🌟 We had a fantastic time participating in the European Conference on Computer Vision (ECCV24), one of the top conferences in computer vision! It was a pleasure attending the event and catching up with old and new colleagues. 🤝
We’re also excited to announce that two of our papers were accepted:
📄 Boost Your NeRF: Project page Francesco Di Sario Riccardo Renzulli Enzo Tartaglione Marco Grangetto
📄 AA-SGAN: Project page Mirko Zaffaroni Federico Signoretta
Excited for what’s next! 🚀
EIDOS is very proud to announce that Andrea Bragagnolo, who got his PhD in our group, received the award for “Best Italian PhD Thesis 2023” assigned by con.Scienze. The title of his thesis is “Exploring the Design and Implementation of Pruning Techniques for Deep Neural Networks”.
Congratulations Andrea!
Congratulations to Ayesha Hoor Chaudhry for successfully defending her PhD thesis, titled “Medical Volumetric Image Processing With Deep Neural Networks”.
The committee was composed by:
- Prof. Davide CAVAGNINO – Computer Science Dept. - University of Turin;
- Prof. Sinem ASLAN – Dept. of Environmental Sciences, Informatics and Statistics – Ca’ Foscari University of Venice;
- Prof. Maurizio MARTINA – Dept. of Electronics and Telecommunications – Polytechnic of Turin;
PhD Supervisor: Marco Grangetto (University of Turin)
EIDOS is very proud to contribute to ISBI 2024 with paper:
- AI-Assisted Diagnosis for Covid-19 CXR Screening: From Data Collection to Clinical Validation by Carlo Alberto Barbano (University of Turin, Télécom Paris), Riccardo Renzulli (University of Turin), Marco Grosso (ASL Torino 3), Domenico Basile (ASL Torino 3), Marco Busso (ASL Torino 3), Marco Grangetto (University of Torino)
Congratulations to Carlo Barbano for presenting his work.
Marco Grangetto special guest on the RBL channel EULERO show, talking about Computer Vision and prejudice.
EIDOS is very proud to contribute to DCC 2024:
- Domain Adaptation for Learned Image Compression with Supervised Adapters by Presta, Alberto; Spadaro, Gabriele; Tartaglione, Enzo; Fiandrotti, Attilio; Grangetto, Marco;
Congratulations to Alberto Presta for presenting his work with an amazing oral talk.
The Data Compression Conference (DCC) is an international forum for current work on data compression and related applications.
Congratulations to Carlo Alberto Barbano for successfully defending his PhD thesis, titled “Collateral-Free Learning of Deep Representations: From Natural Images to Biomedical Applications”. The committee awarded his defense with honors.
The committee was composed by:
- Prof. Daniel RUECKERT – Dept. Computing - Imperial College London;
- Prof. Hervé LOMBAERT - ETS Montreal;
- Prof. Rosa MEO – Dip. Informatica – Università di Torino;
- Prof. Enrico MAGLI – Dip. Elettronica e Telecomunicazioni – Politecnico di Torino;
- Prof. Isabelle BLOCH - Télécom Paris – Institut Polytechnique de Paris;
- Prof. Marco GRANGETTO - Dip. Informatica – Università di Torino;
- Prof. Pietro GORI - Télécom Paris – Institut Polytechnique de Paris …
PhD Supervisor: Marco Grangetto (University of Turin), Pietro GORI (Télécom Paris – Institut Polytechnique de Paris), Isabelle BLOCH (Télécom Paris – Institut Polytechnique de Paris)
Congratulations to Riccardo Renzulli for successfully defending his PhD thesis, titled “Hierarchical Object-centric Learning with Capsule Networks”. The committee awarded his defense with honors.
The committee was composed by:
- Prof. Peter Sincak, TU Kosice
- Prof. Georgios Leontidis, University of Aberdeen
- Prof. Lia Morra, Polytechnic University of Turin
- Prof. Attilio Fiandrotti, University of Turin
PhD Supervisor: Marco Grangetto (University of Turin)
One postdoc/postgrad position is available at the University of Turin on the topic AI for cardiovascular imaging. The initial appointment is for 12 months with the possibility of renewal.
The relevance of Machine Learning (ML) in cardiology has grown over the years. While the field applied to risk prediction on tabular variables has been extensively explored, it remains highly relevant to delve into the field of cardiovascular imaging evaluation.
In particular, this grant will be aimed at the following objectives:
- Develop image analysis in biomedical field (non-invasive images such as echocardiograms, or invasive images like intracoronary or intravascular imaging).
- Implement clinical event prediction from these types of images using machine learning.
- Implement a comparison between invasive and non-invasive methods using machine learning.
The research activities will be carried out within an interdisciplinary team including Cardiologists and EIDOS group.
For inquiries or further information, please contact prof. Marco Grangetto, prof. Fabrizio D’Ascenzo
The selection process will open in November.
We are inviting applications for a postgrad/postdoc position in the field of AI for surgery, with a specific focus on the following areas:
- Minimally Invasive Surgery: Endoscopy, Laparoscopic Surgery, and Robotics
- Prostate, Renal, and Adrenal Neoplasms
This position offers an exciting opportunity for young researchers interested in advancing the application of artificial intelligence in surgical procedures. The successful candidate will have the chance to work on cutting-edge projects and contribute to the development of AI-driven solutions in the context of minimally invasive surgery and the treatment of prostate, renal, and adrenal neoplasms.
Key Responsibilities:
- Conduct research in the field of AI and its applications in surgery. Collaborate with surgeons and medical professionals to develop AI-based tools and technologies.
- Analyze medical data, including imaging and diagnostic information.
- Contribute to the development of AI algorithms and models for surgical planning and decision support.
- Publish research findings in reputable scientific journals and conferences.
For inquiries or further information, please contact prof. Marco Grangetto, prof. Cristian Fiori.
The selection process will open in December.