About

Neelesh A. Patankar is a Professor of Mechanical Engineering at Northwestern University, with courtesy appointments in Engineering Sciences and Applied Mathematics. He is also the Director of the Northwestern Advanced Institute for Science and Engineering (NAISE). His research group focuses on three primary missions: developing fully resolved computational fluid dynamics (CFD) techniques for fluid-structure interaction problems, using theory and CFD to understand organ physiology and integrating mechanics-based analyses and diagnostic tools into clinical practice, and establishing the foundational science of controlling phase transitions such as anti-icing, anti-frosting, boiling, condensation, and non-wetting superhydrophobic surfaces through surface roughness and chemistry. Patankar's work has significant implications across multiple fields, including biomedical engineering, fluid mechanics, and surface science. He has received numerous recognitions, including the NSF CAREER Award, the Searle Junior Fellowship, and the International Conference on Multiphase Flow Junior Award. He has also been honored for outstanding teaching and has contributed extensively to the academic community through his research, teaching, and leadership roles.

Research topics

• Physics
• Composite material
• Materials science
• Mechanics
• Thermodynamics
• Mathematical optimization
• Meteorology
• Chemistry
• Mathematical analysis
• Mathematics
• Chemical physics
• Geomorphology
• Nanotechnology
• Classical mechanics
• Geology

Selected publications

• Addressing Gaps in the Chicago Classification Version 4.0: Defining an Optimal Intrabolus Pressure Measurement on Esophageal Manometry

  Neurogastroenterology & Motility · 2026-04-01 · 1 citations

  articleOpen access

  BACKGROUND: Intrabolus pressure (IBP) reflects the pressure within the esophageal lumen during bolus transit and serves as a physiologic marker of outflow resistance at the esophagogastric junction (EGJ). The lack of a standardized or validated method to measure IBP is a critical limitation for interpreting high resolution manometry (HRM) and identification of clinically relevant EGJ outflow obstruction (EGJOO). METHODS: Three distinct cohorts, "Controls", Normal motility", and "conclusive EGJOO" were selected from a prospectively enrolled cohort of adult patients. All patients had at least undergone HRM with impedance (HRIM), and functional lumen impedance probe (FLIP) testing. 4D HRM analysis was performed blinded to clinical characteristics. 4D HRM IBP results were assessed on a per-swallow and also on a per-patient level. Receiver operating curve (ROCs) to assess each metrics prediction of conclusive EGJOO vs. not EGJOO (normal motility and controls) were utilized for the per-swallow analysis. KEY RESULTS: 33 controls, 35 normal motility, and 15 conclusive EGJOO patients were included. Swallow level analysis was conducted on 156 swallows, 165 swallows, and 61 swallows from each group, respectively. Per-swallow analysis demonstrated differences between conclusive EGJOO, normal motility, and controls for all ten IBP measures (P-values < 0.001), with greater IBP measures in conclusive EGJOO than in normal motility and controls. The 1 s max IBP had the greatest AUROC. CONCLUSIONS & INFERENCES: Standardized measurement of IBP using an optimized method (1-s max IBP) within the 4D-HRM framework with impedance-confirmed bolus tracking and phase-specific measures represents a physiologically grounded and clinically meaningful advance in HRIM interpretation.

  PublisherDOI

• A Soft-Robotic Biomimetic Benchtop Model for Esophageal Motility Simulation

  Nature Communications · 2026-03-12

  articleOpen access

  Large animal models, while valuable, are expensive, time-consuming, and limited to discrete interventional or terminal timepoints, while existing benchtop models do not offer an accurate representation of the esophageal environment. Moreover, current pre-clinical models cannot effectively simulate swallowing dysfunction (dysphagia), restricting progress in understanding motility disorders like achalasia and hindering evidence-based dietary recommendations. In response, we present RoboGullet, a biomimetic soft-robotic model with independent localized longitudinal and circumferential muscle actuation, enabling, for the first time, simulation of both normal and diseased esophageal motility. We further enhance realism with a biohybrid variant, RoboGullet + , incorporating porcine esophageal mucosa/submucosa. We demonstrate this platform's versatility through three key applications: assessing stent migration, simulating achalasia I-III within clinical diagnostic criteria, and analyzing bolus swallowing. Our findings reveal that: (1) stent migration increases over fivefold when incorporating longitudinal muscle movement versus isolated circumferential; (2) using a viscous non-Newtonian bolus improves high-resolution manometry diagnostic sensitivity of Achalasia III through increasing the Distal Latency diagnostic metric by 20.83%; and (3) stirring Greek-style yoghurt (common non-Newtonian dietary recommendation) significantly improves bolus transit versus unstirred for Achalasia Types I-II patients. This establishes RoboGullet+ as a powerful translational tool, advancing our understanding of esophageal motility and its therapeutic interventions.

  PublisherOA PDFDOI

• IP10-24 MECHANOPHYSIOLOGY OF THE LOWER URINARY TRACT: DETERMINING STRICTURE SEVERITY BY ESTIMATING TISSUE COMPLIANCE FROM RETROGRADE URETHROGRAMS

  The Journal of Urology · 2026-04-27

  articleSenior author
  PublisherDOI

• Perspectives on physics-based one-dimensional modeling of lung physiology

  Frontiers in Physiology · 2025-09-24 · 2 citations

  articleOpen accessSenior authorCorresponding

  The need to understand how infection spreads to the deep lung was acutely realized during the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic. The challenge of modeling virus laden aerosol transport and deposition in the airways, coupled with mucus clearance, and infection kinetics, became evident. This perspective provides a consolidated view of coupled one-dimensional physics-based mathematical models to probe multifaceted aspects of lung physiology. Successes of 1D trumpet models in providing mechanistic insights into lung function and optimalities are reviewed while identifying limitations and future directions. Key non-dimensional numbers defining lung function are reported. The need to quantitatively map various pathologies on a physics-based parameter space of non-dimensional numbers (a virtual disease landscape) is noted with an eye on translating modeling to clinical practice. This could aid in disease diagnosis, get mechanistic insights into pathologies, and determine patient specific treatment plan. 1D modeling could, thus, be an important tool in developing novel measurement and analysis platforms that could be deployed at point-of-care.

  PublisherOA PDFDOI

• Direct and Retrograde Wave Propagation in Unidirectionally Coupled Wilson-Cowan Oscillators

  Physical Review Letters · 2025-02-06 · 2 citations

  articleOpen accessSenior author

  Some biological systems exhibit both direct and retrograde propagating signal waves despite unidirectional coupling. To explain this phenomenon, we study a chain of unidirectionally coupled Wilson-Cowan oscillators. Surprisingly, we find that changes in the homogeneous global input to the chain suffice to reverse the wave propagation direction. To obtain insights, we analyze the frequencies and bifurcations of the limit cycle solutions of the chain as a function of the global input. Specifically, we determine that the directionality of wave propagation is controlled by differences in the intrinsic frequencies of oscillators caused by the differential proximity of the oscillators to a homoclinic bifurcation.

  PublisherOA PDFDOI

• Ex-vivo mechano-structural characterization of fresh diseased human esophagus

  Acta Biomaterialia · 2025-02-26 · 1 citations

  articleOpen access

  The esophagus, the tube-like organ responsible for transporting food from the pharynx to the stomach, operates as a highly mechanical structure, exhibiting complex contraction and distension patterns triggered by neurological impulses. Despite the critical role of mechanics in its function and the need for high-fidelity models of esophageal transport, mechanical characterization studies of human esophagus remain relatively scarce. In addition to the paucity of studies in human specimens, the available results are often scattered in terms of methodology and scope, making it difficult to compare findings across studies and thereby limiting their use in computational models. In this work, we present a detailed passive-mechanical and structural characterization of the esophageal muscular layers, excised from short esophageal segments obtained from live patients with varied clinical presentations. Specifically, we conducted uniaxial and planar biaxial extension tests on the smooth muscle layers, complemented by pre- and post-testing structural characterization via histological imaging. Unlike existing studies, our experimental results on passive behavior are discussed in the context of physiological relevance (e.g., physiological stretches, and activity-inhibiting pathologies), providing valuable insights that guide the subsequent modeling of the esophagus' mechanical response. As such, this work provides new insights into the passive properties of the fresh human esophagus, expands the existing database of mechanical parameters for computational modeling, and lays the foundation for future studies on active mechanical properties. STATEMENT OF SIGNIFICANCE: Understanding the mechanical properties of the esophagus is crucial for developing accurate models of its function and suitable replacements. This study provides insights into the passive mechanical behavior of fresh human esophageal tissue, enhancing our understanding of how it responds to stretching under physiological conditions. By characterizing the properties of different esophageal layers, obtained from esophagectomy specimens with various presentations, and considering their relevance to both normal and abnormal functioning, this work addresses the gap in ex-vivo human esophagus studies. The findings emphasize the importance of contextually analyzing experimental results within physiological parameters and suggest avenues for future research to further refine our understanding of esophageal mechanics, paving the way for improved diagnostic and therapeutic approaches in managing esophageal disorders.

  PublisherDOI

• Editorial: Translating biomechanics of the human airways for classification, diagnosis and treatment of pulmonary diseases

  Frontiers in Physiology · 2025-11-24

  editorialOpen accessSenior author

  Treatment strategies for COPD and asthmatic patients is a critical issue faced by pulmonologists across the world. The article by Li et al. sheds light on how deeper insights into pathogenesis and phenotyping of COPD may be obtained using a combination of single-photon emission computed tomography (SPECT) and quantitative computed tomography (qCT)-derived biomarkers. These insights can be utilised to develop new avenues for evaluating COPD progression and devising appropriate therapeutic responses. A different interventional approach was adopted by Abu Shaphe et al. They investigated how treadmill exercise responses, guided by the 6-minute walk test, vary among individuals with differing COPD severity. Their findings suggest that personalising treadmill exercise protocols according to COPD severity levels and walk test results can reveal important functional limitations and help tailor rehabilitation strategies for improved outcomes in COPD management. The study by Zhong et al. show that Fe2O3 nanoparticles -when used in optimal concentration -can potentially disrupt the microstructure of airway mucosal fluid significantly lowering the viscoelastic nature of the mucosal fluid and facilitating easier mucus clearance from airways. Tests using mucus from asthmatic patients confirm these findings suggesting that Fe2O3 nanoparticles could act as expectorants, potentially outperforming conventional mucolytics by virtue of their biocompatibility and availability.Pulmonary drug delivery presents a plausible route for achieving efficient systemic drug delivery [West, 2012]. However, despite the clinical relevance, its efficiency remains suboptimal owing to significant deposition of inhaled aerosolised drug dose in the upper respiratory tract (Bessler et al., 2024). Compensation through larger doses is often prescribed although undesirable side effects or even systemic exposure is possible [De Boer et al., 2017]. Various novel strategies are, thus, being investigated for overcoming this drawback [Dua et al., 2020;Chakravarty et al., 2022;Kole et al., 2023]. Bessler et al. reports on a relatively less investigated strategy -leveraging the inherent electrostatic charge present on inhaled aerosols. Their study -using an in vitro airway-on-chip platform mimicking small bronchial geometries -reveal that electrostatic forces substantially alter deposition patterns in constricted airways: for submicron particles, there is enhanced proximal airway deposition due to electrostatic-diffusive effects, while larger particles show extended deposition footprints beyond what gravity alone would allow. These results suggest electrostatic attraction could be strategically used to improve the targeting of inhaled therapeutics in obstructive lung diseases like asthma and COPD.The pulmonary drug delivery systems also warrant personalisation for achieving desired therapeutic efficacy due to inter-patient variability in lung morphology. Direct quantification of such variability is, however, not possible beyond the 7 th lung generation owing to technological limitations, despite recent advances in imaging and diagnostic techniques. The article by Karthiga Devi et al. discusses a novel non-invasive method to estimate morphology of the distal lung by measuring radio-aerosol deposition patterns in healthy individuals utilizing gamma scintigraphy. The results demonstrate that aerosol deposition, particularly in the distal airways, serves as a sensitive marker of morphological variability, suggesting this approach could be developed into a walk-in lab test to personalize diagnosis and optimize pulmonary drug delivery.A different aspect of personalised respiratory care is highlighted in Vijay Anand et al. They presented a mechanistic compartmental model designed to investigate how airway secretion accumulation and its removal affect respiratory dynamics in ICU patients on mechanical ventilation. The study identifies characteristic changes in ventilator waveforms due to secretion buildup-such as reduced inspiratory flow and longer exhalation-and introduces a model-informed secretion index for continuous bedside monitoring. These findings can be utilised to improve personalized respiratory care and secretion management for mechanically ventilated patients.Another key contribution to this research topic (Chakravarty et al.) discusses the development of a versatile physics-based, 1D reduced-order computational model encompassing varied and complex bio-physical phenomena involving airflow, gas exchange, particle/aerosol transport and deposition, mucus transport and pathogen infection progression within the human airways. The model has been utilised for identifying routes of improving drug delivery to the acinar region of the lung (Chakravarty et al., 2022). A different application of this model (Chakravarty et al., 2023) led to the hypothesis of re-aerosolisation of nasopharyngeal mucosa (RNM) as a plausible route of COVID-19 infection spread to the acinar region of the lung (Morawska et al., 2022), while reinforcing the utility of vaccination in preventing fatal infections.The hypothesis of RNM is being investigated through computations and experiments by various groups [Pairetti et al., 2021;Anzai et al., 2022;Kant et al. 2023;Saha et al., 2024;Li et al., 2025]. One such group (Ilegbusi et al.) studied the formation and transport of mucus droplets during cough across CTderived upper airway geometries. Increases in mucus thickness and viscosity-characteristic of respiratory diseases-is observed to substantially affect the number and size of exhaled droplets, with thicker mucus yielding more and larger droplets, while more viscous mucus results in fewer but larger droplets. Similar findings were reported by Saha et al. (2024). A more generic case of the same mechanism involving inhaled lower airway transmission of pathogen-laden microdroplets fragmented from the upper airway mucosa has been recently explored in a different study (Basu, 2025), through full-scale computational simulation of the intra-airway inhalation physics within CT-based anatomical domains. The simulated patterns of advective transport were validated against reduced-order analytical estimates (tracking the impact of dominant vortex cores in the laryngotracheal space on downwind bronchial transport) and published experimental results (Miguel, 2017). The mechanism has been hypothesized (Basu, 2025;Chakravarty et al., 2023) as a key factor for brisk onset of secondary deep lung infections, following the emergence of symptoms in the upper respiratory tract. These findings show that the distribution of exhaled cough droplets can act as a sensitive, non-invasive biomarker for classifying pulmonary diseases, underlining the diagnostic potential of droplet dynamics and mucosal properties in respiratory health assessment.To summarise, the article collection on the research topic highlights the potential of airway biomechanics to be used for defining clinically-relevant metrics called physiomarkers and develop diagnostic tools. For example, the reduced-order model (Chakravarty et al.) introduces several dimensionless parameters for defining lung physiology which can be used to construct a virtual disease landscape (VDL) --essentially a mapping of different disease groups and normal function in a hyperspace of dimensionless parameters controlling lung function. These parameters defining the VDL can help obtain mechanistic insights into pathologies and hence used as physiomarkers for disease classification and diagnosis. The VDL -coupled machine learning techniques -could be developed into a powerful diagnostic tool for disease trajectory prediction, optimize therapeutic interventions, and ultimately improve patient outcomes.

  PublisherOA PDFDOI

• Modeling based insights into mechanical dysfunction in esophageal motility disorders

  PLoS Computational Biology · 2025-12-26 · 1 citations

  articleOpen accessSenior author

  Esophageal motility arises from the continuous coupling between enteric neural activity and the organ's mechanical response, yet the structure of this coupling remains poorly understood. Esophageal motility disorders represent mechanical dysfunctions that originate from abnormalities in neural control, underscoring the need to understand how neural and mechanical processes interact to produce coordinated motion. We present an empirically guided neuromechanical model of the esophagus, comprising unidirectionally coupled relaxation oscillators activated by intrinsic enteric nervous system mechanoreceptors sensitive to wall distension. The model reveals complex behaviors emerging from interactions among its components, predicting various clinically observed normal and abnormal esophageal responses to distension. Specifically, repetitive antegrade contractions (RACs) are shown to arise from the coupled neuromechanical dynamics in response to sustained volumetric distension. Normal RACs are shown to have a robust balance between excitatory and inhibitory neural activities and mechanical input through these intrinsic distension-sensitive mechanoreceptors. When this balance is affected, contraction patterns resembling motility disorders emerge. For example, clinically observed repetitive retrograde contractions emerge due to hypersensitive mechanoreceptors in the esophageal wall. Such neuromechanical insights may ultimately guide the development of targeted pharmacological interventions.

  PublisherDOI

• Mechanophysiology of endometriosis: a non-dimensional physiomarker to detect retrograde flow

  bioRxiv (Cold Spring Harbor Laboratory) · 2024-05-16

  preprintOpen accessSenior authorCorresponding

  Abstract Endometriosis affects a significant portion of fertile-age women, often leading to infertility and a substantial decline in quality of life. Despite its prevalence, current diagnostic methods are limited, focusing on assessing the presence or absence of endometrial lesion, rather than the origin of the disorder. Thus, resulting in underdiagnosis. A potential mechanics-based metric for diagnosing endometriosis is proposed here by leveraging the retrograde menstruation hypothesis. By examining the interplay between uterine and fallopian tube peristalses, a non-dimensional physiomarker is introduced to signify the onset of retrograde flow. The analysis reveals that increased uterine contractile activity, coupled with decreased fallopian tube contractile activity, correlates with retrograde flow, suggesting a predisposition to endometriosis. This mechanophysiology-based approach offers a promising avenue for origin based diagnosis, with the proposed non-dimensional physiomarker – the endometriosis number – serving as a potential indicator of endometrial cell migration and the onset of endometriosis.

  PublisherOA PDFDOI

• Direct and retrograde signal propagation in unidirectionally coupled Wilson-Cowan oscillators

  arXiv (Cornell University) · 2024-02-28

  preprintOpen accessSenior author

  Certain biological systems exhibit both direct and retrograde propagating wave signals, despite unidirectional neural coupling. However, there is no model to explain this. Therefore, the underlying physics of reversing the signal's direction for one-way coupling remains unclear. Here, we resolve this issue using a Wilson-Cowan oscillators network. By analyzing the limit cycle period of various coupling configurations, we determine that intrinsic frequency differences among oscillators control wave directionality.

  PublisherOA PDFDOI

Recent grants

• SI2-SSI: Collaborative Research: Scalable Infrastructure for Enabling Multiscale and Multiphysics Applications in Fluid Dynamics, Solid Mechanics, and Fluid-Structure Interaction

  NSF · $513k · 2015–2021

• Fully resolved simulation of self-propelling fish

  NSF · $330k · 2008–2012

• CAREER: Computational Techniques for Sub-Micron/Nanoscale Fluid Dynamics

  NSF · $375k · 2002–2007

• Using Biofluiddynamics to Interrogate the Spinal Circuitry Controlling Movements

  NSF · $329k · 2011–2016

• Collaborative Research: Fluctuating Hydrodynamics of Suspensions of Rigid Bodies

  NSF · $155k · 2014–2018

Frequent coauthors

• John E. Pandolfino

  Medpace (United States)

  65 shared

• Peter J. Kahrilas

  Northwestern University

  64 shared

• Wenjun Kou

  Lanzhou University of Technology

  59 shared

• Sourav Halder

  West Bengal University of Animal and Fishery Sciences

  50 shared

• Amneet Pal Singh Bhalla

  43 shared

• Shashank Acharya

  McCormick (United States)

  41 shared

• Dustin A. Carlson

  Northwestern University

  34 shared

• Guy Elisha

  Northwestern University

  30 shared

Labs

• Patankar GroupPI

Awards & honors

• International Conference on Multiphase Flow Junior Award, 20…
• Defense Science Study Group member, 2010-2011
• Associated Student Government Honor Roll for outstanding tea…
• Honorable mention McCormick Teacher of the Year, 2008
• NSF CAREER Award, 2002