Kshitij Dwivedi

I am an Applied Scientist at Amazon Robotics, Berlin.

Previously, I was a PhD student at CVAI lab in Goethe University Frankfurt, where I was advised by Prof. Gemma Roig and collaborated with Prof. Radek Cichy's lab.

Before starting my PhD I've worked as an Engineer at Kamitani lab in ATR, Japan and Samsung R&D India. I did my Bachelors and Masters in Electrical Engineering at IIT Kanpur.

Email / Resume / Publications / Google Scholar / LinkedIn

Research Interests

I am interested in transfer learning and interpretability of neural networks. During my Phd I focused on understanding how computer vision models and human visual cortex represent visual information. Below you can find my publications related to Computer Vision and Human Vision highlighted in respective colors.

Publications

	What do navigation agents learn about their environment? Kshitij Dwivedi, Gemma Roig, Aniruddh Kembhavi, Roozbeh Mottaghi CVPR, 2022 Project Page / arxiv / Code A new method to find what is encoded in hidden units of navigation agents
	Net2Brain: A Toolbox to compare artificial vision models with human brain responses Domenic Bersch, Kshitij Dwivedi, Martina Vilas, Radoslaw Martin Cichy, Gemma Roig CCN, 2022 arxiv / Code A new toolbox to facilitate easier comparison of DNN features with brain responses.
	A large and rich EEG dataset for modeling human visual object recognition Alessandro Gifford, Kshitij Dwivedi, Gemma Roig, Radoslaw Martin Cichy NeuroImage, 2022 Data / bioRxiv / Code A new large-scale dataset of EEG recordings of human viewing natural images.
	The spatiotemporal neural dynamics of object location representations in the human brain Monika Graumann, Caterina Ciuffi, Kshitij Dwivedi, Gemma Roig, Radoslaw Martin Cichy Nature Human Behavior, 2022 Here, we investigated where, how and when representations of object location and category emerge in the human brain.
	Unveiling functions of the visual cortex using task-specific deep neural networks Kshitij Dwivedi, Michael F. Bonner, Radoslaw Martin Cichy, Gemma Roig PLOS Computational Biology, 2021 * jointly directed work Project Page / preprint / Code / CCN 2019 We investigated the potential of deep neural networks trained on a diverse set of tasks in finding functional roles of different regions of the human visual cortex
	The Algonauts Project 2021 Challenge: How the Human Brain Makes Sense of a World in Motion Radoslaw Martin Cichy, Kshitij Dwivedi, Benjamin Lahner, Alex Lascelles, Polina Iamshchinina, Monika Graumann, Alex Andonian, N Apurva Ratan Murty, Kendrick Kay, Gemma Roig, Aude Oliva arxiv, 2021 Project Page / arxiv / Code We present Algonauts 2021 challenge where the goal is to determine which computational model best explains human brain responses while humans view everyday events
	Duality Diagram Similarity: a generic framework for initialization selection in task transfer learning Kshitij Dwivedi, Jiahui Huang, Radoslaw Martin Cichy, Gemma Roig ECCV, 2020 pdf / code Highly efficient and accurate approach for initialization selection in task transfer learning.
	Unravelling Representations in Scene-selective Brain Regions Using Scene Parsing Deep Neural Networks Kshitij Dwivedi, Radoslaw Martin Cichy, Gemma Roig Journal of Cognitive Neuroscience, 2020 *jointly directed work Early Access / bioRxiv / ECCV workshop 2018 We show that a scene parsing model explains human scene-selective responses better than a scene classification model. Further, components predicted by scene parsing models can be used to distinguish functional roles of human scene-selective areas PPA and OPA.
	Representation Similarity Analysis for Efficient Task taxonomy & Transfer Learning Kshitij Dwivedi, Gemma Roig CVPR, 2019 pdf / code Efficient method to estimate task similarities and its application to transfer learning
	End-to-End Deep Image Reconstruction From Human Brain Activity Guohua Shen, Kshitij Dwivedi, Kei Majima , Tomoyasu Horikawa, Yukiyasu Kamitani Frontiers in Computational Neuroscience, 2019 *equal contribution code Reconstructing perceived images from human fMRI responses.
	The Algonauts Project: A Platform for Communication between the Sciences of Biological and Artificial Intelligence Radoslaw Martin Cichy, Gemma Roig, Alex Andonian, Kshitij Dwivedi, Benjamin Lahner, Alex Lascelles, Yalda Mohsenzadeh, Kandan Ramakrishnan, Aude Oliva Conference on Cognitive Computational Neuroscience (CCN) , 2019 Workshop We organized a challenge and workshop to predict human fMRI and MEG responses using computational models.

Conference abstracts and Workshop Papers

Unveiling functions of visual cortex using task-specific deep neural networks
Kshitij Dwivedi, Michael F. Bonner, Radoslaw Martin Cichy, Gemma Roig
Neuromatch 2.0 , 2020 (Short talk)
slides

Deep Anchored Convolutional Neural Networks
Jiahui Huang, Kshitij Dwivedi, Gemma Roig
Computer Vision and Pattern Recognition Workshop (CVPRW) on Compact and Efficient Feature Representation and Learning (CEFRL), 2019 (Oral Presentation)
pdf

Neural network compression using convolutional parameters sharing.

Explaining Scene-selective Visual Area Using Task-specific and Category Specific DNN Units
Kshitij Dwivedi, Michael F. Bonner, Gemma Roig
Vision Sciences Society Conference, 2019
Abstract

Navigational Affordance Cortical Responses Explained by Semantic Segmentation model
Kshitij Dwivedi, Gemma Roig
European Conference on Computer Vision Workshops (ECCVW) on Brain-Driven Computer Vision (BDCV), 2018
pdf

Relating functions of visual cortex to deep neural network functions.

Plug and Play DNN Modules for Multi-domain Learning
Kshitij Dwivedi, Gemma Roig
European Conference on Computer Vision Workshops (ECCVW) on Interactive and Adaptive Learning in an Open World (IAL), 2018
pdf

Efficient multi-domain learning using parameter sharing.

Importance of object selection in Relational Reasoning tasks
Kshitij Dwivedi, Gemma Roig
Neural Information Processing Systems Workshops on Relation Representation Learning (R2L), 2018
pdf

Teaching

	TA, Computer Vision 2020-21, Goethe University Frankfurt am Main
	TA, Multivariate EEG online school 2020
	Lead TA, Neuromatch Academy 2020
	TA, Data Structure and Algorithms 2014, IIT Kanpur

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