Computer Science at OSU

             Computer Science is the study of the theory of computing and algorithms and their applications to solve real-world problems. This is a rapidly-developing field with applications in all areas of human endeavor. The discipline encompasses many specialized subfields with different theoretical models and focuses on practical problem-solving. Courses in the OSU Computer Science program teach students the latest technology in software development with hands-on experience with tools and frameworks supported by learning labs. Our highly-talented faculty emphasizes both research and teaching in areas such as artificial intelligence, computer vision, big data, immersive computing, security, and robotics. The Department of Computer Science takes pride in providing a safe, diverse, and inclusive learning environment that facilitates close interaction with faculty with the goal to ensure the success of every student.

Please check out our Mission, Objectives, and Student Outcomes. 

Departmental Calendar: CS Calendar

New Research

Sathyanarayanan Aakur is broadly interested in the intersection of computer vision, natural language processing, and psychology.  His aim is to build intelligent agents that understand the visual world beyond recognition (labels) or captions (sentences) without the need for explicit human supervision. This entails developing approaches such as self-supervised predictive learning for video event segmentation, common sense reasoning for ground perception and prior knowledge, and generative modeling for building knowledge.

Arunkumar Bagavathi focuses on designing deep-learning frameworks to learn multiple activities in social media to enhance network-based machine learning tasks such as prediction, forecasting, and clustering. His work also leverages the use of cloud tools to frame a collection of scalable data-agnostic models to glean actionable recommendations from massive data sources. For example, his multiplex model can identify user communities in social media from their various activities and his action-mining model can impart personalized recommendations for hospitals to handle patients to improve care and reduce readmission rates.

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