Computer Science
Research

About our Research

The Department of Computer Science at Cleveland State University is engaged in pioneering research supported by grants and partnerships with leading organizations. The department is very active in research.

Research areas span machine learning, deep learning, AI in healthcare, smart grid technology, data science, quantum computing, and more. Students have the opportunity to work on funded projects, collaborating with faculty on publications and presentations that contribute to the global knowledge base in computer science. Partnerships with Cleveland-area companies like Hyland Software, KeyBank, and the Cleveland Clinic enable students to address pressing industry needs through research that combines theoretical innovation with practical application.

Research Labs

Big Data Analytics & AI Lab

Sunnie Sun Chung, Ph.D.

Big Data is changing every aspect of modern life. Research in Big Data Analytics & AI Lab focuses on how to shape the changes by Big Data better.
 

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Center for Computing Education and Instruction

_{^{Stefan Andrei, Ph.D., Executive Director
Dr. Rebecca Odom-Bartel, Ph.D., Lead Research and Content Development}}

The Center for Computing Education and Instruction (CCEI) advances high-quality computer science and AI education through teacher preparation, curriculum innovation, and research on teaching and learning. The Center focuses not only on expanding access to computing, but on improving how computer science is taught across K–12 and higher education settings. By connecting research, instructional design, and classroom practice, CCEI develops scalable approaches that prepare educators and students for a rapidly evolving digital and AI-driven world.
 

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Human-Technology Interaction Lab

Apostolos Kalatzis, Ph.D.

At the Human-Technology Interaction Lab (HTI Lab), we focus on humanizing technology by putting humans at the center of the interaction. Our research seeks to understand the limitations of human-technology interactions, ensuring that technological advancements are designed to enhance, rather than hinder, human capabilities. 
 

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Intelligent Secure Cyber-Systems and Applications Research (ISCAR) Lab

Sathish Kumar, Ph.D.

ISCAR lab focuses research in the intersection of the following areas: Cybersecurity; Artificial Intelligence/Machine Learning; and Quantum Computing.
 

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Real-Time Embedded Systems Lab

Stefan Andrei, Ph.D.

The Real-Time Embedded Systems Lab at CSU discusses the design and implementation of laboratory equipment suitable for teaching and research in this area. The design and implementation of laboratory equipment are foundational to global scientific progress, ensuring safety, precision, and reproducibility.

Secure and Intelligent Systems and Networks Lab

Haodong Wang, Ph.D.

The Secure and Intelligent Systems and Networks Lab at CSU studies the cutting edge research problems in the areas of IoTs security and automation solutions, robust security system design and implementation for resource constrained devices, end-to-end security design for large and heterogenous computing systems, and developing high performance computing intensive security schemes.

Jingru Zhang Lab

Jingru Zhang, Ph.D.

To Be Announced.

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Efficient and Robust Machine Learning Lab

Tianyun Zhang, Ph.D.

The Efficient and Robust Machine Learning Lab at CSU focuses on optimization-driven approaches for designing efficient, scalable, and robust deep neural networks. Our research aims to improve the performance, reliability, and resource efficiency of modern machine learning systems, enabling their deployment in real-world applications where computational constraints and robustness are critical considerations.

Security and Privacy Research Lab

Ye Zhu, Ph.D.

The Security and Privacy Research Lab at CSU focuses on security and privacy research topics on networking, computing including wearable computing, big data, machine learning/deep learning, and IoT.

Teaching Labs

Parallel and Distributed Computing Laboratory

Janche Sang, Ph.D.

The Parallel and Distributed Computing Laboratory is a dedicated teaching facility designed to support courses in operating systems, parallel programming, distributed systems, and network computing. The laboratory consists of a cluster of Linux workstations interconnected via a network, with each workstation equipped with a dedicated GPU and the NVIDIA CUDA development environment. This infrastructure enables students to gain hands-on experience in multicore and manycore programming,  and distributed application development using modern parallel/network computing technologies.

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