Sathyanarayanan N. Aakur

me
Sathyanarayanan N. Aakur

Assistant Professor
Department of Computer Science
Oklahoma State University

Email: saakurn -at- okstate.edu

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Highlights and News


2019-2020:
I will be on the Program Committee/Reviewer for WACV 2019, ICCV 2019, AAAI 2020, CVPR 2020, CRV 2020, ECCV 2020.
Fall '19:
One paper accepted at VLSID 2020 on Dissecting CNNs for Implementation on Constrained Platforms.
Fall '19:
One paper accepted at IFIP IoT on Latent Space modeling for PUF encrypted IoT Node security.
Summer '19:
I have accepted a position as Assistant Professor at Oklahoma State University. Exciting times ahead!
Spring '19:
One paper accepted at ISVLSI on Machine Learning based Attack and Defense for PUF-based IoT Security.
Spring '19:
One paper accepted at CVPR on Video Event Segmentation with Self-Supervised Learning.
Fall '18:
Paper on Open Domain Activity Interpretation accepted in Quarterly of Applied Mathematics.
Fall '18:
One paper accepted at WACV 2019 on Video Activity Interpretation using Commonsense Knowledge.

About Me

I am an Assistant Professor of Computer Science at Oklahoma State University.

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.

Research

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 IoT security and running deep learning algorithms on constrained platforms like FPGA.

Teaching

Group

I lead the Computer Vision and Understanding Lab. Here are the current and past members:

Students

Funding

My group is supported by the following:

Talks