Research Areas

Artificial Intelligence (AI) has a long history in our department, and currently supports a very dynamic program of research and education. Our educational curriculum provides a broad range of courses including introductory AI, automated planning, cognitive modeling, commonsense reasoning, evolutionary computation, game theory, machine learning, multi-agent systems, natural language processing, and neural computation. The AI group has consistently ranked high in external national assessments: for example, in the US News ranking of best graduate schools, our AI program is ranked 9th among all universities and 6th among public universities.

Many of our former students have gone on to very high levels of achievement. Examples include Vipin Kumar (PhD 1982), Fellow of the AAAS, ACM, and IEEE; Qiang Yang (PhD 1989), Fellow of the IEEE; Naresh Gupta (PhD 1993), Senior Vice President at Adobe; Lee Spector (PhD 1992), Fellow of the ISGEC; Gary Flake (PhD 1993), Microsoft Distinguished Engineer and well known author of The Computational Beauty of Nature; Narendra Ahuja (PhD 1979), Fellow of the IEEE, AAAI , SPIE, and ACM; and Granger Sutton (PhD 1992), whose software was used in the first-ever assembly of the complete whole genome of a free-living organism, the Haemophilus influenzae genome.

Associated Faculty

Photo of John Aloimonos

John Aloimonos

Professor
Photo of Jordan Boyd-Graber

Jordan Boyd-Graber

Associate Professor
Photo of Marine Carpuat

Marine Carpuat

Assistant Professor
Photo of Hal Daumé III

Hal Daumé III

Professor
Photo of Larry Davis

Larry Davis

Professor
Director of the Center for Automation Research (CfAR)
Photo of John Dickerson

John Dickerson

Assistant Professor
Photo of Tom Goldstein

Tom Goldstein

Assistant Professor
Photo of Furong Huang

Furong Huang

Assistant Professor
Photo of David Jacobs

David Jacobs

Professor
Associate Chair of Graduate Education
Photo of Ming Lin

Ming Lin

Professor
Elizabeth Stevinson Iribe Chair of Computer Science
Photo of Dinesh Manocha

Dinesh Manocha

Professor
Paul Chrisman Iribe Professor of Computer Science and Professor of Electrical and Computer Engineering
Photo of Dana Nau

Dana Nau

Professor
Photo of Don Perlis

Don Perlis

Professor
Photo of James Reggia

James Reggia

Professor
Photo of William Regli

William Regli

Professor
Director, Institute for Systems Research (ISR)
Photo of Hanan Samet

Hanan Samet

Professor
Distinguished University Professor
Photo of Abhinav Shrivastava

Abhinav Shrivastava

Assistant Professor
Photo of Bonnie Dorr

Bonnie Dorr

Professor Emerita
Photo of Laveen Kanal

Laveen Kanal

Professor Emeritus
Photo of Jack Minker

Jack Minker

Professor Emeritus
Photo of Lise Getoor

Lise Getoor

Adjunct Professor
Photo of John Grant

John Grant

Adjunct Professor
Photo of Ramalingam Chellappa

Ramalingam Chellappa

Affiliate Professor
Minta Martin Professor of Engineering and Chair; Distinguished University Professor
Photo of Doug Oard

Doug Oard

Affiliate Professor
Photo of Philip Resnik

Philip Resnik

Affiliate Professor

Theoretical Computer Science (TCS) is concerned with understanding the very nature of computation: What problems can be solved by computers and how efficiently can such problems be solved? Can "hard" problems be used to our advantage in any way? TCS encompasses research in such diverse areas as complexity theory, algorithms, cryptography and coding theory, distributed and parallel computing, social networks, machine learning, game theory, and more. The common thread is a focus on precise models and rigorous mathematical analysis of particular problems within those models.

Associated Faculty

Photo of Andrew Childs

Andrew Childs

Professor
Co-director, Joint Center for Quantum Information and Computer Science (QuICS)
Photo of William Gasarch

William Gasarch

Professor
Photo of Mohammad Hajiaghayi

Mohammad Hajiaghayi

Professor
Jack and Rita G. Minker Professor
Photo of Furong Huang

Furong Huang

Assistant Professor
Photo of Jonathan Katz

Jonathan Katz

Professor
Distinguished Scholar-Teacher
Photo of Samir Khuller

Samir Khuller

Professor
Distinguished Scholar Teacher
Photo of Clyde Kruskal

Clyde Kruskal

Associate Professor
Photo of Max Leiserson

Max Leiserson

Assistant Professor
Photo of David Mount

David Mount

Professor
Associate Chair of Undergraduate Education
Photo of Hanan Samet

Hanan Samet

Professor
Distinguished University Professor
Photo of Aravind Srinivasan

Aravind Srinivasan

Professor
Photo of Xiaodi Wu

Xiaodi Wu

Assistant Professor
Photo of Brad Lackey

Brad Lackey

Adjunct Professor
Photo of Yi-Kai Liu

Yi-Kai Liu

Adjunct Associate Professor
Photo of Carl Miller

Carl Miller

Adjunct Assistant Professor
Photo of Alexander Barg

Alexander Barg

Affiliate Professor
Photo of Dana Dachman-Soled

Dana Dachman-Soled

Affiliate Assistant Professor
Photo of Joseph Ja' Ja'

Joseph Ja' Ja'

Affiliate Professor
Photo of Andre Tits

Andre Tits

Affiliate Professor
Photo of Uzi Vishkin

Uzi Vishkin

Affiliate Professor

Computational Biology and Bioinformatics is a multidisciplinary area dedicated to answering questions arising from the genome revolution. It spans multiple areas in computer science, including algorithms for combinatorial optimization, machine learning, data management, and scientific computing. It brings together scientists and engineers from many fields, including computer science, molecular biology, genomics, genetics, mathematics, statistics, and physics. The Center for Bioinformatics and Computational Biology is organized as a center within the University of Maryland Institute for Advanced Computer Studies (UMIACS), an interdisciplinary research institute supporting high-performance computing research across the College Park campus. 

Associated Faculty

Photo of Hector Corrada Bravo

Hector Corrada Bravo

Associate Professor
Photo of Max Leiserson

Max Leiserson

Assistant Professor
Photo of Atif Memon

Atif Memon

Professor
Photo of Mihai Pop

Mihai Pop

Professor
Interim Director, University of Maryland Institute for Advanced Computer Studies (UMIACS)
Photo of Eytan Ruppin

Eytan Ruppin

Professor
Photo of Aravind Srinivasan

Aravind Srinivasan

Professor
Photo of Michael Cummings

Michael Cummings

Affiliate Associate Professor
Photo of Sridhar Hannenhalli

Sridhar Hannenhalli

Affiliate Associate Professor

The University of Maryland has one of the oldest and largest research groups in computer vision in the US.  The Center for Automation Research (CFAR) was founded in 1964 by computer vision pioneer Azriel Rosenfeld, and CFAR still houses a large and thriving computer vision community, consisting of almost a dozen faculty and roughly fifty graduate students.  Research at UMD addresses every aspect of computer vision, featuring work in areas such as Face Recognition, Vision for Robotics, 3D Reconstruction, Image Segmentation, and Visual Classification.  Much of this work explores the use of Big Data and Deep Learning in Computer Vision.  The work at UMD is quite interdisciplinary, drawing students and faculty from CS, ECE and Applied Math, and forming close collaborations with other areas of computer science such as Human-Computer Interaction, Machine Learning, Computer Graphics, Augmented and Virtual Reality, Robotics, and Optimization.

Associated Faculty

Photo of John Aloimonos

John Aloimonos

Professor
Photo of Larry Davis

Larry Davis

Professor
Director of the Center for Automation Research (CfAR)
Photo of Ramani Duraiswami

Ramani Duraiswami

Professor
Photo of Tom Goldstein

Tom Goldstein

Assistant Professor
Photo of David Jacobs

David Jacobs

Professor
Associate Chair of Graduate Education
Photo of Ming Lin

Ming Lin

Professor
Elizabeth Stevinson Iribe Chair of Computer Science
Photo of Hanan Samet

Hanan Samet

Professor
Distinguished University Professor
Photo of Abhinav Shrivastava

Abhinav Shrivastava

Assistant Professor
Photo of Ramalingam Chellappa

Ramalingam Chellappa

Affiliate Professor
Minta Martin Professor of Engineering and Chair; Distinguished University Professor
Photo of Leila De Floriani

Leila De Floriani

Affiliate Professor
Photo of David Doermann

David Doermann

Affiliate Senior Research Scientist

Faculty work on multiple aspects of computer security, with particular strengths in cryptography, programming-language security, and network security. We also collaborate closely with faculty working in this field in other departments, through the Maryland Cybersecurity Center.

Associated Faculty

Photo of Jeffrey Foster

Jeffrey Foster

Professor
Associate Chair for Graduate Education
Photo of Michael Hicks

Michael Hicks

Professor
Associate Chair of Undergraduate Education; Distinguished Scholar-Teacher
Photo of Jonathan Katz

Jonathan Katz

Professor
Distinguished Scholar-Teacher
Photo of Pete Keleher

Pete Keleher

Associate Professor
Photo of Dave Levin

Dave Levin

Assistant Professor
CS Honors Chair
Photo of Michelle Mazurek

Michelle Mazurek

Assistant Professor
Photo of Neil Spring

Neil Spring

Professor
Associate Chair of Facilities
Photo of David Van Horn

David Van Horn

Assistant Professor
Photo of William Arbaugh

William Arbaugh

Associate Professor Emeritus
Photo of Dov Gordon

Dov Gordon

Visiting Senior Research Scientist
Photo of Michael Marsh

Michael Marsh

Visiting Research Scientist
Photo of Peter Druschel

Peter Druschel

Adjunct Professor
Photo of Brad Lackey

Brad Lackey

Adjunct Professor
Photo of Elaine  Shi

Elaine Shi

Adjunct Associate Professor
Photo of Michel Cukier

Michel Cukier

Affiliate Associate Professor
Photo of Dana Dachman-Soled

Dana Dachman-Soled

Affiliate Assistant Professor
Photo of Tudor Dumitras

Tudor Dumitras

Affiliate Assistant Professor
Photo of Charalampos (Babis) Papamanthou

Charalampos (Babis) Papamanthou

Affiliate Assistant Professor

In recent years, we have seen a tremendous increase in the data available in the digital format, the World Wide Web being a prominent example, and this trend is expected to accelerate with the increasing proliferation of devices, ranging from genome sequencing machines to microscopic biomedical sensors, that are capable of capturing even the minutest details of our everyday world. The database group at the University of Maryland at College Park carries out a multi-faceted and diverse research agenda that focuses on exploring the data management challenges in a wide variety of environments. Some of the most important focus areas over the last few years include life sciences and biological databases, graph databases, sensor network data management, social network data management, mobile databases, P2P networks, and unstructured text databases. At the same time, the database group has continued innovating in the traditional data management topics such as managing and querying data warehouses, spatial databases, query processing and optimization, data streams, approximate query processing, and data mining.

Associated Faculty

Photo of Daniel Abadi

Daniel Abadi

Professor
Darnell-Kanal Professor of Computer Science
Photo of Leilani Battle

Leilani Battle

Assistant Professor
Photo of Amol Deshpande

Amol Deshpande

Professor
Photo of John Dickerson

John Dickerson

Assistant Professor
Photo of Mohammad Hajiaghayi

Mohammad Hajiaghayi

Professor
Jack and Rita G. Minker Professor
Photo of Samir Khuller

Samir Khuller

Professor
Distinguished Scholar Teacher
Photo of Hanan Samet

Hanan Samet

Professor
Distinguished University Professor
Photo of Alan Sussman

Alan Sussman

Professor
Photo of Lise Getoor

Lise Getoor

Adjunct Professor
Photo of Vanessa Frias-Martinez

Vanessa Frias-Martinez

Affiliate Assistant Professor
Photo of Richard Marciano

Richard Marciano

Affiliate Professor
Photo of Louiqa Raschid

Louiqa Raschid

Affiliate Professor

The University of Maryland's Graphics and Visual Informatics Laboratory (GVIL) was established in 2000 by the Department of Computer Science and the University of Maryland Institute for Advanced Computer Studies to promote research and education in computer graphics, scientific visualization, and virtual environments. Here, we work to improve the efficiency and usability of visual computing applications in science, engineering, and medicine. The scope of this laboratory's research covers design of algorithms and data structures for reconciling realism and interactivity for very large graphics datasets, leveraging principles of visual saliency for architecting visual attention management tools, building systems for rapid access to distributed graphics datasets across memory and network hierarchies, and study of the influence of heterogeneous display and rendering devices over the visual computing pipeline. The activities of the laboratory involve development of visual computing tools and technologies to support the following research-driving applications: protein folding and rational drug design, navigation and interaction with mechanical CAD datasets, and ubiquitous access to distributed three-dimensional graphics datasets.

Our cutting-edge displays, like the Augmentarium, allow for the effective visualization of large and complex data, and for higher-level products derived from data, which are essential to engage the creativity of the human brain to find patterns and relationships that would otherwise remain unobserved.

Further information is available at http://www.cs.umd.edu/gvil/

Augmented and virtual reality (AR and VR) are poised to change our world in ways we only could have imagined a few years ago. At the University of Maryland we are working on several driving applications for next-generation virtual and augmented reality, including augmented navigation, medical training, virtual manufacturing, and immersive education. We are developing technologies in five interconnected thrust areas: scene capture and generation; tracking and registration; multimodal rendering; displays; and interfaces and usability.

For scene capture and generation, we are working on both mobile and stationary multi-camera arrays that enable us to capture the light fields of real-world immersive environments with resolution matching human visual acuity. Using one of these unique arrays, we have recorded live footage of actual surgeries at UMB’s Shock Trauma Center, and we are building towards high-fidelity telepresence using arrays of over 1000 cameras.

We are designing, developing, and validating both multimodal rendering algorithms and low-latency embedded systems that are extremely efficient, consume very little power, use information about the salient components of the scene and just-in-time tracking to scale up to very high resolution displays at high frame rates needed to maintain the illusion of immersion, vital to VR experiences.

To address interface and usability issues in VR and AR, we must understand the cause of psychophysical problems that arise from extended exposure to immersive environments. We are currently developing real-time algorithms for multi-stream visualization and data mining from EEG data on modern parallel environments to classify and quantify the onset of cybersickness.

More information is available at http://augmentarium.umd.edu.

Associated Faculty

Photo of John Aloimonos

John Aloimonos

Professor
Photo of Ming Lin

Ming Lin

Professor
Elizabeth Stevinson Iribe Chair of Computer Science
Photo of Dinesh Manocha

Dinesh Manocha

Professor
Paul Chrisman Iribe Professor of Computer Science and Professor of Electrical and Computer Engineering
Photo of Hanan Samet

Hanan Samet

Professor
Distinguished University Professor
Photo of Amitabh Varshney

Amitabh Varshney

Professor
Dean, College of Computer, Mathematical, and Natural Sciences
Photo of Matthias Zwicker

Matthias Zwicker

Professor
Reginald Allan Hahne Endowed E-nnovate Professorship
Photo of Leila De Floriani

Leila De Floriani

Affiliate Professor

High Performance Computing involves using large computers to solve major scientific and engineering problems.  HPC is used from weather prediction to designing consumer products.  The members of the HPC group at Maryland investigate many aspects of High Performance Computing from innovations in core numerical algorithms, to system software and tools to enabling productive use of large-scale computation.

Numerical analysis and scientific computing have a long history in our department, dating from the 1970s. Our research today includes work on numerical linear algebra, ill-posed problems, fast summation methods, and the use of such ideas in diverse applications such as imaging, fluid dynamics and acoustics. The group has always had close ties with numerical analysts in the Mathematics Department, and our students are drawn from the Department of Computer Science as well as the Applied Mathematics and Scientific Computing Program.

Associated Faculty

Photo of Ramani Duraiswami

Ramani Duraiswami

Professor
Photo of Howard Elman

Howard Elman

Professor
Photo of Tom Goldstein

Tom Goldstein

Assistant Professor
Photo of Jeffrey K. Hollingsworth

Jeffrey K. Hollingsworth

Professor
Vice President & CIO, University of MD
Photo of Ming Lin

Ming Lin

Professor
Elizabeth Stevinson Iribe Chair of Computer Science
Photo of Dinesh Manocha

Dinesh Manocha

Professor
Paul Chrisman Iribe Professor of Computer Science and Professor of Electrical and Computer Engineering
Photo of Alan Sussman

Alan Sussman

Professor
Photo of Amitabh Varshney

Amitabh Varshney

Professor
Dean, College of Computer, Mathematical, and Natural Sciences
Photo of Dianne O'Leary

Dianne O'Leary

Professor Emerita
Distinguished University Professor
Photo of G.W. (Pete) Stewart

G.W. (Pete) Stewart

Professor Emeritus
Distinguished University Professor
Photo of Ray Chen

Ray Chen

Faculty Research Assistant
Photo of Sukhyun Song

Sukhyun Song

Research Associate

Founded in 1983, UMD’s Human-Computer Interaction lab is one of the world's oldest centers for the study of human centered computing. With a long history of creating innovative interaction designs and understanding human performance, we have contributed to the development of applications that serve the community. The HCIL is an interdisciplinary lab jointly operated by UMIACS and the College of Information Studies (iSchool), as well as comprised of faculty and students from Computer Science, Information Studies, Psychology, and other campus units. Our current work includes new approaches to information visualization, education, social computing, mobile devices, medical informatics and explores technology design methods with and for children.

Associated Faculty

Photo of Leilani Battle

Leilani Battle

Assistant Professor
Photo of Ben Bederson

Ben Bederson

Professor
Associate Provost of Learning Initiatives & Executive Director of Teaching and Learning Center
Photo of Evan Golub

Evan Golub

Senior Lecturer
Photo of Ming Lin

Ming Lin

Professor
Elizabeth Stevinson Iribe Chair of Computer Science
Photo of Michelle Mazurek

Michelle Mazurek

Assistant Professor
Photo of Atif Memon

Atif Memon

Professor
Photo of Ben Shneiderman

Ben Shneiderman

Professor Emeritus
Distinguished University Professor
Photo of Jon Froehlich

Jon Froehlich

Adjunct Associate Professor
Photo of Eun Kyoung Choe

Eun Kyoung Choe

Affiliate Assistant Professor
Photo of Niklas Elmqvist

Niklas Elmqvist

Affiliate Associate Professor
Photo of Leah Findlater

Leah Findlater

Affiliate Assistant Professor
Photo of Jennifer Golbeck

Jennifer Golbeck

Affiliate Associate Professor
Photo of Hernisa Kacorri

Hernisa Kacorri

Affiliate Assistant Professor
Photo of Doug Oard

Doug Oard

Affiliate Professor

Information Retrieval is an interdisciplinary area which corresponds to the process of finding relevant information units that satisfy an information need from a collection of information sources.  The data is usually text although the increasing use of the web as a data repository has led to the inclusion of multimedia data such as images, videos, and sound where exact matches are replaced by similarity searches. The main component of the retrieval is a search which is facilitated by imposing an index on the underlying data.  The growth of the web and the increasing popularity of smartphones and the embedding of GPS in these devices has led to the increasing importance of location as a component of all types of data and when coupled with this data is known as spatial data.  Database systems that deal with spatial data and its retrieval are known as Geographic Information Systems (GIS), and the department has been in the forefront of dealing with this type of data for over 50 years.

Associated Faculty

Photo of Jordan Boyd-Graber

Jordan Boyd-Graber

Associate Professor
Photo of Ramani Duraiswami

Ramani Duraiswami

Professor
Photo of Ming Lin

Ming Lin

Professor
Elizabeth Stevinson Iribe Chair of Computer Science
Photo of David Mount

David Mount

Professor
Associate Chair of Undergraduate Education
Photo of Hanan Samet

Hanan Samet

Professor
Distinguished University Professor
Photo of Leila De Floriani

Leila De Floriani

Affiliate Professor
Photo of Vanessa Frias-Martinez

Vanessa Frias-Martinez

Affiliate Assistant Professor
Photo of Richard Marciano

Richard Marciano

Affiliate Professor
Photo of Doug Oard

Doug Oard

Affiliate Professor

Data science is an emerging field encapsulating interdisciplinary activities used to create data-centric products, applications or programs, that address specific scientific, socio-political, or business questions. It is making deep inroads in industry, government, health, and journalism. Data Science incorporates practices from a variety of fields in computer science: Machine Learning, Statistics, Databases, Visualization, Natural Language Processing, Systems, Algorithms, and others. The University of Maryland Computer Science Department, and other partner departments on campus, have world-class expertise in these areas.

Associated Faculty

Photo of Ashok Agrawala

Ashok Agrawala

Professor
Photo of Leilani Battle

Leilani Battle

Assistant Professor
Photo of Jordan Boyd-Graber

Jordan Boyd-Graber

Associate Professor
Photo of Marine Carpuat

Marine Carpuat

Assistant Professor
Photo of Hector Corrada Bravo

Hector Corrada Bravo

Associate Professor
Photo of Hal Daumé III

Hal Daumé III

Professor
Photo of Amol Deshpande

Amol Deshpande

Professor
Photo of John Dickerson

John Dickerson

Assistant Professor
Photo of Soheil Feizi

Soheil Feizi

Assistant Professor
Photo of Tom Goldstein

Tom Goldstein

Assistant Professor
Photo of Mohammad Hajiaghayi

Mohammad Hajiaghayi

Professor
Jack and Rita G. Minker Professor
Photo of Furong Huang

Furong Huang

Assistant Professor
Photo of Ben Shneiderman

Ben Shneiderman

Professor Emeritus
Distinguished University Professor
Photo of Leila De Floriani

Leila De Floriani

Affiliate Professor
Photo of Naomi Feldman

Naomi Feldman

Affiliate Associate Professor
Photo of Vanessa Frias-Martinez

Vanessa Frias-Martinez

Affiliate Assistant Professor
Photo of Jennifer Golbeck

Jennifer Golbeck

Affiliate Associate Professor
Photo of Joseph Ja' Ja'

Joseph Ja' Ja'

Affiliate Professor
Photo of Hernisa Kacorri

Hernisa Kacorri

Affiliate Assistant Professor
Photo of Richard Marciano

Richard Marciano

Affiliate Professor
Photo of Louiqa Raschid

Louiqa Raschid

Affiliate Professor
Photo of Philip Resnik

Philip Resnik

Affiliate Professor

Natural Language Processing research aims to design algorithms and methods that enable computers to perform human language-related tasks, as well as to use computational methods to improve the scientific understanding of the human capacity for language. Areas of interest at UMD include deep learning, human-in-the-loop machine learning, multilingual text processing and machine translation, summarization, computational psycholinguistics, computational social science, and more. Natural Language Processing research at UMD is highly interdisciplinary, and builds on the intellectual diversity of the Computational Linguistics and Information Processing (CLIP) lab and the UMD Language Science Center.

Associated Faculty

Photo of Jordan Boyd-Graber

Jordan Boyd-Graber

Associate Professor
Photo of Marine Carpuat

Marine Carpuat

Assistant Professor
Photo of Hal Daumé III

Hal Daumé III

Professor
Photo of Naomi Feldman

Naomi Feldman

Affiliate Associate Professor
Photo of Hernisa Kacorri

Hernisa Kacorri

Affiliate Assistant Professor

Programming languages are our means of expressing computations. Thus, programming languages are a powerful locus of research toward building high-quality software, i.e., software that is flexible, secure, reliable, available, efficient, reusable, and more. We can design new languages, or we can build tools that analyze programs in existing languages, toward maximizing quality.

The Lab for Programming Languages and the University of Maryland (PLUM) is engaged in exciting research that aims to improve software quality through new languages and software tools. Our work involves formalism and proof (e.g., to show that a particular analysis establishes a certain property of the programs it considers) as well as implementation and evaluation (e.g., to show that our ideas work on real software at reasonable cost). Current interests focus on cloud computing, mobile computing, high-availability systems, static analysis, functional programming, debugging, and privacy-preseving computation.

Associated Faculty

Photo of Rance Cleaveland

Rance Cleaveland

Professor
Photo of Jeffrey Foster

Jeffrey Foster

Professor
Associate Chair for Graduate Education
Photo of Michael Hicks

Michael Hicks

Professor
Associate Chair of Undergraduate Education; Distinguished Scholar-Teacher
Photo of Atif Memon

Atif Memon

Professor
Photo of Adam Porter

Adam Porter

Professor
Fraunhofer Executive Director
Photo of David Van Horn

David Van Horn

Assistant Professor
Photo of Xiaodi Wu

Xiaodi Wu

Assistant Professor
Photo of Victor Basili

Victor Basili

Professor Emeritus
Research Professor
Photo of William Pugh

William Pugh

Professor Emeritus
Photo of Marvin Zelkowitz

Marvin Zelkowitz

Professor Emeritus
Photo of Arnab Ray

Arnab Ray

Adjunct Associate Professor
Senior Research Scientist, Fraunhofer Center for Experimental Software Engineering
Photo of Elaine  Shi

Elaine Shi

Adjunct Associate Professor
Photo of Rajeev Barua

Rajeev Barua

Affiliate Associate Professor

Quantum computing aims to exploit a quantum mechanical representation of information to enable new computers and new communication devices capable of performing tasks that would otherwise be infeasible. In particular, it studies the implications of quantum mechanics for computational complexity, cryptographic security, data transmission, and other aspects of information processing.

Quantum computers promise to address computational challenges with significant applications. For example, quantum simulation can efficiently determine properties of chemical systems and models of condensed matter physics, with potentially revolutionary impact on problems such as drug design and the development of new materials. Quantum computers also enable attacks on classically-secure cryptosystems, motivating the design of novel cryptographic primitives that are secure against quantum attacks. Furthermore, quantum information provides tools to study diverse topics including condensed matter physics, quantum gravity, and the foundations of quantum mechanics through the lens of information and computation.

Ongoing work also applies the principles of classical computer science to the design of quantum computers. Topics under investigation include the development of quantum algorithms, programming languages, compilers, and hardware architectures that offer robust, scalable advantages over classical devices.

Associated Faculty

Photo of Andrew Childs

Andrew Childs

Professor
Co-director, Joint Center for Quantum Information and Computer Science (QuICS)
Photo of Xiaodi Wu

Xiaodi Wu

Assistant Professor
Photo of Gorjan Alagic

Gorjan Alagic

Affiliate Assistant Professor

Computer Systems provides the foundation upon which all other software applications rely. The goal of systems research is to develop the key abstractions and services that enable software to be efficiently and portably run on hardware. Areas of interest to the systems group include operating systems, computer networks, parallel and distributed computation, and computer security. The systems group tackles problems from both theoretical and experimental approaches. To support our experimental work, the group maintains several laboratories in the Computer Science department and in UMIACS.

The Laboratory for Parallel and Distributed systems includes a collection of parallel computers and clusters to support systems research. Current equipment includes a 24 processor SPARC SMP, 8 processor IBM Power 4 system, and a 128 processor Myrinet-connected Linux cluster. The Distributed Systems Software Laboratory contains flexible networking environment to allow students to configure networking switches to allow for experimental research. In addition, the laboratory includes about 20 machines to support experiments.

The history of the systems group at Maryland dates back more than 30 years. One early member of the group, Yaohan Chu, wrote the book Computer Organization and Microprogramming which was the first major book on the subject. This book was used extensively at many universities and colleges. David Mills was an early researcher in computer networks. He set up an ARPANet IMP (predecessor of the current Internet) in his basement using a PDP 11/45 (an early mini-computer). At the time, this was the only full ARPANet node not located at a University or a Government facility. In the late 1970's, Chuck Rieger and Mark Weiser built ZMOB, an early parallel computer based on commodity microprocessors. The system consisted of 128 Z-80 processors.

Students and PostDocs from the systems group have gone on to faculty and industry positions around the world. Former graduate students in faculty positions include: Gagan Agrawal (Ohio State University), Suman Banerjee (University of Wisconsin), Ugur Cetintemel (Brown University), Ibrahim Matta (Boston University), Bongki Moon (University of Arizona), Ron Larsen (Dean of College of Information Science, University of Pittsburgh), Sang Son (University of Virginia), Dave Levin (University of Maryland), and Aaron Schulman (University of California San Diego).

Many of our former students have gone on to careers at major research labs including AT&T Labs (Vijay Gopalakrishnan, Seungjoon Lee), Google (Ruggero Morselli), and IBM T.J.Watson (Henrique Andrade, I-Hsin Chung, Andrzej Kochut, Kyung Ryu). The group also has a rich history of PostDoc researchers who have gone on to successful careers. For example, Anurag Acharya and Guy Edjlali are now at Google. The Systems group receives support from the Department of Defense, Department of Energy, NASA, and the National Science Foundation. Additional support is provided by industrial partners including DoCoMo, Fujitsu, IBM, Microsoft, Samsung, and Sun Microsystems.

Associated Faculty

Photo of Daniel Abadi

Daniel Abadi

Professor
Darnell-Kanal Professor of Computer Science
Photo of Ashok Agrawala

Ashok Agrawala

Professor
Photo of Michael Hicks

Michael Hicks

Professor
Associate Chair of Undergraduate Education; Distinguished Scholar-Teacher
Photo of Jeffrey K. Hollingsworth

Jeffrey K. Hollingsworth

Professor
Vice President & CIO, University of MD
Photo of Pete Keleher

Pete Keleher

Associate Professor
Photo of Dave Levin

Dave Levin

Assistant Professor
CS Honors Chair
Photo of Michelle Mazurek

Michelle Mazurek

Assistant Professor
Photo of A. Udaya Shankar

A. Udaya Shankar

Professor
Photo of Neil Spring

Neil Spring

Professor
Associate Chair of Facilities
Photo of Alan Sussman

Alan Sussman

Professor
Photo of Raymond Miller

Raymond Miller

Professor Emeritus
Photo of Michael Marsh

Michael Marsh

Visiting Research Scientist
Photo of Nirupam Roy

Nirupam Roy

Visiting Assistant Professor
Photo of Peter Druschel

Peter Druschel

Adjunct Professor
Photo of Anirudha (Anirud) Sahoo

Anirudha (Anirud) Sahoo

Adjunct Professor
Photo of Rajeev Barua

Rajeev Barua

Affiliate Associate Professor
Photo of Colin Dixon

Colin Dixon

Research Associate
Photo of Ray Chen

Ray Chen

Faculty Research Assistant
Photo of Sukhyun Song

Sukhyun Song

Research Associate