We award the best paper with the SAIAD Best Paper Award!

Call for Papers

We are soliciting high quality papers covering the topics listed below. Papers should follow the standard CVPR formatting instructions and paper length (author guidelines). Accepted papers will appear in the CVPR workshop proceedings!

• Submission Deadline: March 2, 2026

• Author Notification: March 20, 2026

• Camera ready due: April 2, 2026

• Submission via OpenReview*:  https://openreview.net/group?id=thecvf.com/CVPR/2026/Workshop/SAIAD

* Note: Authors creating a new OpenReview profile should be aware that accounts created without an institutional email address are subject to a moderation process that may take up to two weeks. Profiles created with an institutional email address are typically activated automatically.

Topics of Interest

The topics of interest include (but are not limited to):

• Interpretable and explainable Deep Neural Networks

• Standardization in Safe AI

• Ethics and legal aspects in Safe AI

• Safe Deep Neural Network design

• Certification of DNNs

• Detection of out-of-distribution data

• Robustness to anomalies / out-of-distribution data / adversarial examples

• Uncertainty modeling

• Transparent DNN training

• Integrating legal requirements

• Novel evaluation schemes

We follow a high quality review process with a notable Program Committee.

• Aayan Yadav, Indian Institute of Technology, Roorkee

• Abhishek Vivekanandan, Karlsruher Institut für Technologie

• Andreas Bär, Technische Universität Braunschweig

• Avisek Naug, Hewlett Packard Enterprise

• Chih-Hong Cheng, Chalmers University of Technology

• Claus Bahlmann, Siemens Corporate Research

• Cristiano Patrício, Universidade da Beira Interior

• Hakan Yekta Yatbaz, The Queen's University Belfast

• Hanno Gottschalk, Technische Universität Berlin

• Javier Muñoz-Haro, Universidad Autónoma de Madrid

• Jeethesh Pai Umesh, Hensoldt AG

• Jinliang Li, Tsinghua University

• Jing Li, Tsinghua University

• Joakim Johnander, Linköping University

• Jonas Uhrig, Mercedes Benz AG

• Julian Fierrez, Universidad Autónoma de Madrid

• Karl Amende, Valeo

• Karsten Roscher, Fraunhofer IKS

• Kento Oonishi, Mitsubishi Electric Corporation

• Ketan V Kotecha, Symbiosis International University

• kishor datta gupta, Clark Atlanta University

• Konrad Groh, Bosch

• Konstantin Kirchheim, Otto-von-Guericke University

• Lakshit Arora, Google

• Lena Heidemann, Technische Universität München

• Mahmoud Salem, Karlsruher Institut für Technologie (KIT)

• Marion Neumeier, Technische Universität München

• Markus Enzweiler, Esslingen University of Applied Sciences

• Martin Meinke, Bosch

• Martin Rabe, Technische Universität Ilmenau

• Mert Keser, Technische Universität München

• Michael Mock, Fraunhofer Institute IAIS, Fraunhofer IAIS

• Michael Paulitsch, Intel

• Muneeb A. Khan, Ulsan National Institute of Science and Technology

• Nael Fasfous, BMW AG

• Neslihan Kose, Intel Deutschland GmbH

• Nicola Franco, AI4I

• Nikolas Ebert, Technische Hochschule Mannheim

• Nilaksh, Mila - Quebec Artificial Intelligence Institute

• Oliver Wasenmüller, Technische Hochschule Mannheim

• Pallavi Mitra, Berliner Hochschule für Technik

• Paul Melki, EXXACT Robotics

• Qutub Sha Syed, Technische Universität München

• Rajesh Vayyala

• René Schuster, German Research Center for AI (DFKI)

• Sebastian Dorn, Technical University of Applied Sciences Augsburg

• Shree Singhi, Indian Institute of Technology, Roorkee

• Svetlana Pavlitska, FZI Research Center for Information Technology

• Thomas Stauner, BMW Deutschland

• Tim Fingscheidt, Technische Universität Braunschweig

• Wojciech Samek, Technische Universität Berlin

• Youssef Shoeb, Technische Universität Berlin

• Zigan Wang, Tsinghua University

• Ziliang Xiong, Linköping University