The Department of Computer Science has many research groups and labs.The Department of Computer Science has many research groups and labs.

Groups & Labs

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AquaLab - Research in Distributed Computing

The AquaLab conducts research on large-scale distributed systems and networking. Its approach is mainly experimental, focusing on the design, deployment, and evaluation of systems that people use. This lab is headed by Fabián Bustamante.

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Assistive and Rehabilitation Robotics Laboratory

The Assistive and Rehabilitation Robotics Laboratory strives to advance human ability through robotics autonomy by easing the burden of controlling assistive machines. This lab is headed by Brenna Argall.

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Campanoni Lab

Research focuses on code compilation challenges for both energy efficiency and performance on commodity processors. These challenges are addressed by co-designing compilers, the computer architecture of the platform they target and programming languages. This lab is headed by Simone Campanoni.

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Center for Connected Learning and Computer-Based Modeling

Northwestern's Center for Connected Learning and Computer-Based Modeling is dedicated to the creative use of technology to deepen learning. This center is headed by Uri Wilensky.

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Delta Lab

The Delta Lab is an interdisciplinary research lab and design studio at Northwestern University. Its driving mission is to improve the way we design, work, learn, play, and fundamentally change the way we interact. This lab is headed by Haoqi Zhang.

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IDEAS - Design Automation of Intelligent Systems

IDEAS Lab aims to develop innovative design automation methodologies and algorithms for software synthesis of cyber-physical systems (CPS), which have applications in key sectors such as automotive, aerospace, healthcare, and industrial automation.

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Interactive Audio Lab

The Interactive Audio Lab applies machine learning, signal processing, natural language processing, and database search techniques to make new auditory tools and interfaces. This lab is headed by Bryan Pardo.

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Ka Moamoa – Mobile and Ubiquitous Computing Lab

Research at Ka Moamoa  explores energy efficient and mobile computing devices, like wearables, implantables, and energy harvesting sensors,  in the context of global scale applications ranging from healthcare to environmental engineering.

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Northwestern Lab for Internet and Security Technology

The Northwestern Lab for Internet and Security Technology works to improve the reliability, agility, and security of the current Internet, including wireless networks. This lab is headed by Yan Chen.

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Northwestern Networks Group

The Northwestern Networks Group conducts research on computer networking. This lab is headed by Aleksandar Kuzmanovic.

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NuLogiCS Group

Human intelligence lies on the capability of thinking. With the development of the programmable computer, slow thinking has found its solid foundation on computation. With the recent progress of machine learning, especially deep learning, fast thinking is discovering its root on learning. Logics is the foundation of both computation and learning. NuLogiCS group's goal is to build the new logic foundation for Artificial Intelligence (which needs a tight integration between computation and learning), and for Security (which needs a tight integration between cryptography and formal verification).

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Parallel Architecture Group at Northwestern

The overreaching research umbrella at the Parallel Architecture Lab at Northwestern is energy-efficient computing. This lab is headed by Nikos Hardavellas.

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Prescience Lab

The Prescience Lab conducts a range of experimental computer systems research with a current focus on virtualization, empathic systems, and parallel and distributed systems. This lab is headed by Peter Dinda.

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Qualitative Reasoning Group

The research of this group includes efforts to both create new kinds of cognitive systems and model human cognition. It has strong collaborations with other cognitive scientists in a number of fields at various institutions. This group is headed by Kenneth D. Forbus and Tom Hinrichs.

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Swarm Robotics Lab

Research interests interests include advancing the control and design of multi-robot systems, enabling their use instead of traditional single robots and to solve problems for which traditional robots are not suitable. Using these multi-robot systems can offer more parallelism, adaptability, and fault tolerance when compared to a traditional single robot. The lab is interested in investigating how new technologies will allow for more capable multi-robot systems and how these technologies impact the design of multi-robot algorithms, especially as these systems begin to number in the hundreds, thousands, or even millions of robots. This lab is headed by Michael Rubenstein.

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Tangible Interaction Design and Learning (TIDAL) Lab

TIDAL Lab is a team of designers, artists, learning scientists, and computer scientists at Northwestern University. Its research creates and studies innovative technology-based learning experiences. This lab is headed by Michael Horn.

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Northwestern CS Theory Group

Theoretical computer science looks at fundamental questions about computation by creating formal models of computation and understanding the resources needed to solve general and specific algorithmic questions.  TCS studies the design of efficient algorithms and understanding the computational complexity of various computational tasks that arise in computer science, statistics, economics and the other sciences.

The major research areas include design and analysis of algorithms, computational complexity, randomness in computation, combinatorial optimization, approximation algorithms, online algorithms. The theory group at Northwestern also has strong interests in using computation as a fundamentally new lens to study other fundamental sciences, leading to areas of algorithmic game theory, machine learning and bioinformatics.

VLSI Research Lab

The VLSI Research Lab at NU focuses on the areas of energy efficient computing with digital and mixed signal design approaches. We are dedicating our effort to explore new computing method for many emerging applications including energy efficient edge computing, accelerator designs for artificial intelligence, etc.

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