Research

Research

Computer Science at Indiana University explores a broad range of areas to push the boundaries of modern computing. Our faculty work closely in a number of disciplines, primarily focusing on the following areas of research.

BioInformatics

Our research in bioinformatics is concerned with the processing and managing of biological data to understand living systems and guide decisions about them, mostly at the molecular level. By organizing and systemizing data to develop algorithms, we make inferences about that data to aid research in computational biology, biomedical informatics and clinical informatics. Through the use of genetic and genomic data, our research allows us to better understand the core causes of disease and use big data to attack biological problems at their root.


Computer Science faculty in this area include:
Raj Acharya, Volker Brendel, Mehmet Dalkilic, Matthew Hahn, Paul Purdom, Predrag Radivojac, Endre Somogyi, Haixu Tang, Yuzhen Ye

Intelligent Systems

Intelligent systems encompasses a number of subfields studying reasoning and learning methods that collect data, analyze it and make inferences about the real world.

Artificial intelligence, machine learning, and data mining provides decision support for physicians, makes recommendations to consumers, aids scientists at complex tasks, and provides intelligent user interfaces and knowledge management systems.

Computer Science faculty in this area include:
Randall Beer, David Crandall, Funda Ergun, Geoffrey Charles Fox, Michael Gasser, Andrew Hanson, Apu Kapadia, David Leake, Andrew Lumsdaine, Sriraam Natarajan, Beth Plale, Predrag Radivojac, Christopher Raphael, Michael Ryoo, Chung-chieh Shan, Dirk Van Gucht, Donald Williamson, Grigory Yaroslavtsev, Yuzhen Ye, Qin Zhang, Yuan Zhou

Programming Languages

Our research on programming languages focuses on two key areas – the practical side and the more philosophical aspects of programming.

We are also working to build bridges between mainstream languages and cutting-edge approaches, such as logic programming, that will enable programming at a higher-level. Our research on the philosophical side looks for connections with other fields to discover how they are interrelated and identify patterns that can be useful in other disciplines, such as quantum physics, to push the envelope to programming and computing.

Computer Science faculty in this area include:
R. Kent Dybvig, Daniel Friedman, Christopher Haynes, Steven Johnson, Andrew Lumsdaine, Ryan Newton, Gregory J. E. Rawlins, Amr Sabry, Chung-chieh Shan, Dirk Van Gucht

Security

Our researchers work in areas such as systems, software, and network security to protect from outside attack, and usable security to ensure people from broad ranges.

That’s why few areas are more important to the future of computing than security. IU features one of the most robust security groups in the nation. Our researchers work in areas such as systems, software, and network security to protect from outside attack, and usable security to ensure people from broad ranges.

Computer Science faculty in this area include:
L. Jean Camp, Minaxi Gupta, Ryan Henry, Raquel Hill, Yan Huang, Apu Kapadia, Steven Myers, XiaoFeng Wang

Databases

Research into the improvement of the organization of data makes information more quickly accessible and develops the tools to identify problematic data.

Our work in analyzing, modeling and more efficiently applying information allows better data management for both mobile and stationary systems while providing a better workflow. Research into the improvement of the organization of data makes information more quickly accessible and develops the tools to identify problematic data.

Computer Science faculty in this area include:
Mehmet Dalkilic, Paul Purdom, Dirk Van Gucht, Qin Zhang

Data Mining

Our research on data mining identifies patterns in data that solves both computational and practical problems.

Analyzing and extracting information from data can solve issues in bioinformatics, intelligence systems and machine learning, and our work in improving both the collection of and organization of data pushes computing to the next frontier.

Computer Science faculty in this area include:
Adeel Bhutta, David Crandall, Mehmet Dalkilic, Andrew Hanson, Mitja Hmeljak, Andrew Lumsdaine, Beth Plale, Paul Purdom, Predrag Radivojac, Christopher Raphael, Haixu Tang, Dirk Van Gucht, Donald Williamson, Grigory Yaroslavtsev, Yuzhen Ye, Qin Zhang

Foundation Theory

Our work on Foundational Theory focuses on the study of the applied logic, algorithms, computational models, and methods that form the basis of computer science.

Studying the foundations of computing allows us to build more reliable systems and push the frontiers of computing while better understanding the relationship between computers and the world around us using computational complexity theory and other approaches.

Computer Science faculty in this area include:
Funda Ergun, Daniel Friedman, Steven Myers, Paul Purdom, Gregory J. E. Rawlins, Dirk Van Gucht, Qin Zhang

Parallel Systems

Designing and optimizing both hardware and software to more efficiently operate on a large scale is the focus of our research into parallel systems.

Our work on synchronizing mobile and location-based computing to more efficiently use cloud computing and data pushes the limits of systems. We also focus on high-performance computing, big data and how to best utilize multiple processors to accelerate computations while minimizing bugs and maximizing reliability.

Computer Science faculty in this area include:
Randall Bramley, Volker Brendel, Arun Chauhan, Funda Ergun, Geoffrey Charles Fox, Minaxi Gupta, Christopher Haynes, Raquel Hill, Steven Johnson, Apu Kapadia, Andrew Lumsdaine, Ryan Newton, Feng Qian, Gregory J. E. Rawlins, Jeremy Siek, Martin Swany, Sam Tobin-Hochstadt, Grigory Yaroslavtsev

Hardware

Our research in improving methods for designing system hardware and how to better utilize the computing tools currently at our disposal is the focus of our work in hardware.

Using digital technology – and in some cases, analog hardware – we can find more efficient systems that use less power while outputting improved performance. Research also focuses on both experimental and theoretical work on computer architecture.

Computer Science faculty in this area include:
Geoffrey Brown, Eduardo Izquierdo, Gerardo Ortiz, Beth Plale