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Robotics
research labs.
Discover faculty research in robotics, autonomous systems, and human-robot interaction. Follow each profile to its official sources and selected work before deciding which groups to investigate further.
What to compare
Compare a group's emphasis on hardware, control, learning, or interaction. Check whether projects involve physical experiments, simulation, or both, and ask about access to equipment and expectations for new researchers.
Profiles appear here because their listed research keywords match this topic. Inclusion does not establish an open position. Check the official sources and any published application instructions before reaching out.
Prepare a research introduction ↗19 research-led lab profiles
Browse labs by their listed college affiliationAction Lab
Northeastern University, US
Dagmar Sternad · University Distinguished Professor
How do people learn to control their movements when the body and surrounding objects create complex dynamics? The Action Lab combines behavioral experiments with mathematical models of movement and nonlinear control. Researchers investigate single-joint and coordinated movements, manipulation tasks and locomotion, including experiments in virtual environments. Measurements of motion and force are complemented by muscle and brain electrical recordings. The work also studies older adults and people with neurological conditions such as Parkinson's disease, connecting movement coordination with questions about learning and impairment.
Independently curated · UnclaimedAlice E. Smith Research Group
The University of Alabama
Alice E. Smith · Endowed Shelby Distinguished Professor
Alice E. Smith's faculty-led research profile covers Advanced Manufacturing, Artificial Intelligence, Autonomous Vehicles, and Data Analytics.
Independently curated · UnclaimedAlvaro A. Cardenas Research Group
University of California, Santa Cruz
Alvaro A. Cardenas · Professor of Computer Science and Engineering
How can autonomous and cyber-physical systems detect and recover from real-world adversarial manipulations to sensors and actuators? The research group designs and evaluates attack detection and real-time recovery architectures for autonomous vehicles, drones, and robotic systems using physics-aware and common-sense reasoning in control loops. The researchers perform measurement studies and resilient-control designs for industrial control systems and the power grid, analyzing real-world ICS/SCADA attacks and proposing monitoring and resilient architectures. The lab develops ML- and AI-based methods for automated cybersecurity tasks including anomaly detection, alert fusion, and incident response for critical infrastructures. The group prototypes and evaluates defenses in platforms ranging from consumer drones to large-scale power-grid measurement datasets.
Independently curated · UnclaimedBineet Ghosh Research Group
The University of AlabamaBineet Ghosh · Assistant Professor
Bineet Ghosh's faculty-led research profile covers Artificial Intelligence, Autonomous Vehicles, Deep Learning, and Embedded Systems.
Independently curated · UnclaimedCollaborative Haptics and Robotics in Medicine (CHARM) Lab
Stanford University
Allison M. Okamura · Richard W. Weiland Professor of Engineering; Professor of Mechanical Engineering
How can a robot communicate through touch? Allison Okamura’s CHARM Lab designs the devices, models, and control methods that make physical interaction useful in robotics and medicine. Its projects connect wearable haptic garments, surgical teleoperation, soft robots, and training environments. Haptiknit explores knitted structures with distributed stiffness for wearable feedback; loop-closure grasping investigates how a robot can hold objects strongly and gently. Researchers combine mechanical design, fabrication, control, and studies of human interaction to understand both what a device does and how a person experiences it.
Independently curated · UnclaimedGeorge Konidaris Research Group
Brown University
George Konidaris · Professor of Computer Science
Can robots autonomously learn abstract skills that enable fast, goal-directed planning across diverse tasks and environments? The Intelligent Robot Lab constructs high-level symbolic representations and abstraction hierarchies to enable planning, for example work on "From Skills to Symbols" and related projects. The lab develops hierarchical reinforcement learning and probabilistic learning methods to learn task-level skills and then composes them for long-horizon planning using projects such as "Autonomous Robot Skill Acquisition." Researchers integrate optimal control, planning, and learned skills to produce robust behavior under uncertainty in manipulation and navigation. The lab builds applied systems including robot motion-planning hardware and software prototypes described as "Robot Motion Planning on a Chip.
Independently curated · UnclaimedHuman And Robot Partners (HARP) Lab
Carnegie Mellon University
Henny Admoni · Associate Professor, Robotics Institute
A helpful robot needs to understand the person beside it. Henny Admoni’s HARP Lab studies how robots infer human intentions, learn from human teachers, and collaborate in everyday tasks. Its projects investigate robots that ask for help when uncertain, models of what a human teacher believes, and shared control that blends human input with robot actions. Assistive robotics provides a practical setting for these questions, including interfaces for people with motor impairments. Selected publications examine transparent robot policies and the feedback preferences of power-wheelchair users controlling a robotic arm.
Independently curated · UnclaimedHuman-Technology Interaction Lab (HTIL)
The University of AlabamaChris S. Crawford · Associate Professor
The Human-Technology Interaction Lab (HTIL), led by Dr. Chris S. Crawford at The University of Alabama, studies brain-computer interfaces and human-robot interaction. The team combines neurophysiological sensing, software engineering, and robotics to explore how technology can respond to a person’s cognitive state. Projects include Brains and Blocks for creating neurofeedback applications, brain-controlled drone racing, EEG signal processing with bci.js, and NeuroBrush for interactive art. Collaborative research also explores RF sensing for sign language recognition. Computing education connects this work with hands-on learning about physiological interfaces.
Independently curated · UnclaimedLeonard Lab
Princeton UniversityNaomi Ehrich Leonard · Edwin S. Wilsey Professor of Mechanical and Aerospace Engineering; Department Chair
How do many individuals coordinate without a single leader? Naomi Ehrich Leonard’s lab studies the dynamics, control, and learning behind networked systems, from robot teams to collective animal behavior. Projects include decentralized robot task allocation, nonlinear models of opinion formation, and learning three-dimensional rotational dynamics from images. The work combines mathematical models, feedback control, and computational experiments to explain how local interactions produce group-level behavior. Its selected papers offer two entry points: predicting rigid-body motion with physics-based learning, and tuning how a network reaches agreement or maintains disagreement.
Independently curated · UnclaimedMonica Anderson Research Group
The University of AlabamaMonica Anderson · Associate Professor & Associate Department Head for Undergraduate Studies
Monica Anderson's faculty-led research profile covers Artificial Intelligence, Computer Science Education, Engineering Education and Pedagogy, and Robotics.
Independently curated · UnclaimedNoorbakhsh Amiri Golilarz Research Group
The University of AlabamaNoorbakhsh Amiri Golilarz · Assistant Professor
Noorbakhsh Amiri Golilarz's faculty-led research profile covers Artificial Intelligence, Computer Vision, Data Analytics, and Deep Learning.
Renato Mancuso Research Group
Boston University
Renato Mancuso · Associate Professor
How can embedded systems guarantee predictable timing for safety-critical control in hybrid CPU+FPGA platforms? The Cyber-Physical Systems Lab develops software/hardware techniques for fine-grained performance profiling and management to achieve controllable timeliness in accelerator-enabled embedded systems. Researchers design real-time virtualization and hypervisor technologies to provide spatio-temporal isolation and workload-aware tuning for high-performance cyber-physical applications. The group builds workload profiling tools to capture interactions between applications, processors, and memory resources for informed resource management. Projects explore neural-network-driven flight control and deployable NN-based controllers with emphasis on safety assessment and system deployability.
Independently curated · UnclaimedSilvia Ferrari Research Group
Cornell University
Silvia Ferrari · John Brancaccio Professor of Mechanical and Aerospace Engineering
How can information-driven planning improve decision-making for sensing and control in distributed autonomous systems? The Laboratory for Intelligent Systems and Control (LISC) develops algorithms for information-driven path planning and control, active perception, and sensorimotor learning. Researchers formulate and apply adaptive dynamic programming, reinforcement learning, and nonparametric Bayesian models for target tracking and distributed sensor-network control. Projects include scalable learning algorithms for spiking neuronal networks and value-function approximation methods for multiscale dynamical systems.
Stefanos Nikolaidis Research Group
University of Southern California
Stefanos Nikolaidis · Fluor Early Career Chair in Engineering and Associate Professor of Computer Science
How can robots behave robustly when interacting with people in unconstrained everyday environments? The ICAROS lab develops computational human-robot interaction algorithms and end-to-end robotic systems to assist users in complex, real-world tasks. The group builds automatic scenario generation methods to create diverse, realistic test scenarios that improve robotic robustness and evaluation. Researchers combine procedural content generation and quality diversity optimization with experimental deployments to enable robots to adapt through simulated and real-world experiences. The lab investigates end-to-end solutions that enable deployed robotic systems to act robustly when interacting with people in practical applications.
Independently curated · UnclaimedSudip Mittal Research Group
The University of AlabamaSudip Mittal · Associate Professor
Sudip Mittal's faculty-led research profile covers Artificial Intelligence, Cyber Security, Data Analytics, and Digital Twins.
Independently curated · UnclaimedTITANS Lab
The University of AlabamaMahmoud Mahmoud · Associate Professor
TITANS Lab advances trustworthy and adversarially robust AI for autonomous systems, cyber-physical infrastructure, and safety-sensitive decision environments.
Yu Sun Research Group
University of South FloridaYu Sun · Professor
Yu Sun’s research brings together robotics, deep learning, computer vision, haptics, and human-computer interaction. His work in robotic hands, grasping, and manipulation examines how robots can handle objects and carry out useful tasks, while medical applications connect intelligent systems with human needs. He also directs USF’s Center for Innovation, Technology, and Aging. The program links perception, physical interaction, and AI rather than treating them as separate problems, offering a research setting at the intersection of robotic capability, interactive technology, and applications involving people.
Independently curated · UnclaimedYuqi Zhou Research Group
The University of AlabamaYuqi Zhou · Assistant Professor
Yuqi Zhou's faculty-led research profile covers Distributed Systems, Human-Computer Interaction, Robotics, and Wearable Technologies.
Independently curated · UnclaimedZhi-Li Zhang Research Group
University of Minnesota
Zhi-Li Zhang · Professor, Qwest Land Grant Chair in Telecommunications
How can next-generation networks and AI be combined to support resilient, application-aware services like autonomous driving? The Computer Networking, Mobile, and AI Research Lab builds service-oriented, application-aware, scalable and secure 5G/NextG networked systems. The group develops AI/ML algorithms to enable intelligent software-defined networking, edge/cloud systems and Digital Twins. Researchers design and experimentally evaluate architectures for collaborative autonomous driving, metaverse applications, and IoT with cross-layer performance and security considerations. Work combines formal modeling, analysis, implementation, and real-world evaluation to measure and optimize networked system behavior.
Showing 1–19 of 19 labs