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Dr. Sathya Aakur

Department of Computer Science

Dr. Sathya Aakur

I joined OSU as an Assistant Professor in the Department of Computer Science in Fall 2019. I earned my Ph.D. in Computer Science and Engineering in Summer 2019 and a master’s degree in Management Information Systems from the University of South Florida in Fall 2015. Before my graduate studies, I worked as a software engineer in the logistics industry and have a bachelor’s degree in Electronics and Communication Engineering from Anna University, Chennai.


Since my childhood, I have always been fascinated by three topics – the human brain, robotics, and computers. Combined with my fascination with science fiction novels on the future of mankind and technology, I naturally went on to pursue engineering and then on to computer science where I learned the foundations of communication, computer science, and electronics engineering. With this background, I aim to build computational approaches driven by artificial intelligence to allow robots to learn and perceive the world like humans. The real world is complex and requires an understanding of many different phenomena such as object permanence, physics, social interactions, and commonsense reasoning, among many other things. How the human brain balances all these factors, in addition to processing the onslaught of sensory observations is a mystery and serves as the inspiration for much of my group’s work. At the Computer Vision and Understanding Lab, we are interested in building computational models of the visual world that integrates perception and reasoning to build commonsense knowledge over time from large amounts of unlabeled data such as text, videos, and images. We work on building intelligent agents that understand the visual world beyond just recognition of objects or actions without the need for explicit human supervision leveraging cognitive theories of event perception and commonsense reasoning. Much of my group's current work focuses on analyzing, modeling, and synthesizing complex video scenes and the semantic structure that can describe them.


In addition to computer vision research, I am interested in using artificial intelligence for understanding biological processes. Specifically, I work with colleagues from the College of Veterinary Medicine to apply artificial intelligence to develop computational pipelines for detecting the presence of novel and emerging pathogens from genome data. This line of research offers an exciting alternative to traditional testing by allowing us to leverage the learning capabilities of artificial intelligence approaches to the problem of learning to detect pathogens from genome data and help improve the quality of life by early diagnosis and treatment of complex diseases to provide an acceptable and affordable option for use in diagnostic laboratories. Our research is funded by grants from the US Department of Agriculture (USDA) and the National Science Foundation (NSF). 


I married my college sweetheart in 2013 and we have one son and a puppy together. My family enjoys exploring new things, traveling, and watching movies together. Go Pokes!

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