About Me

I work as a Lead ML Scientist at Adobe. I was previously at Alexa AI and Artificial General Intelligence orgs of Amazon as a Senior Applied Scientist. I have a Doctor of Philosophy (PhD) in Computer Science from the University of Southern California, USA, and a Bachelor of Technology (BTech) in Computer Science and Engineering from National Institute of Technology Calicut, India. My research interests are in Deep Learning, Representation Learning, Adversarial Learning, Generative AI, and their applications.

Contact Details

ayush#jaiswal AT adobe DOT com [delete #]
LinkedIn

Work

Adobe

Lead ML Scientist • July 2024 - Current

I currently work as a Lead ML Scientist at Adobe Sensei & Search.

Amazon

Senior Applied Scientist • June 2020 - July 2024

I worked as a Senior Applied Scientist in Alexa AI and Artificial General Intelligence orgs.

USC Information Sciences Institute

Research Assistant • Aug 2017 - May 2019 • Aug 2019 - May 2020

I worked as a Research Assistant to my PhD advisor, Prof. Premkumar Natarajan, at the USC ISI Center for Video Image Speech and Text Analytics (VISTA). I worked on robust and fair representation learning in deep neural networks and on semantic integrity assessment of multimedia data.

Amazon

Applied Scientist Intern • May 2019 - Aug 2019

I worked as an Applied Scientist Intern in the Natural Understanding team of Alexa AI.

NVIDIA

Deep Learning Intern • May 2016 - Aug 2016 • May 2017 - Aug 2017

I worked with the Data Analytics Platform team on various use-cases of machine learning and deep learning to improve their service and monitor their systems, involving anomaly detection and forecasting, as well as image segmentation.

USC Viterbi School of Engineering

Teaching Assistant • Jan 2017 - May 2017

I worked as a Teaching Assistant for USC CSCI 104L (Data Structures and Object Oriented Design). I helped oranize lab sessions, held office hours and graded assignments and tests.

USC Viterbi School of Engineering

Research Assistant • Aug 2014 - Apr 2016 • Aug 2016 - Dec 2016

I worked as a Research Assistant to my then PhD advisor, Prof. Raghavendra, in the Predictive Analytics lab. I worked on projects involving oilfield and healthcare data.

USC Information Sciences Institute

Visiting Research Scholar • May 2013 - Jul 2013

I worked with Prof. Knoblock and his team on the task of predicting the next location of a smartphone user using sparse GPS data. I also worked on designing workflows for adding Data Mining features to their Data Integration project, Karma.

Education

University of Southern California, USA

PhD in Computer Science• May 2020

I completed Doctor of Philosophy in Computer Science at University of Southern California. My research interests include Machine Learning applications in multiple domains with a focus on Deep Learning, Representation Learning, Adversarial Learning, Visual Semantics and Healthcare. I was advised by Prof. Premkumar Natarajan.

National Institute of Technology Calicut, India

BTech in Computer Science and Engineering • Gold Medalist • May 2014

I completed Bachelor of Technology in Computer Science and Engineering with the Gold Medal at National Institute of Technology Calicut, India.

Awards

  • Greatest Potential for Long-term Impact Award, Amazon Alexa NU Spark • Product idea with the largest long-term impact • Oct, 2023
  • Big Dream Believers Award, Amazon Demo Crawl • Award for thinking out of the box and building a demo of a bold new ambitious and visionary idea • Aug, 2023
  • 2nd Prize, Min Family Social Entrepreneurship Competition • Business idea with a large social impact • Apr, 2016
  • Global Impact Prize, USC Stevens Innovator Showcase • Business idea with the most global impact • Oct, 2015
  • Gold Medal, National Institue of Technology Calicut • Best academic performance in BTech (CSE) class of 2014 • Dec, 2014
  • Best Outgoing Student Award, Presented by Tata Consultancy Services • Best academic performance in BTech (CSE) class of 2014 • Jun, 2014
  • Prof. P.M. Jussay Award, Presented by NIT Calicut Alumni Association • Best academic performance in BTech (CSE) class of 2014 • Jan, 2014
  • Viterbi-India Award, Indo-US Science and Technology Forum • Scholarship awarded for summer research internship at University of Southern California. • Feb, 2013

Publications

2023
  • FashionNTM: Multi-turn fashion image retrieval via cascaded memory. Pal, A.; Wadhwa, S.; Jaiswal, A.; Zhang, X.; Wu, Y.; Chada, R.; Natarajan, P.; Christensen, H. In Proceedings of the IEEE/CVF International Conference on Computer Vision (CVPR), 2023.
  • User-controllable arbitrary style transfer via entropy regularization. Cheng, J.; Wu, Y.; Jaiswal, A.; Zhang, X.; Natarajan, P.; Natarajan, P. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2023.
2022
  • FashionVLP: Vision Language Transformer for Fashion Retrieval with Feedback. Goenka, S.; Zheng, Z.; Jaiswal, A.; Chada, R.; Wu, Y.; Natarajan, P.; Hedau, V. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
2021
  • Style-Aware Normalized Loss for Improving Arbitrary Style Transfer. Cheng, J.; Jaiswal, A.; Wu, Y.; Natarajan, P.; Natarajan, P. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
  • Class-agnostic Object Detection. Jaiswal, A.; Wu, Y.; Natarajan, P.; Natarajan, P. In Proceedings of the IEEE Winter Conference on Applications of Computer Vision (WACV), 2021.
  • Adversarial Mask Generation for Preserving Visual Privacy. Gupta, A.; Jaiswal, A.; Wu, Y.; Yadav, V.; Natarajan, P. In Proceedings of the IEEE International Conference on Automatic Face and Gesture Recognition (FG), 2021.
2020
  • MEG: Multi-Evidence GNN for Multimodal Semantic Forensics. Sabir, E.; Jaiswal, A.; AbdAlmageed, W.; Natarajan, P. In Proceedings of the International Conference on Pattern Recognition (ICPR), 2020.
  • Keypoints-aware Object Detection. Jaiswal, A.; Wu, Y.; Natarajan, P.; Natarajan, P. In Proceedings of the NeurIPS Pre-registration Workshop, 2020.
  • Invariant Representations through Adversarial Forgetting. Jaiswal, A.; Moyer, D.; Steeg, G.V.; AbdAlmageed, W.; Natarajan, P. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2020.
  • Discovery and Separation of Features for Invariant Representation Learning. Jaiswal, A.; Brekelmans, R.; Moyer, D.; Steeg, G.V.; AbdAlmageed, W.; Natarajan, P. arXiv Preprint, 2020.
  • CORD19STS: COVID-19 Semantic Textual Similarity Dataset. Guo, X.; Mirzaalian, H.; Sabir, E.; Jaiswal, A.; AbdAlmageed, W. arXiv Preprint, 2020.
2019
  • AIRD: Adversarial Learning Framework for Image Repurposing Detection. Jaiswal, A.; Wu, Y.; AbdAlmageed, W.; Masi, I.; Natarajan, P. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
  • RoPAD: Robust Presentation Attack Detection through Unsupervised Adversarial Invariance. Jaiswal, A.; Xia, S.; Masi, I.; AbdAlmageed, W. In Proceedings of the International Conference on Biometrics (ICB), 2019.
  • NIESR: Nuisance Invariant End-to-end Speech Recognition. Hsu, I.; Jaiswal, A.; Natarajan, P. In Interspeech, 2019.
  • Unified Adversarial Invariance. Jaiswal, A.; Wu, Y.; AbdAlmageed, W.; Natarajan, P. arXiv Preprint, 2019.
  • Recurrent Convolutional Strategies for Face Manipulation Detection in Videos. Sabir, E.; Cheng, J.; Jaiswal, A.; AbdAlmageed, W.; Masi, I.; Natarajan, P. In Proceedings of the CVPR Workshop on Applications of Computer Vision and Pattern Recognition to Media Forensics, 2019
2018
  • Unsupervised Adversarial Invariance. Jaiswal, A.; Wu, Y.; AbdAlmageed, W.; Natarajan, P. In Advances in Neural Information Processing Systems (NIPS), 2018
  • Bidirectional Conditional Generative Adversarial Networks. Jaiswal, A.; AbdAlmageed, W.; Wu, Y.; Natarajan, P. In Proceedings of the Asian Conference on Computer Vision (ACCV), 2018.
  • CapsuleGAN: Generative Adversarial Capsule Network. Jaiswal, A.; AbdAlmageed, W.; Wu, Y.; Natarajan, P. In Proceedings of the ECCV Workshop on Brain-Driven Computer Vision (BDCV), 2018.
2017
  • Multimedia Semantic Integrity Assessment Using Joint Embedding Of Images And Text. Jaiswal, A.*; Sabir, E.*; AbdAlmageed, W.; Natarajan, P. In Proceedings of the 2017 ACM on Multimedia Conference, 2017.
2016
  • Large-Scale Unsupervised Deep Representation Learning for Brain Structure. Jaiswal, A.; Guo D.; Raghavendra, C.S.; Thompson, P. arXiv Preprint, 2016.
2015
  • Brain Tumor Segmentation with Deep Learning. Rao, V.; Sarabi, M.; Jaiswal, A. MICCAI Multimodal Brain Tumor Segmentation Challenge (BraTS), 2015.
  • Autoencoder-derived Features as Inputs to Classification Algorithms for Predicting Well Failures. Liu, J.; Jaiswal, A.; Yao, K.; Raghavendra, C. S. Society of Petroleum Engineers Western Regional Meeting, 2015.
2014
  • Integration and Automation of Data Preparation and Data Mining. Narayanan, S.; Jaiswal, A.; Chiang, Y.; Geng, Y.; Knoblock, C.; Szekely, P. In Proceedings of the First Workshop on Data Integration and Application (ICDM DINA), 2014.
  • Explicit Semantic Analysis for Computing Semantic Relatedness of Biomedical Text. Jaiswal, A.; Bhargava, A. In Proceedings of Confluence The Next Generation Information Technology Summit (IEEE), 2014
  • Location Prediction With Sparse GPS Data. Jaiswal, A.; Chiang, Y.; Knoblock, C. A.; Lan, L. In Proceedings of the 8th Geographic Information Science. 2014.