Philip LeDuc

About

Philip LeDuc is the William J. Brown Professor in the Department of Mechanical Engineering at Carnegie Mellon University. His research operates at the intersection of mechanical engineering and biology, where he investigates cells and molecules as systems that can be analyzed using principles similar to those applied to machines such as planes and automobiles. His work encompasses a broad range of biological systems, from mammalian cells and microorganisms to developmental biology systems, applying mechanical engineering concepts like solid mechanics, fluid mechanics, and control theory to understand diverse nature-based systems. In addition to his fundamental research, LeDuc focuses on energy-related applications, particularly algae and bacterial fuel cells, conducting both basic science and applied research in these areas. LeDuc has received numerous awards, including the National Science Foundation CAREER award, George Tallman Ladd Research Award, and the Beckman Foundation Young Investigator Award. He is a Fellow of several professional societies, including the Biomedical Engineering Society, American Society of Mechanical Engineers, and the American Institute for Medical & Biological Engineering. His contributions extend to leadership roles in research initiatives such as the Center for the Mechanics and Engineering of Cellular Systems and the Bioengineered Organs Initiative. His work has been recognized for its innovative approach to understanding cellular and…

Research topics

• Computer Science
• Engineering
• Biology
• Artificial Intelligence
• Medicine
• Computational biology
• Engineering drawing
• Data science
• Cancer research
• Electrical engineering

Selected publications

• Tumor-on-a-chip for integrating a 3D tumor microenvironment: chemical and mechanical factors

  Lab on a Chip · 2020 · 111 citations

  Senior authorCorresponding

  Tumor progression, including metastasis, is significantly influenced by factors in the tumor microenvironment (TME) such as mechanical force, shear stress, chemotaxis, and hypoxia. At present, most cancer studies investigate tumor metastasis by conventional cell culture methods and animal models, which are limited in data interpretation. Although patient tissue analysis, such as human patient-derived xenografts (PDX), can provide important clinical relevant information, they may not be feasible…

  DOI

• Hierarchical Machine Learning for High-Fidelity 3D Printed Biopolymers

  ACS Biomaterials Science & Engineering · 2020 · 106 citations

  = 0.643). Optimization allowed for the prediction of build parameters that gave rise to high-fidelity prints of the measured features. A trade-off was identified when optimizing for the fidelity of different features printed within the same construct, showing the need for complex predictive design tools. A combination of known and discovered relationships was used to generate process maps for the 3D bioprinting designer that show error minimums based on the chosen input variables. Our approach o…

  DOI

• Microfluidics for understanding model organisms

  Nature Communications · 2022 · 47 citations

  Senior authorCorresponding

  New microfluidic systems for whole organism analysis and experimentation are catalyzing biological breakthroughs across many fields, from human health to fundamental biology principles. This perspective discusses recent microfluidic tools to study intact model organisms to demonstrate the tremendous potential for these integrated approaches now and into the future. We describe these microsystems' technical features and highlight the unique advantages for precise manipulation in areas including i…

  PublisherOA PDFDOI

• Decidual Vasculopathy Identification in Whole Slide Images Using Multiresolution Hierarchical Convolutional Neural Networks

  American Journal Of Pathology · 2020 · 33 citations

  Senior authorCorresponding
  DOI

• Nanotopographical Cues Tune the Therapeutic Potential of Extracellular Vesicles for the Treatment of Aged Skeletal Muscle Injuries

  ACS Nano · 2023-10-05 · 25 citations

  articleOpen access

  Skeletal muscle regeneration relies on the tightly temporally regulated lineage progression of muscle stem/progenitor cells (MPCs) from activation to proliferation and, finally, differentiation. However, with aging, MPC lineage progression is disrupted and delayed, ultimately causing impaired muscle regeneration. Extracellular vesicles (EVs) have attracted broad attention as next-generation therapeutics for promoting tissue regeneration. As a next step toward clinical translation, strategies to…

  PublisherDOI

Recent grants

• CAREER: Understanding Cellular and Molecular Mechanics with Nano-/Micro-technology

  NSF · $407k · 2004–2011

• Role of extracellular matrix in age-related declines of muscle regeneration

  NIH · $474k · 2019–2024

• Role of extracellular matrix in age-related declines of muscle regeneration

  NIH · $2.1M · 2019–2025

Frequent coauthors

• C. Bermond

  Institut polytechnique de Grenoble

  101 shared

• T. Lacrevaz

  Institut polytechnique de Grenoble

  88 shared

• L. Cadix

  STMicroelectronics (Switzerland)

  81 shared

• N. Sillon

  CEA Grenoble

  77 shared

• B. Fléchet

  Institut de Microélectronique, Electromagnétisme et Photonique

  73 shared

• A. Farcy

  STMicroelectronics (Czechia)

  62 shared

• Chao‐Min Cheng

  National Tsing Hua University

  60 shared

• S. Chéramy

  Commissariat à l'Énergie Atomique et aux Énergies Alternatives

  60 shared

Labs

• The LeDuc LabPI

  The LeDuc Lab focuses on the intersection of biology and engineering, with research interests including artificial cardiac tissue, renewable energies, biomimicry, regenerative medicine, robotics, additive manufacturing, and more.

Awards & honors

• National Science Foundation CAREER award
• George Tallman Ladd Research Award
• Russell V. Trader Career Faculty Fellow
• Benjamin Richard Teare Teaching Award
• Professor of the Year as voted by the senior class

Similar researchers at Carnegie Mellon University

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• Jack Beuthh-41
• Maarten de Boerh-40