About

Noah Cowan is a professor in the Department of Mechanical Engineering at Johns Hopkins University. His research focuses on mechanics and control in animals and machines, specifically the neuromechanics of motion, which lies at the intersection of neuroscience and engineering. Cowan's innovations in robotics and discoveries in neuroscience are advancing both fields and may impact neuroprosthetics development and physical rehabilitation. He founded and directs the Locomotion in Mechanical and Biological Systems (LIMBS) Laboratory, which studies neuromechanics, locomotion, control theory, system identification, and robotics, working across disciplinary boundaries with collaborators to understand how the brain navigates and controls the body with precision and grace. Cowan's team uses exotic creatures such as electric knife fish to develop algorithms and robotic devices inspired by animal locomotion.

Research topics

• Artificial Intelligence
• Computer Science
• Engineering
• Psychology
• Neuroscience
• Biology
• Control engineering
• Physics
• Polymer chemistry
• Cognitive science
• Materials science
• Biological system
• Biophysics
• Physical medicine and rehabilitation
• Nanotechnology
• Medicine
• Software engineering
• Chemistry
• Composite material
• Structural engineering
• Thermodynamics

Selected publications

• Bio-Inspired Event-Based Visual Servoing for Ground Robots

  arXiv (Cornell University) · 2026-03-24

  preprintOpen access

  Biological sensory systems are inherently adaptive, filtering out constant stimuli and prioritizing relative changes, likely enhancing computational and metabolic efficiency. Inspired by active sensing behaviors across a wide range of animals, this paper introduces a principled 1D event-based visual servoing framework for ground robots operating in structured environments. Utilizing a Dynamic Vision Sensor (DVS), we demonstrate that by applying a fixed spatial kernel to the asynchronous event stream generated from structured logarithmic intensity-change patterns, the resulting net event flux analytically isolates specific combinations of kinematic states. We establish a generalized theoretical bound for this event rate estimator and show that linear and quadratic spatial profiles isolate the robot's velocity and position-velocity product, respectively. Leveraging these properties, we employ a multi-pattern stimulus to directly synthesize a nonlinear state feedback term entirely without traditional state estimation. To overcome the inescapable loss of linear observability at equilibrium inherent in event sensing, we propose a bio-inspired active sensing limit-cycle controller. Experimental validation on a 1/10-scale autonomous ground vehicle confirms the efficacy, extreme low-latency, and computational efficiency of the proposed direct-sensing approach.

  PublisherDOI

• Simultaneous path-integration recalibration in head direction and place cells

  Current Biology · 2026-03-17

  articleOpen accessSenior author

  Accurate spatial navigation relies on path integration, a process of tracking one's location by integrating self-motion cues. Path integration uses a gain factor relating self-motion signals to displacement on the cognitive map. This gain is plastic, recalibrating rapidly to match perceived displacements relative to external cues. To elucidate the mechanism of recalibration, we simultaneously recorded from place cells, which instantiate the cognitive map, and head direction (HD) cells, thought to orient the map. Persistent conflict between self-motion and visual feedback induced functionally identical recalibration of path-integration gain in the two neural populations during forward locomotion; however, during locomotor immobility accompanied by head scanning, HD cells did not exhibit recalibration. Moreover, the two populations manifested differential field-shifting dynamics relative to landmarks during recalibration. These results uncover a tightly coordinated yet behavior-dependent recalibration process across the navigation circuit that achieves robust yet flexible coupling of the internal sense of position and direction.

  PublisherDOI

• Bio-Inspired Event-Based Visual Servoing for Ground Robots

  ArXiv.org · 2026-03-24

  articleOpen access

  Biological sensory systems are inherently adaptive, filtering out constant stimuli and prioritizing relative changes, likely enhancing computational and metabolic efficiency. Inspired by active sensing behaviors across a wide range of animals, this paper introduces a principled 1D event-based visual servoing framework for ground robots operating in structured environments. Utilizing a Dynamic Vision Sensor (DVS), we demonstrate that by applying a fixed spatial kernel to the asynchronous event stream generated from structured logarithmic intensity-change patterns, the resulting net event flux analytically isolates specific combinations of kinematic states. We establish a generalized theoretical bound for this event rate estimator and show that linear and quadratic spatial profiles isolate the robot's velocity and position-velocity product, respectively. Leveraging these properties, we employ a multi-pattern stimulus to directly synthesize a nonlinear state feedback term entirely without traditional state estimation. To overcome the inescapable loss of linear observability at equilibrium inherent in event sensing, we propose a bio-inspired active sensing limit-cycle controller. Experimental validation on a 1/10-scale autonomous ground vehicle confirms the efficacy, extreme low-latency, and computational efficiency of the proposed direct-sensing approach.

  PublisherOA PDF

• A multi-muscular, redundant strategy for free-flight roll stability

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-10-01

  preprintOpen access

  Abstract Whether recovering after a gust of wind, or rapidly saccading away from an oncoming predator, fruit flies show remarkable aerial dexterity about their body roll axis. Here, we investigated the detailed wing kinematic changes during free-flight roll motion and probed the neuromuscular basis for such changes. Consistent with previous work, we observed that flies manipulated the stroke amplitude difference between their wings to control their roll angle. Here, we show that flies are capable of achieving such changes by altering the stroke amplitude of either or both of their wings. Further we found that during corrections flies can also take advantage of an aerodynamically significant change in the angle of attack of their uppermost wing. Curiously, these corrective wing changes cannot be eliminated when motor neurons hypothesized to be used during roll maneuvers (i1, i2, b1, b2, and b3) are individually inhibited. However, free-flight optogenetic manipulations and quasi-steady aerodynamic calculations show that each of these motor neurons individually can effect kinematic changes consistent with a roll correction. Combining this evidence with an analysis of haltere inputs found in the BANC connectome, we propose that the observed robustness could be the result of two sets of muscular redundancies that receive shared inputs from haltere sensory afferents: one set, containing b1 and b2, is able to increase the stroke amplitude of the lower wing; while the other set, containing i1, i2, and b3, is able to decrease the stroke amplitude and wing pitch angle of the upper wing. Because of the redundancy in the input sensory information and output wing motion in the muscles in each cluster, the fly is able to perform roll stability maneuvers even when one of the constituent motor neurons is inhibited. This framework proposes new ways fast aerial maneuverability can be implemented when dealing with the fly’s most unstable rotational degree of freedom.

  PublisherOA PDFDOI

• Synchronized path-integration recalibration but distinct landmark-control dynamics in head direction and CA1 place cells

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-10-10 · 2 citations

  preprintOpen accessSenior author

  Accurate spatial navigation relies on path integration, a process of tracking one's location by integrating self-motion cues. Path integration uses a gain factor relating self-motion signals to displacement on the cognitive map. This gain is plastic, recalibrating rapidly to match perceived displacements relative to external cues. To elucidate the mechanism of recalibration, we simultaneously recorded from place cells, which instantiate the cognitive map, and head direction (HD) cells, thought to orient the map. Persistent conflict between self-motion and visual feedback induced functionally identical recalibration of path-integration gain in the two neural populations during forward locomotion; however, during locomotor immobility accompanied by head-scanning, HD cells did not exhibit recalibration. Moreover, the two populations manifested differential field-shifting dynamics relative to landmarks during recalibration. These results uncover a tightly coordinated yet behavior-dependent recalibration process across the navigation circuit that achieves a robust yet flexible coupling of the internal sense of position and direction.

  PublisherOA PDFDOI

• Resourcefulness, Robustness, and Recovery: Tail Use during Climbing in Rats

  Integrative and Comparative Biology · 2025-06-18

  articleOpen accessSenior author

  Tails serve diverse evolutionary functions across species, but their mechanical role during complex climbing maneuvers remains understudied. We investigated how Long-Evans rats (Rattus norvegicus) use their tails when climbing up and over a ledge with a climbing bar positioned 23-32 cm above a bottom platform. Using force measurements and motion tracking, we quantified tail-generated impulse during climbing and found that tail usage followed an inverse relationship between the impulse they imparted to the bottom platform and the usage of their tail: a higher initial jumping impulse required less assistance from the tail, while a lower initial momentum required a greater compensatory force from the tail. When climbing from greater depths (up to 32 cm), rats maintained consistent jumping impulse but significantly increased tail usage, suggesting a preference for a reliable strategy with mid-climb adjustments rather than pre-calibrated jumping force. Rats demonstrated one-shot learning when the forelimb torque was eliminated by covertly unlocking the climbing bar. After a single near-failure, they shifted from a dynamic, ballistic climbing style to a more controlled, quasistatic approach. This new method involved increased tail usage and adjusted body positioning to reduce gravitational moments. These findings reveal that rats employ their tails as actively controlled limbs that contribute substantial forces during complex maneuvers, adapting usage based on initial conditions and mechanical constraints.

  PublisherOA PDFDOI

• Teleoperator Coupling Dynamics Impact Human Motor Control Across Pursuit Tracking Speeds

  IEEE Transactions on Haptics · 2025-01-01

  article

  Robotic teleoperators introduce novel electromechanical dynamics between the user and the environment. While considerable effort has focused on minimizing these dynamics, we lack a robust understanding of their impact on user task performance across the range of human motor control ability. Here, we utilize a 1-DoF teleoperator testbed with interchangeable mechanical and electromechanical couplings between the leader and follower to investigate to what extent, if any, the dynamics of the teleoperator influence performance in a visual-motor pursuit tracking task. We recruited N = 30 participants to perform the task at frequencies ranging from 0.55-2.35 Hz, with the testbed configured into Mechanical, Unilateral, and Bilateral configurations. Results demonstrate that tracking performance at the follower was similar across configurations. However, participants' adjustment at the leader differed between Mechanical, Unilateral, and Bilateral configurations. In addition, participants applied different grip forces between the Mechanical and Unilateral configurations. Finally, participants' ability to compensate for coupling dynamics diminished significantly as execution speed increased. Overall, these findings support the argument that humans are capable of incorporating teleoperator dynamics into their motor control scheme and producing compensatory control strategies to account for these dynamics; however, this compensation is significantly affected by the leader-follower coupling dynamics and the speed of task execution.

  PublisherDOI

• Feedback and feedforward control are differentially delayed in cerebellar ataxia

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-02-10 · 4 citations

  preprintOpen accessSenior author

  Damage to the cerebellum can cause ataxia, a condition associated with impaired movement coordination. Typically, coordinated movement relies on a combination of anticipatory mechanisms (specifically, feedforward control) and corrective mechanisms (embodied by feedback control). Here, we show that in 3D reaching in VR, ataxia preserves the visuomotor feedforward and feedback control structure compared to the control group. However, the ataxia group exhibits a small increase in feedback delay (~ 20 ms) and a substantial increase in feedforward delay (~ 70 ms) together with a reduced feedback gain (~ 25% lower). Our results suggest that the feedforward and feedback pathways remain largely intact in ataxia, but that time delay deficits and temoral discoordination amongst these control pathways may contribute to the disorder. We also find that providing a preview-analogous to driving on a clear night and seeing the road ahead vs. driving in the fog-improves tracking performance in the ataxia group, although the control group was significantly better able to exploit this preview information. Overall, our results indicate that the feedforward control and preview utilization are relatively well-preserved in individuals with cerebellar ataxia, and that preview could potentially be leveraged to enhance the feedforward performance of those with ataxia.

  PublisherDOI

• Multisensory integration for active mechanosensation in <i>Drosophila</i> flight

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-06-24

  preprintOpen access

  and a multisensory behavioral apparatus simulating forward flight to determine how visual and mechanosensory information are integrated and control active movements of an important multimodal sensory organ, the antennae. We found that flies perform active antennal movements in response to varying airflow, and that the direction of these movements changes depending on the visual environment. Next, we found that antennal movements are amplified in the presence of visual motion, but only when the fly was flying. Through mechanical and optogenetic manipulation of mechanosensory input, we found that mechanosensory feedback is vital to antennal positioning at flight onset. Additionally, we observed unexpected changes in wingbeat frequency when the antenna was mechanically stabilized, suggesting that multiple antennal mechanosensors contribute to flight regulation. Finally, we show that integration of mechanosensory and visual cues for controlling antennal motion follows in a "winner-takes-all" paradigm dependent on the stimulus frequency, mirroring visuo-mechanosensory guided behaviors in other species. Together, these results reveal novel behavioral gating of sensory information and expand our understanding of the efferent control of active sensing.

  PublisherOA PDFDOI

• Allothetic and idiothetic spatial cues control the multiplexed theta phase coding of place cells

  Nature Neuroscience · 2025-08-26 · 3 citations

  articleOpen access
  PublisherOA PDFDOI

Recent grants

• A Control Theoretic Approach to Addressing Hippocampal Function

  NIH · $3.6M · 2017–2028

• ASM: Multi-Sensory Control of Tracking Behavior in Weakly Electric Fish

  NSF · $504k · 2006–2009

• Active Cannulas for Bio-Sensing and Surgery

  NSF · $243k · 2007–2011

• A Control Theoretic Approach to Addressing Hippocampal Function

  NIH · $446k · 2015–2017

• NIH Grant R01EB006435

  NIH · $1.8M · 2012

Frequent coauthors

• Eric S. Fortune

  New Jersey Institute of Technology

  36 shared

• Manu S. Madhav

  Johns Hopkins University

  34 shared

• James Knierim

  Johns Hopkins University

  24 shared

• Sarah A. Stamper

  Johns Hopkins University

  21 shared

• Mustafa Mert Ankaralı

  Middle East Technical University

  19 shared

• İsmail Uyanık

  Hacettepe University

  16 shared

• Ravikrishnan P. Jayakumar

  Johns Hopkins University

  13 shared

• Allison M. Okamura

  12 shared

Labs

• LIMBS LabPI

Awards & honors

• Presidential Early Career Award for Scientists and Engineers…
• James S. McDonnell Foundation Scholar Award in Complex Syste…
• National Science Foundation CAREER Award (2009)
• Discovery Awards (2015, 2016, 2023)
• William H. Huggins Award for Excellence in Teaching (2004)