Shashank Agnihotri

Researcher & PhD Candidate

Chair for Machine Learning,
University of Mannheim Data and Web Science Group,
School of Business Informatics and Mathematics

B6, 26, Room C0.02 68159 Mannheim
Email:  shashank.agnihotrimail-uni-mannheim.de

I'm a Ph.D. candidate at the Chair for Machine Learning supervised by Prof. Dr.-Ing Margret Keuper.

My research interests are:

• Architectural Design Choices for OOD Robustness and Adversarial Robustness of Vision Models
• Pixel-wise prediction tasks
• Neural Architecture Search.

My Resume

• CosPGD: An efficient white-box adversarial attack for pixel-wise prediction tasks – Accepted at ICML 2024
• Improving Feature Stability during Upsampling -- Spectral Artifacts and the Importance of Spatial Context – Accepted at ECCV 2024

• December 2023 – Present : P.h.D. Candidate, Computer Science, University of Mannheim
• June 2022 – December, 2023 : P.h.D. Candidate, Computer Science, University of Siegen
• October 2018 – September 2021 :  MSc. Computer Science, University of Freiburg
• July 2014 – June 2018 : BE Computer Engineering, VESIT, Univeristy of Mumbai
• June 2000 – May 2014 : Smt. Sulochanadevi Singhania School  

• Agnihotri, Shashank, Julia Grabinski, and Margret Keuper. “Improving Feature Stability during Upsampling -- Spectral Artifacts and the Importance of Spatial Context” accepted at the European Conference on Computer Vision (ECCV) 2024.Agnihotri, S., Jung, S. & Keuper, M.. (2024).
• "CosPGD: an efficient white-box adversarial attack for pixel-wise prediction tasks". Proceedings of the 41st International Conference on Machine Learning, in Proceedings of Machine Learning Research 235:416–451 Available from https://proceedings.mlr.press/v235/agnihotri24b.html.
• Sommerhoff, Hendrik, Shashank Agnihotri, Mohamed Saleh, Michael Moeller, Margret Keuper, and Andreas Kolb. “Differentiable Sensor Layouts for End-to-End Learning of Task-Specific Camera Parameters.” accepted at the Internation Conference on Computational Photography (ICCP) 2024.
• Agnihotri, Shashank, Kanchana Vaishnavi Gandikota, Julia Grabinski, Paramanand Chandramouli, and Margret Keuper. “On the unreasonable vulnerability of transformers for image restoration-and an easy fix.” In Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 3707-3717. 2023.
• Hoffmann, Jasper*, Shashank Agnihotri*, Tonmoy Saikia, and Thomas Brox. “Towards improving robustness of compressed CNNs.” In ICML Workshop on Uncertainty and Robustness in Deep Learning (UDL). 2021.