Sayak Paul

Details: https://discuss.tensorflow.org/t/announcing-the-keras-community-prize-first-edition/13148/29

Details: https://www.kaggle.com/discussions/general/370095

Details: https://www.kaggle.com/discussions/general/358450

In the same way that a Google Peer Bonus is used to recognize a fellow Googler who has gone above and beyond, an Open Source Peer Bonus recognizes external people who have made exceptional contributions to open source. Googlers can nominate contributors who they feel deserve our recognition (and some cash)!

Here's the announcement blog post: https://opensource.googleblog.com/2022/09/announcing-the-second-group-of-open-source-peer-bonus-winners-in-2022.html.

Course website: https://www.oxfordml.school/.

I was accepted to participate in the school amongst over 5000 applicants.

Certificate link: https://drive.google.com/file/d/14DKioe8HRjKkXEeRXAhmclqUP8cvv9Z0/view?usp=sharing

For contributions to benchmarks, evaluation, methods, and for adding code to papers.

Papers With Code: https://paperswithcode.com/
Award: https://github.com/sayakpaul/portfolio/raw/master/images/pwc_award.jpg

Know more about the Google OSS Expert Prize: https://www.kaggle.com/google-oss-expert-prize.

Aritra and I got this prize because of our work on investigating the representations learned by different families of Vision Transformers: https://www.kaggle.com/code/aritrag/probing-vits.

Here's the announcement post from Kaggle: https://www.kaggle.com/discussions/general/328914.

Know more about the Google OSS Expert Prize: https://www.kaggle.com/google-oss-expert-prize.

I got this prize because of my work on implementing and explaining DeiTs: https://www.kaggle.com/code/spsayakpaul/distilling-vision-transformers.

Here's the announcement post from Kaggle: https://www.kaggle.com/discussions/general/322041.

Know more about the Google OSS Expert Prize: https://www.kaggle.com/google-oss-expert-prize.

Aritra and I got this prize because of our work on implementing and explaining Masked Autoencoders: https://www.kaggle.com/code/spsayakpaul/mae-keras.

Here's the announcement post from Kaggle: https://www.kaggle.com/discussions/general/316181.

Know more about the Google OSS Expert Prize: https://www.kaggle.com/google-oss-expert-prize.

Soumik and I got this prize because of our work on explaining and demoing GauGAN: https://www.kaggle.com/soumikrakshit/gaugan-keras/.

Here's the announcement post from Kaggle: https://www.kaggle.com/general/310354.

Received multiple #TFCommunitySpotlight awards for collaborative and interesting projects. Details:

* https://twitter.com/TensorFlow/status/1351590466068783105
* https://twitter.com/TensorFlow/status/1428433434972618754
* https://twitter.com/TensorFlow/status/1446611368078086144
* https://twitter.com/TensorFlow/status/1460321709488152579
* https://twitter.com/TensorFlow/status/1469019016782041095
* https://twitter.com/TensorFlow/status/1516869315517198337
*… Show more

Received multiple #TFCommunitySpotlight awards for collaborative and interesting projects. Details:

* https://twitter.com/TensorFlow/status/1351590466068783105
* https://twitter.com/TensorFlow/status/1428433434972618754
* https://twitter.com/TensorFlow/status/1446611368078086144
* https://twitter.com/TensorFlow/status/1460321709488152579
* https://twitter.com/TensorFlow/status/1469019016782041095
* https://twitter.com/TensorFlow/status/1516869315517198337
* https://twitter.com/TensorFlow/status/1521558632768409600
* https://twitter.com/TensorFlow/status/1540033393462738944
* https://twitter.com/TensorFlow/status/1545115276152389636
* https://twitter.com/TensorFlow/status/1611469033714470919
* https://twitter.com/TensorFlow/status/1626629821022208020 Show less

Received NeurIPS 2021 AI4Science Workshop Travel Grant [1] for this work [2].

[1] https://ai4sciencecommunity.github.io/
[2] https://openreview.net/forum?id=kXgbFvXcwDX

Blog post: https://blog.tensorflow.org/2021/11/2021-TF-Contributor-Awardees.html.

My Google Cloud Innovator page: https://cloud.google.com/innovators/champions?text=Sayak.

The flood event detection contest, organized by the NASA Interagency Implementation and Advanced Concepts Team in collaboration with the IEEE GRSS Earth Science Informatics Technical Committee, seeks to develop approaches to delineate open water flood areas as an effort to identify flood extent, an impactful disaster that occurs frequently throughout the world. The competition involves a supervised learning task—participants will develop algorithms to identify flood pixels after training their… Show more

The flood event detection contest, organized by the NASA Interagency Implementation and Advanced Concepts Team in collaboration with the IEEE GRSS Earth Science Informatics Technical Committee, seeks to develop approaches to delineate open water flood areas as an effort to identify flood extent, an impactful disaster that occurs frequently throughout the world. The competition involves a supervised learning task—participants will develop algorithms to identify flood pixels after training their algorithm against a training set of synthetic aperture radar (SAR) images. Participants are required to submit binary classification maps, and performance will be evaluated using the intersection over union (IOU) score. Competition pape: https://nasa-impact.github.io/etci2021/.

Our solution (with Siddha Ganju): https://git.io/JW3P8.
Certificate: https://bit.ly/etci-2021-sayak. Show less

My report [1] secured the eighth rank at Appliedroots Blogathon 2021. Link: https://www.appliedroots.com/blogathon.

[1] An Introduction to Adversarial Examples in Deep Learning: https://bit.ly/3b2zss2

In the same way that a Google Peer Bonus is used to recognize a fellow Googler who has gone above and beyond, an Open Source Peer Bonus recognizes external people who have made exceptional contributions to open source. Googlers can nominate contributors who they feel deserve our recognition (and some cash)!

Here's the announcement blog post: https://opensource.googleblog.com/2021/09/announcing-latest-open-source-peer-bonus-winners.html.

Camera scene detection task is one of the most popular problems related to mobile photography. While nowadays almost every smartphone has a built-in automatic mode for this task, there are still no free open-source datasets and models that can solve this problem accurately and fast. To address this problem, we propose a novel dataset consisting of 30 most important camera scene classes and organize a camera scene detection challenge. In this competition, the target is to obtain high precision… Show more

Camera scene detection task is one of the most popular problems related to mobile photography. While nowadays almost every smartphone has a built-in automatic mode for this task, there are still no free open-source datasets and models that can solve this problem accurately and fast. To address this problem, we propose a novel dataset consisting of 30 most important camera scene classes and organize a camera scene detection challenge. In this competition, the target is to obtain high precision results as measured by Top-1 / Top-3 accuracy, and at the same time the model should be very efficient as measured by inference time on the mobile platform.

The top ranked participants will be awarded and invited to follow the CVPR submission guide for workshops to describe their solution and to submit to the associated MAI workshop at CVPR 2021. Competition homepage: https://competitions.codalab.org/competitions/28113.

Our solution approach is detailed here: https://arxiv.org/abs/2105.08819. Show less

In the same way that a Google Peer Bonus is used to recognize a fellow Googler who has gone above and beyond, an Open Source Peer Bonus recognizes external people who have made exceptional contributions to open source. Googlers can nominate contributors who they feel deserve our recognition (and some cash)!

Here's the announcement blog post - https://opensource.googleblog.com/2020/10/announcing-latest-google-open-source.html.

Got recognized as a Top Innovator for 2019 by the Intel Software Innovator Program for my community contributions and innovative projects.

Certificate link: https://www.dropbox.com/s/mzsy1q8jgkwj6cj/Intel_Top_Innovator_2019.jpg?dl=0

Star moderator award for my contribution to the AI community of the Campus Commune (second one).

Got this award for proposing novel solution ideas to the problems faced by different internal business units of TCS at different levels.

For being an active moderator on Campus Commune's Artificial Intelligence for Q4.

For showing proactiveness in learning and enhancing knowledge.

For paper acceptance.