Dagmar Sternad

About

Dagmar Sternad is a University Distinguished Professor at Northeastern University, with appointments in the departments of Biology and Electrical and Computer Engineering, and affiliated roles in Bioengineering and Physics. Her research centers on computational motor neuroscience, human movement control and learning, human-robot interaction, and clinical applications. She investigates the learning and control of sensorimotor coordination in humans, including both healthy individuals and those with neurological impairments. Her work integrates behavioral experiments with mathematical models of control and nonlinear dynamics, bridging biology, engineering, and physics. At the core of her research is the Action Lab, which focuses on understanding the control and coordination of goal-directed human behavior through a systems-level approach. This involves revealing the organizational principles of the nervous system in interaction with the mechanical system of the body and environment. Her experimental work examines single- and multi-joint movements, upper limb manipulation, and locomotion, including studies involving virtual environments and populations such as the elderly and patients with neurological disorders like Parkinson's disease. Her contributions have been recognized through numerous awards and continuous research support from agencies such as the NIH, NSF, and Office of Naval Research.

Research topics

• Computer Science
• Artificial Intelligence
• Human–computer interaction
• Engineering
• Psychology
• Cognitive psychology
• Cognitive science
• Simulation
• Neuroscience
• Mathematics

Selected publications

• Neural Encoding and Representation of Time for Sensorimotor Control and Learning

  Journal of Neuroscience · 2020 · 68 citations

  The ability to perceive and produce movements in the real world with precise timing is critical for survival in animals, including humans. However, research on sensorimotor timing has rarely considered the tight interrelation between perception, action, and cognition. In this review, we present new evidence from behavioral, computational, and neural studies in humans and nonhuman primates, suggesting a pivotal link between sensorimotor control and temporal processing, as well as describing new t…

  DOI

• Preparing to move: Setting initial conditions to simplify interactions with complex objects

  PLoS Computational Biology · 2021 · 28 citations

  Senior authorCorresponding

  Humans dexterously interact with a variety of objects, including those with complex internal dynamics. Even in the simple action of carrying a cup of coffee, the hand not only applies a force to the cup, but also indirectly to the liquid, which elicits complex reaction forces back on the hand. Due to underactuation and nonlinearity, the object's dynamic response to an action sensitively depends on its initial state and can display unpredictable, even chaotic behavior. With the overarching hypoth…

  DOI

• Predictive strategies for the control of complex motor skills: recent insights into individual and joint actions

  Current Opinion in Behavioral Sciences · 2025-04-04 · 6 citations

  preprintOpen access

  Humans perform exquisite sensorimotor skills, both individually and in teams, from athletes performing rhythmic gymnastics to everyday tasks like carrying a cup of coffee. The ‘predictive brain’ framework suggests that mastering these skills relies on predictive mechanisms, raising the question of how we deploy predictions for real-time control and coordination. This review highlights two research lines, showing that during the control of complex objects, people make the interaction with ‘tools’…

  PublisherDOI

• Time-warping analysis for biological signals: methodology and application

  Scientific Reports · 2025-04-05 · 5 citations

  articleOpen accessSenior author

  Any set of biological signals has variability, both in the temporal and spatial domains. To extract characteristic features of the ensemble, these spatiotemporal profiles are typically summarized by their mean and variance, often requiring prior padding or resampling of the data to equalize signal length. Such compression can conceal essential information in the signal. This work presents the method of time-warping, reformulated as elastic functional data analysis (EFDA), in an accessible way. T…

  PublisherOA PDFDOI

• Simplified internal models in human control of complex objects

  PLoS Computational Biology · 2024-11-18 · 5 citations

  articleOpen accessSenior authorCorresponding

  Humans are skillful at manipulating objects that possess nonlinear underactuated dynamics, such as clothes or containers filled with liquids. Several studies suggested that humans implement a predictive model-based strategy to control such objects. However, these studies only considered unconstrained reaching without any object involved or, at most, linear mass-spring systems with relatively simple dynamics. It is not clear what internal model humans develop of more complex objects, and what lev…

  PublisherDOI

Recent grants

• NRI: Collaborative Research: Towards Robots with Human Dexterity

  NSF · $500k · 2017–2020

• Dynamics of Action and Perception in a Rhythmic Task

  NSF · $284k · 2005–2008

• Predictability in Complex Object Control

  NIH · $1.8M · 2015–2022

Frequent coauthors

• Salah Bazzi

  Northeastern University

  101 shared

• Reza Sharif Razavian

  Center for the Neural Basis of Cognition

  94 shared

• Mohsen Sadeghi

  Northern Arizona University

  94 shared

• Aaron P. Batista

  Center for the Neural Basis of Cognition

  92 shared

• Raeed H. Chowdhury

  Center for the Neural Basis of Cognition

  92 shared

• Patrick J. Loughlin

  University of Pittsburgh

  92 shared

• Neville Hogan

  Massachusetts Institute of Technology

  47 shared

• Marta Russo

  Northeastern University

  29 shared

Labs

• Action LabPI

Education

• PhD, Psychology

  University of Connecticut

  1995

Awards & honors

• 2021-22 Fulbright Award to research “Variability and Redunda…
• Klein Lectureship Award Distinguished Lecturer on Life and t…
• 2025 Stanford University Annual Assessment of Author Citatio…
• 2024 Stanford University Annual Assessment of Author Citatio…
• 2023 Stanford University Annual Assessment of Author Citatio…

Similar researchers at Northeastern University

• Herbert Levineh-119
• Raimond Winslowh-72
• Neel Joshih-60