Computer Science: Academic Units: Academics: Luddy School of Informatics, Computing, and Engineering: Indiana University Bloomington

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.

Develop next-generation computing solutions

M.S. Computer Science

Dive deep into programming, software engineering, AI, machine learning, big data, and cybersecurity—everything you need to lead in tomorrow’s tech-driven world.

Guard the digital frontier

M.S. Secure Computing

Turn big data into bigger discoveries

M.S. Bioinformatics

Blend computational biology, data analysis, machine learning, and genomics to turn big biological data into big breakthroughs in health, tech, and biotech.

Push the boundaries of computing research

Ph.D. Computer Science

You'll work alongside leading faculty on advanced research in areas like artificial intelligence, data science, computer vision, and high-performance computing.

Designed to fit into your schedule

Graduate Certificate in Cybersecurity

Gain the skills to secure digital systems and protect critical information. This program prepares you to meet today’s cybersecurity challenges head-on.

Broaden your expertise

Ph.D. Minor in Computer Science

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

Our world class educators and researchers use computing to solve real-world problems while mentoring the next generation of innovators and expand what's possible for people everywhere.

Core Faculty
Adjunct Faculty
Research Areas

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.

Apr 22, 2026

Resonix team wins ‘best-ever’ Cheng Wu Innovation Challenge

Luddy School computer science master's students Dikshitha Karanam Madhusudhanprasad, Jahnavi Vemuri and Preetham Reddy Rallapalli combined compelling research and extraordinary effort to win the "best-ever" Cheng Wu Innovation Challenge.