Pradeep Shenoy

Pradeep Shenoy

Pradeep Shenoy leads the Cognitive modeling & Machine Learning team at Google Research India, which aims to build expressive, robust ML systems, drawing functional and algorithmic inspiration from human cognition. Pradeep also works on modeling human behavior & cognition, with applications in personalization and human-AI interfaces. Recent work has focused on robust learning via instance reweighting, and its application to a range of problem settings in applied ML. Pradeep has a Ph.D. in Computer Science from the University of Washington & post-doctoral research experience at UC San Diego, where he worked in neuroengineering, computational neuroscience & cognitive science. He has previously led machine learning teams at Microsoft, developing and supporting large-scale production models that predict user behavior (clicks, conversions, audience segmentation, etc.) in sponsored search. Pradeep has also worked in various capacities at Microsoft Research, Fraunhofer Institute, and Lucent Bell Laboratories.
Authored Publications
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    Using Early Readouts to Mediate Featural Bias in Distillation
    Rishabh Tiwari
    Durga Sivasubramanian
    Anmol Mekala
    Ganesh Ramakrishnan
    WACV 2024 (2024)
    Edges to Shapes to Concepts: Adversarial Augmentation for Robust Vision
    Aditay Tripathi
    Rishubh Singh
    Anirban Chakraborty
    Computer Vision and Pattern Recognition (CVPR) 2023 (2023) (to appear)
    Interactive Concept Bottleneck Models
    Rishabh Tiwari
    Jan Freyberg
    Dj Dvijotham
    AAAI (2023)
    Adaptive mixing of auxiliary losses in supervised learning
    Durga Sivasubramanian
    Ayush Maheshwari
    Prathosh AP
    Ganesh Ramakrishnan
    AAAI 2023 (2023) (to appear)
    Overcoming simplicity bias in deep networks using a feature sieve
    Rishabh Tiwari
    International Conference on Machine Learning (ICML) (2023) (to appear)