About

Jeffrey Ian Lipton is an assistant professor in Mechanical and Industrial Engineering at Northeastern University. His research focuses on robotics, 3D printing, and mechanical metamaterials with applications in manufacturing. He has previously served as an assistant professor at the University of Washington in the Mechanical Engineering Department and was a founding Director of the Center for Digital Fabrication. Lipton's academic background includes a BS in Applied and Engineering Physics and a PhD in Mechanical Engineering from Cornell University, where his doctoral work was conducted under Hod Lipson in the Creative Machines Lab. His work has influenced the development of 3D printing technologies, including 3D printed foods and applications for the hospitality industry, which have garnered media attention from outlets such as the New York Times and BBC. He was also the lead developer for the Fab@Home project, supporting 3D printing research across all habitable continents. Lipton's research has led to innovations such as deployable structures for artificial gravity space habitats and hybrid soft and hard robotics capable of tasks like screwing in a lightbulb. His contributions have been recognized through selection among the top 2% of most-cited scientists worldwide by Stanford University and awards like the Grand Prize at the MassRobotics Competition.

Research topics

• Computer Science
• Artificial Intelligence
• Engineering
• Mechanical engineering
• Materials science
• Political Science
• Machine Learning
• Physics
• Computer vision
• Control engineering
• Electrical engineering
• Philosophy
• Structural engineering
• Optics
• Composite material
• Law
• Linguistics
• Nanotechnology

Selected publications

• Torsion Resistant Strain Limiting Layers Enable High Grip Strength of Electrically-Driven Handed Shearing Auxetic Grippers

  2026-04-07

  preprintOpen access

  Soft grippers made from handed shearing auxetics (HSAs) have demonstrated a strong ability to successfully pick and manipulate many objects. A key limitation to their wider adoption is their inability to grasp larger payloads due to objects slipping out of grasps. We have overcome this limitation by integrating a torsion resistant strain limiting layer (TRSLL) with Handed Shearing Auxetics. This reduces out-of-plane bending while maintaining the gripper’s softness and in-plane flexibility. We characterized the design space of the strain limiting layer and HSA actuators for a soft gripper through simulation and experimentation. The inclusion of the TR-SLL with HSAs enables HSA grippers to be made with a single digit. We found that the use of our TR-SLL HSA gripper enabled pinch grasping of payloads over 1 kg. We demonstrate a lifting capacity of 5 kg when loading an HSA using the TR-SLL. We also demonstrate a peak pinch grasp force of 5.8 N and a peak planar caging force of 14.5 N. Finally, we test the TR-SLL gripper on a suite of 43 YCB objects. We show success on 37 objects demonstrating significant capabilities.

  PublisherOA PDFDOI

• Large-Expansion Bi-Layer Auxetics Create Compliant Cellular Motion

  2025-05-19

  article

  There is significant interest in creating compliant modular robots that can change their volume. Inspired by how biological cells move, these systems can potentially combine the resilience of modular robotics with the increased environmental interactions of soft robotics. However, current versions have limited speed, expansion, and portability. In this paper, we address these concerns through AuxSwarm, a compliant system composed of auxetic-based robotic voxels. These voxels control their volume through a scissor-like bi-layer auxetic design, growing up to 1.57 times their original size in 0.2 seconds. This combination of speed and expansion is unique across modular soft robots, enabling dynamic locomotion capabilities. We characterize the voxels and demonstrate the versatility of this approach through case studies of 2D bending and 3D cube flipping. AuxSwarm provides a first step towards addressable voxel-based smart materials, while simultaneously addressing the robustness and actuation challenges faced by soft robots.

  PublisherDOI

• Viscous Thread Printing (VTP) for Production of Soft Robotic Fingers

  2025-04-22

  articleSenior author

  Many soft robotic systems use foams in structures and end-effectors, but often incorporate a limited range of homogeneous or laminated foams. These prior foam structures require extensive post-processing or assembly steps for use in soft robotics. Improved control over the production of foam using digital manufacturing tools can produce variable mechanical properties to reduce these issues. Here we show rapidly fabricated, variable stiffness, soft robotic fingers and hands from thermoplastic polyurethane at low-cost using Viscous Thread Printing (VTP) on a material extrusion 3D printer. Demonstrations of variable stiffness fingers are presented with force to angular displacement plots and potential applications are proposed. Experimental results are validated against an FEA model. VTP is shown to produce task-specific, soft robotic structures for compliant applications and opens up new opportunities in accessible, collaborative soft robotics.

  PublisherDOI

• Spring-Brake! Handed Shearing Auxetics Improve Efficiency of Hopping and Standing

  ArXiv.org · 2025-05-28

  preprintOpen accessSenior author

  Energy efficiency is critical to the success of legged robotics. Efficiency is lost through wasted energy during locomotion and standing. Including elastic elements has been shown to reduce movement costs, while including breaks can reduce standing costs. However, adding separate elements for each increases the mass and complexity of a leg, reducing overall system performance. Here we present a novel compliant mechanism using a Handed Shearing Auxetic (HSA) that acts as a spring and break in a monopod hopping robot. The HSA acts as a parallel elastic actuator, reducing electrical power for dynamic hopping and matching the efficiency of state-of-the-art compliant hoppers. The HSA\u2019s auxetic behavior enables dual functionality. During static tasks, it locks under large forces with minimal input power by blocking deformation, creating high friction similar to a capstan mechanism. This allows the leg to support heavy loads without motor torque, addressing thermal inefficiency. The multi-functional design enhances both dynamic and static performance, offering a versatile solution for robotic applications.

  PublisherOA PDFDOI

• Torque Responsive Metamaterials Enable High Payload Soft Robot Arms

  ArXiv.org · 2025-01-16 · 1 citations

  preprintOpen accessSenior author

  Soft robots have struggled to support large forces and moments while also supporting their own weight against gravity. This limits their ability to reach certain configurations necessary for tasks such as inspection and pushing objects up. We have overcome this limitation by creating an electrically driven metamaterial soft arm using handed shearing auxetics (HSA) and bendable extendable torque resistant (BETR) shafts. These use the large force and torque capacity of HSAs and the nestable torque transmission of BETRs to create a strong soft arm. We found that the HSA arm was able to push 2.3 kg vertically and lift more than 600 g when positioned horizontally, supporting 0.33 Nm of torque at the base. The arm is able to move between waypoints while carrying the large payload and demonstrates consistent movement with path variance below 5 mm. The HSA arm's ability to perform active grasping with HSA grippers was also demonstrated, requiring 20 N of pull force to dislodge the object. Finally, we test the arm in a pipe inspection task. The arm is able to locate all the defects while sliding against the inner surface of the pipe, demonstrating its compliance.

  PublisherOA PDFDOI

• Design and Reprogrammability of Zero Modes in 2D Materials from a Single Element

  Advanced Science · 2025-08-20

  articleOpen accessSenior authorCorresponding

  Mechanical extremal materials, a class of metamaterials that exist at the bounds of elastic theory, possess the extraordinary capability to engineer any desired elastic behavior by harnessing mechanical zero modes - deformation modes that demand minimal or, ideally, no elastic energy. However, the potential for arbitrary construction and reprogramming of metamaterials remains largely unrealized, primarily due to significant challenges in qualitatively transforming zero modes within the confines of existing metamaterial design frameworks. This work presents a method for explicitly defining and in situ reprogramming zero modes of 2D extremal materials by employing straight-line mechanisms (SLMs) and planar symmetry, which prescribe and coordinate the zero modes, respectively. The method is used to design, test, and reprogram centimeter-scale isotropic, orthotropic, and chiral extremal materials by reorienting the SLMs in place, enabling these materials to smoothly and reversibly interpolate between extremal modalities (e.g., unimode to bimode), material properties (e.g., negative to positive Poisson's ratios), and selectively enable chirality without changing the metamaterial's global structure. This methodology provides a straightforward and explicit strategy for the design and tuning of all varieties of 2D extremal materials, enabling dynamic mechanical metamaterial construction to completely cover the gamut of elastic properties.

  PublisherOA PDFDOI

• Fabrication-Directed Entanglement for Designing Chiral and Anisotropic Metamaterial Foams

  ArXiv.org · 2025-05-05

  preprintOpen accessSenior author

  Entangled networks are fundamental in various systems, from biological structures to engineered materials. Current techniques for programming entanglement often rely on intricate chemistry or result in statistically homogeneous networks, limiting the ability to create spatially patterned structures with precisely engineered functions. Thus, a key challenge remains in developing approaches to program complex mechanical behaviors, such as anisotropy and chirality, within monolithic entangled structures. This work introduces Fabrication-Directed Entanglement (FDE), a methodology integrating viscous thread printing (VTP) and topology optimization (TO) to program the entanglement of a single homogeneous filament. By spatially adjusting VTP parameters (deposition height, speed), we control local coiling density, creating quasi-two-phase (dense/sparse) regions within a monolithic entangled foam. Topology optimization guides the placement of these regions to achieve target macroscopic mechanical properties. Here we show foam-like mechanical metamaterials with tunable compliance, rigidity, and chirality. Experimental testing and simulation confirm that FDE expands the achievable material property space compared to homogeneous VTP foams, enabling properties like tunable directional stiffness, Poisson's ratios from $ν\approx0.06~\text{to}~0.56$, and novel significant normal-shear coupling ($η_{212}\approx0.72$) from a single base material. This approach offers a viable new pathway for designing complex, functional entangled foam structures with tailored mechanical behaviors.

  PublisherOA PDFDOI

• Fabrication‐Directed Entanglement for Designing Chiral and Anisotropic Metamaterial Foams

  Advanced Engineering Materials · 2025-11-30

  articleOpen accessSenior authorCorresponding

  While entangled networks are fundamental to many materials (e.g., proteins, polymers), current fabrication techniques are limited by scale or produce statistically homogeneous structures. This prevents the spatial programming of complex mechanical behaviors like anisotropy and chirality within a single, monolithic entangled material. This work introduces fabrication‐directed entanglement (FDE), a methodology that integrates topology optimization with viscous thread printing to spatially pattern the entanglement of a single, continuous thread into quasi‐two‐phase (dense/sparse) regions within a monolithic foam. Critically, this work demonstrates the first monolithic foam structures with programmed chirality, achieving significant normal‐shear coupling . The FDE framework also unlocks a broad range of tunable properties, including directional stiffness and Poisson's ratios from to 0.56 . FDE provides a direct pathway for designing and fabricating entangled metamaterials with complex tailored mechanical functions previously inaccessible in monolithic foam structures.

  PublisherOA PDFDOI

• Electrostatic Clutch-Based Mechanical Multiplexer with Increased Force Capability

  ArXiv.org · 2025-01-14 · 1 citations

  preprintOpen accessSenior author

  Robotic systems with many degrees of freedom (DoF) are constrained by the demands of dedicating a motor to each joint, and while mechanical multiplexing reduces actuator count, existing clutch designs are bulky, force-limited, or restricted to one output at a time. The problem addressed in this study is how to achieve high-force multiplexing that supports both simultaneous and sequential control from a single motor. Here we show an electrostatic capstan clutch-based transmission that enables both single-input-single-output (SISO) and single-input-multiple-output (SIMO) multiplexing. We demonstrated these on a four-DoF tendon-driven robotic hand where a single motor achieved output forces of up to 212 N, increased vertical grip strength by 4.09 times, and raised horizontal carrying capacity to 111.2 N, the highest currently among five-fingered tendon-driven robotic hands. These results demonstrate that electrostatic-based multiplexing provides versatile actuation, overcoming the limitations of prior systems.

  PublisherOA PDFDOI

• A Microgravity Experiment for Validating Rigid-Body Simulation of Deployable Mechanisms

  2025-12-01

  article

  Validating physics engines under microgravity conditions is critical for designing and controlling robotic systems in space, where friction, joint clearance, and contact can strongly influence system behavior. However, a lack of experimental data has limited efforts to validate and benchmark these simulators in flightrelevant environments. This work presents the design and execution of a free-floating microgravity experiment conducted on a parabolic flight to generate a dataset for validating rigid-body simulations. The experiment captures the centripetal deployment of three deployable mechanisms: a translational scissor, a polar scissor, and a pop-up extending truss (PET), using synchronized high-speed video and motion-capture sensors. We utilize multi-view reconstruction techniques to convert image data into 3D trajectory data of rigid elements across deployment. This dataset is used to validate the Dojo physics engine, which models full multi-rigid-body dynamics, including contact, joint friction, and clearance. By optimizing simulation parameters to match experimental trajectories, the accuracy of the model is quantified to assess sim-to-real alignment. Initial results show $\mathbf{1. 3 c m}$, 1.2cm, and 4.4cm RMSE for the scissor, polar scissor, and PET systems, respectively. This work contributes one of the first publicly documented microgravity datasets for evaluating rigid-body simulators and demonstrates a repeatable experimental framework for validating space robotics.

  PublisherDOI

Frequent coauthors

• Daniela Rus

  16 shared

• Chad C. Kessens

  United States Army Combat Capabilities Development Command

  7 shared

• Lillian Chin

  Massachusetts Institute of Technology

  6 shared

• Patrick O’Brien

  University of Washington

  6 shared

• Ian Good

  University of Washington

  6 shared

• Zachary Manchester

  5 shared

• Jeffrey T. Auletta

  DEVCOM Army Research Laboratory

  4 shared

• Sawyer Thomas

  Seattle University

  4 shared

Labs

• Jeffrey Ian LiptonPI

Education

• Ph.D., Computer Science

  Massachusetts Institute of Technology

  1986

• M.S., Computer Science

  University of California, Santa Barbara

  1982

• B.S., Mathematics

  University of California, Santa Barbara

  1980

Awards & honors

• Stanford University Annual Assessment of Author Citations (2…
• Stanford University Annual Assessment of Author Citations (2…
• Northeastern Team Wins Grand Prize at MassRobotics Competiti…
• Fall 2024 Spark Fund Award from Northeastern’s Center for Re…
• National Defense Science and Engineering Graduate Research F…