Sathyanarayanan N. Aakur

Sathyanarayanan N. Aakur

Assistant Professor
Department of Computer Science and Software Engineering
Auburn University

Email: san0028 -at-

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Highlights and News

One paper accepted for Oral presentation at IEEE ICMLA 2023! Congrats to Shubham and my undergrad student Udhav on their second and first papers, respectively!
Serving as Area Chair for IEEE/CVF WACV 2024
Serving as Demo Chair and Area Chair at CVPR 2024! Looking forward to your submissions!
Moved to the CSSE Department at Auburn University!
Serving as Senior Program Committee Member for CODS-COMAD 2024
Our paper, with Dr. Sudeep Sarkar (USF), on neuro-symbolic knowledge distillation for commonsense NLI has been accepted into the prestigious IEEE Transactions on Pattern Analysis and Machine Intelligence! Preprint to come soon!
Serving as Area Chair for NeurIPS 2023!
One paper on Scene Graph Generation accepted at CVPR 2023. Congrats to Sanjoy on his first CVPR paper and third overall. Preprint here
Received funding from USDA for multimodal time series classification for stress detection in precision agriculture!
Serving as Area Chair for CVPR 2023 !
Two papers accepted at ECCV 2022!
Received the prestigious NSF CAREER award to pursue research on multi-modal event understanding!
More news..

About Me

I am an Assistant Professor in the Computer Science and Software Engineering Deoartment at Auburn University. Previously, I was an Assistant Professor in the Department of Computer Science at Oklahoma State University, Stillwater.

I received my PhD from University of South Florida, where I worked with Dr. Sudeep Sarkar in the Computer Vision and Pattern Recognition Group and with Dr. Kenneth Malmberg. I received my Master's degree in Management Information Systems from the Muma College of Business at the University of South Florida and my undergraduate degree in Electronics and Communication Engineering from Velammal Engineering College, Anna University, India.


In my research, I’m broadly interested in the intersection of computer vision, natural language processing, and psychology: I aim to build intelligent agents that understand the visual world beyond recognition (labels) or captions (sentences) without the need for explicit human supervision through expensive annotations.

This entails developing approaches that do things such as:

Much of my group's current work focuses on analyzing, modeling, and synthesizing complex video scenes and the semantic structure that can describe them. I also work on applying machine learning to other domains, such as IoTs We also work on use-inspired artificial intelligence research with applications in agriculture and animal diagnostics.