Computer Science

Female student writing on a white board with a big screen behind her with code on it.

About the Department of Computer Science

At Luddy Bloomington, we prepare students to lead the future of computing by combining computer science theory, systems, and applications in areas such as algorithms, artificial intelligence, biomedical and health technologies, cybersecurity, quantum computing, and robotics.

Founded in 1969, we bring over 50 years of leadership in research and education, and we continue to innovate in the rapidly changing technology landscape.

Learning at a research university

As part of IU, students have access to advanced labs, high-speed infrastructure, and one of the fastest university supercomputers in the country—Big Red 200. We support interdisciplinary study through collaborations with other IU programs and provide opportunities for hands-on research at every level.

Undergraduate programs

Tap into the power of computing

B.S. in Computer Science

Learn computing theory and how to use computers to solve problems. This degree prepares you for a wide range of in-demand careers.

Broaden your expertise

Minor in Computer Science

Add computer science to your skill set and open doors to a wider variety of career opportunities.

Two degrees in five years

Accelerated M.S. in Computer Science

Strengthen your technical skills with a master’s degree earned in just one extra year after your B.S. in Computer Science.

Fast-tracking your future

Accelerated M.S. in Secure Computing

Specialize in cybersecurity by adding one year to your B.S. in Computer Science and earning a master’s degree.

CS research areas at Luddy

Algorithms and theoretical computer science

Theoretical computer science focuses on the very foundations of computing. It is concerned with abstract models of computation (such as the Turing machine, von Neumann architecture, or quantum computers), how real-world computers relate to these models, and the types of problems these models can solve. It also deals with designing efficient algorithms that can solve foundational problems and analyzing the algorithms’ performance mathematically.

Artificial intelligence and machine learning

Artificial intelligence research encompasses foundational areas such as knowledge representation, reasoning, planning, and decision making, as well as applied areas such as vision, speech, and music processing. Machine learning is a highly influential subfield of artificial intelligence that is concerned with the development of systems that learn from experience and the use of large training data to improve their performance on specific tasks.

Bioinformatics and computational biology

Bioinformatics and computational biology are concerned with processing and managing large-scale biomolecular (especially sequential) data to better understand living systems and predict their behavior. These areas also focus on the discovery and analysis of the root causes of diseases—for example, in the form of genomic alterations—and investigate how they affect cellular systems.

Computer vision, speech, and music processing

Computer vision, speech, and music processing are among the most significant application areas of machine learning and AI. Research focuses on visual and auditory pattern recognition, 3D image reconstruction, visual and speech classification, vision and speech processing for robotics, musical signal processing, and computer music generation.

Databases and data mining

Research in databases and data mining is concerned with the improvement of data organization with the primary goal of providing efficient and meaningful access to information, explicitly presented or implicitly included in large data sets with diverse types and structures.

Programming languages

Programming languages provide means of expressing computational tasks in a succinct, flexible, secure, reliable, efficient, and reusable manner. Research involves the design and implementation of new languages and language constructs, and analysis and improvement of existing languages through formal methods and proofs.

Security and privacy

Security and privacy research at IU focuses on areas such as systems, software, and network security as well as privacy-preserving processing of biomedical data, to provide means of protection from various forms of outside attacks.

Systems and high performance computing

This area focuses on designing and optimizing hardware and software to more efficiently perform large-scale computations, especially through the use of parallelism. This research also focuses on theoretical and applied work on computer architecture.

Teaching and learning

Research in teaching and learning involves the examination of pedagogy practices, student learning outcomes, and strategies for collecting and analyzing data related to teaching computer science, with the goal of improving the student learning experience.

A male student standing in front of a white board with a formula on it, while he explains it to a female in front of him.
The past leading the future

Alumni & donor engagement

Our alumni and donors help drive student success by mentoring, recruiting, and supporting scholarships, research, and travel through the Computer Science Student Fund and other initiatives.

Luddy CS in the news

Discover how CS at Luddy is building what's next.

Jan 27, 2026

Luddy School Online Master’s Info Tech Program improves 29 spots in national rankings

The Luddy School's Online Master's Information and Technology Program improved 29 spots to No. 30 nationally in the 2026 U.S. News & World Report Best Online Master's in Information Technology Programs ratings.

Jan 13, 2026

Luddy computer science professor, student, high-school teacher co-author cover story

Luddy School professor Dan-Adrian German co-authored a cover story in the prestigious ACM Inroads along with Luddy student John M. Phillips and a high school teacher that showcased the fast-growing field of quantum computing, why it matters and how educators can make it accessible to students.

Dec 8, 2025

Luddy research team honored for paper on using AI to improve climate disaster management

AI's ability to improve climate disaster management was the focus of an award-winning paper produced by Luddy School Computer Science Associate Professor Da Yan and his research team. 

Contact Computer Science

812-855-6486
iucs@iu.edu

Luddy Hall 2062
700 N. Woodlawn Avenue
Bloomington, IN 47408