I am currently a Postdoctoral Associate with the Center for Machine Learning (CML) in the University of Maryland Institute for Advanced Computer Studies (UMIACS). I work under the supervision of Tom Goldstein.
I received my PhD in Computer Science at University of Maryland, Baltimore County. I was advised by Hamed Pirsiavash. In my dissertation, I studied ways in which state-of-the-art deep learning methods for computer vision are vulnerable to backdoor attacks and proposed defense methods to remedy the vulnerabilities.
During my PhD, I have worked as a Machine Learning Research Intern at Bosch Center for AI, an Applied Scientist Intern at Amazon Rekognition, and a Machine Learning Intern at Matroid.
Prior to this, I was a Software Engineer at Samsung Research Institute Bangalore, India where I was part of the DRAM Group of Samsung Semiconductor India Research.
My hobbies include photography, writing, playing football and chess. I support Manchester United FC.
Complete list on Google Scholar.
Backdoor Attacks on Self-Supervised Learning Paper Code
Aniruddha Saha, Ajinkya Tejankar, Soroush Abbasi Koohpayegani, Hamed Pirsiavash
CVPR 2022 Oral
Role of Spatial Context in Adversarial Robustness for Object Detection Paper Slides Video Code
Aniruddha Saha*, Akshayvarun Subramanya*, Koninika Patil, Hamed Pirsiavash
CVPR 2020 Workshop on Adversarial Machine Learning in Computer Vision
Universal Litmus Patterns: Revealing Backdoor Attacks in CNNs Paper Webpage Slides Video Code
Soheil Kolouri*, Aniruddha Saha*, Hamed Pirsiavash, Heiko Hoffmann
CVPR 2020 Oral
An Adaptive Foreground-Background Separation Method for Effective Binarization of Document Images Paper
Bishwadeep Das, Showmik Bhowmik, Aniruddha Saha, Ram Sarkar
Proceedings of the Eighth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016)
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