Vineeth Vijaya Kumar
Vineeth Vijaya Kumar
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Bio: Passionate about leveraging computational fluid dynamics and machine learning to innovate in aerodynamics and digital twin development.
Postdoctoral Research Associate
Texas A&M University, Kingsville, Texas, US
Research Interests:
Computational fluid dynamics
Bio-inspired propulsion
Vortex wakes
Implementation of machine learning models for wake structure prediction
Digital twins
Publications
V K Vineeth, Chris Harris, Vinod Kumar, Toward Digital Twin-Enabled Venous Flow Modelling: Interactive Valve Geometry and Lab-on-Chip Generation Framework, Computers in Biology and Medicine (2026) Vol. 212, p. 111755.
V K Vineeth, Devendra Kumar Patel, Dynamic wake behaviour and aerodynamic characteristics of a custom airfoil under combined pitching and heaving motion, International Journal of Modern Physics C, (2025) Vol. 36, No. 2, pp. 1-30 (IF: 1.5).
V K Vineeth, Devendra Kumar Patel, Dependence of wake structure evolution on frequency of a pitching wing: A numerical investigation using LES, International Journal of Modern Physics C, Vol. 34 (2023), No. 08, pp. 2350108 (IF: 1.5).
V K Vineeth, Devendra Kumar Patel, Influence of aspect ratio on the wake dynamics of a pitching wing, Physics of Fluids, Vol 34 (2022), No. 3, pp. 035106 (IF: 4.1).
V K Vineeth, Devendra Kumar Patel, A comparative analysis of the characteristics of the vortex wake behind a flapping wing performing oscillations of different types, Fluid Dynamics, Vol. 56 (2021), pp. S101-125 (IF: 1.0).
V K Vineeth, Devendra Kumar Patel, Propulsion performance and wake transitions of a customized heaving airfoil, International Journal of Modern Physics C, Vol. 32 (2021), No. 09, pp. 2150117 (IF: 1.5).
V K Vineeth, Devendra Kumar Patel, Subhransu Roy, Srikanth Goli, Arnab Roy, Investigations into transient wakes behind a custom airfoil undergoing pitching motion, European Journal of Mechanics/ B Fluids, Vol. 85 (2021), pp. 193-213. (IF: 2.5).
Wakes behind a pitching airfoil
von Karman wake
Neutral wake
reverse von Karman wake
Conferences
Vineeth V K, Sai Jeevan Puchakayala, Aswathy Ravikumar, Arturo Rodriguez, Vinod Kumar, Advancing Wake Structure Classification behind Oscillating Airfoils by Mitigating Class Imbalance with a Novel Data-Driven Machine Learning Framework, 11th Thermal and Fluids Engineering Conference, March, 9-12, 2026 , Arizona State University, Tempe, AZ, USA. Link
Noah L. Estrada, Marc A. Cantu, Arturo Rodriguez, Andrew R. Ybarra, Jeffrey H. Farris, Francisco O. Aguirre Ortega, Vineeth V K, Vinod Kumar, Verification of Convergent-Divergent Nozzle Designs in Propulsion Aerospace Applications, 11th Thermal and Fluids Engineering Conference, March, 9-12, 2026 , Arizona State University, Tempe, AZ, USA. Link
Arturo Rodriguez, Christopher Harris, Avinash Potluri, Noah L. Estrada, Alan M. Hernandez, Vyom Kumar, Francisco O. Aguirre Ortega, Vineeth V K, Numerical and Analytical Modelling of Heat Transfer in Current-Carrying Conductors using the Heat Equation implemented using Finite-JAX, 11th Thermal and Fluids Engineering Conference, March, 9-12, 2026 , Arizona State University, Tempe, AZ, USA. Link
Arturo Rodriguez, Avinash Potluri, Aryan Singh, Vyom Kumar, Kate Reza, Francisco O. Aguirre Ortega, Vineeth V K, Noah L. Estrada, Cross-Model Verification of Wall-Bounded Flows using Finite-JAX, 11th Thermal and Fluids Engineering Conference, March, 9-12, 2026, Arizona State University, Tempe, AZ, USA. Link
Vineeth V K, Sai Jeevan Puchakayala, Aswathy Ravikumar, Arturo Rodriguez, Vinod Kumar, Unsteady Aerodynamic Wake Modes in Pitching Airfoils: Machine Learning Enabled Classification and Prediction, APS Division of Fluid Dynamics Annual Meeting, Nov 23-25, 2025, Houston, TX, United States.
Aryan Singh, Vyom Kumar, Arturo Rodriguez, Vineeth V K, Christopher Harris, CFD Modelling of Venous Valve Flow Characteristics at Various Reynolds Numbers, APS Division of Fluid Dynamics Annual Meeting, Nov 23-25, 2025, Houston, TX, United States.
Vyom Kumar, Aryan Singh, Vineeth V K, Arturo Rodriguez, Jeffrey H. Farris, Andrew R.Ybarra, Christopher Harris, Assimilated Physical Digital Twin of Venous Valve for Biological Flows, APS Division of Fluid Dynamics Annual Meeting, Nov 23-25, 2025, Houston, TX, United States.
Avinash Potluri, Arturo Rodriguez, Vineeth V K, Gopishwar Sharma Palepu, Vinod Kumar, Shock Dynamics Flows Dataset Creation using Explicit and Implicit Finite Difference Solvers, APS Division of Fluid Dynamics Annual Meeting, Nov 23-25, 2025, Houston, TX, United States.
Alan M. Hernandez, Arturo Rodriguez, Vineeth V K, Avinash Potluri, Gopishwar Sharma Palepu, Vinod Kumar, Physics-Informed Neural Networks: Forward and Inverse Design Solutions for Hypersonic Blunt Cones, APS Division of Fluid Dynamics Annual Meeting, Nov 23-25, 2025, Houston, TX, United States.
Arturo Rodriguez, Vinod Kumar, Vineeth V K, Avinash Potluri, Gopishwar Sharma Palepu, Partition of Unity Physics-Informed Neural Networks (POU-PINNs) for Darcy Flow, APS Division of Fluid Dynamics Annual Meeting, Nov 23-25, 2025, Houston, TX, United States.
Oswaldo Aguirre, Arturo Rodriguez, Jose F. Espiritu, Vineeth V K, Vinod Kumar, Generative Probability Density Function for Atmospheric Turbulence Flows, APS Division of Fluid Dynamics Annual Meeting, Nov 23-25, 2025, Houston, TX, United States.
Gopishwar Sharma Palepu, Arturo Rodriguez, Avinash Potluri, Vineeth V K, Vinod Kumar, Scientific Discovery of Shock Dynamics via Generative Artificial Intelligence, APS Division of Fluid Dynamics Annual Meeting, Nov 23-25, 2025, Houston, TX, United States.
Vinod Kumar, Christopher Harris, Vineeth V K, Arturo Rodriguez, Herb Janssen, Digital Twin Framework: Integrating Experimentation, Simulation, and AI for Patient-Specific Hemodynamics in Venous Valves, APS Division of Fluid Dynamics Annual Meeting, Nov 23-25, 2025, Houston, TX, United States.
Sai Jeevan Puchakayala, Vineeth V K, Aswathy Ravikumar, Devendra Kumar Patel, Machine Learning-Driven Classification and Prediction of Wake Structures in Pitching Airfoils for Enhanced Aerodynamic Analytics, 4th International Conference on Machine Learning and Data Engineering, Nov 6-8, 2025, Dehradun, India.
Vineeth V K, Christopher K. Harris, Herb Janssen, Vinod Kumar, Assessing DVT Risk based on Venous Valve Geometry Using Fluid-Structure Interaction (FSI) Modelling, 71st Annual Conference, American Society for Artificial Internal Organs (ASAIO), Jun 4-7, 2025, New Orleans, Los Angels, USA. Link
Christopher K. Harris, Vinod Kumar, Herb Janssen, Vineeth V K, Discriminating Between Blood Rheological Models using Differential Changes in Shear Stress versus Shear Rate, 71st Annual Conference, American Society for Artificial Internal Organs (ASAIO), Jun 4-7, 2025, New Orleans, Los Angels, USA. Link
Sai Jeevan Puchakayala, Aswathy Ravikumar, Vineeth V K, An ensemble deep learning model based high precision automated analogue meter reading utilising EfficientDet detection and U-Net segmentation, IEEE World Conference on Applied Intelligence and Computing, July 27-28, 2024, Gwalior, India. Link
V K Vineeth, Devendra Kumar Patel, Influence of aspect ratio on wake structure evolution and wake profiles behind a heaving wing, AIAA Aviation Forum, Jun 12-16, 2023, San Diego, California, USA. Link
V K Vineeth, Devendra Kumar Patel, Large-eddy simulation of wake structure behind a pitching wing with different aspect ratios, AIAA Sci-TECH Forum, Jan 3-7, 2022, San Diego, California, USA. Link
V K Vineeth, Devendra Kumar Patel, Comparison of wake characteristics behind a custom-designed airfoil performing different types of flapping oscillations, 26th National and 4th International ISHMT-ASTFE Heat and Mass Transfer Conference, Dec 17-20, 2021, IIT Madras. Link
Vineeth V K, Devendra Kumar Patel, Splendid Nehemiah, Mukul Shrivastava, Different Wake Structures Behind a Flapping Airfoil and it’s Influence on Propulsion Performance, 4th International Congress on Advances in Mechanical Sciences, Nov 26-27, 2021 Vardhaman College of Engineering, Hyderabad. Link
deflected wake
Coherent structures in flow using proper orthogonal decomposition
Books & Book Chapters
Vineeth V K, Devendra Kumar Patel, Flapping wings: Bio-mimicking for future- A computational perspective of the application, Lambert Academic Publishing (ISBN: 978-620-6-14424-3). Link
Aparna Nair M K, Vineeth V K, Future of AI-based Applications in Education Sector: Challenges and Scope, in Book “Advanced AI Technologies for Improving Education Systems”, Taylor & Francis, ISBN: 9781041070610. Link
Sai Jeevan Puchakayala, Aswathy Ravikumar, Vineeth V K, Digital Twins in the Modern Era of IoT and AI, in Book “Human Centric Intelligent Transportation Systems for Modern Society: Fundamentals, Methods, Practical Implementations, and Future Applications”, Taylor & Francis, ISBN: 9781041092414. Link
Aparna Nair M K, Vineeth V K, Digital Twins for Healthcare Facilities in Society 5.0 in Book “6G Embedded Blockchain Based Smart Healthcare for Society 5.0", Taylor & Francis (With publisher).
Vineeth V K, Vinod Kumar, Chris Harris, Machine Learning and Digital Twin Frameworks for Thermal Management Applications in Book "Next-Generation Nano-fluid Technologies for Advanced Thermal Management", Elsevier (In drafting).
Completed Projects: 1
Wake dynamics and thrust performance of oscillating airfoils
Funded by
Council of Scientific & Industrial Research (CSIR), Government of India
Visualization below:
Multiple vortex wakes behind airfoils performing combined pitching and heaving motion
2P wake
4P wake
8S wake
Completed Projects: 2
Wake characteristics and performance evaluation of flapping wings
Funded by
Council of Scientific & Industrial Research (CSIR), Government of India
Visualization below:
Wake visualisation through isosurfaces of Q-function
Symmetric teardrop airfoil performing pitching oscillations
Cambered NACA8412 airfoil performing pitching oscillations
Collaborative Project: 1
Title: Unsteady Aerodynamic Wake Modes in Pitching Airfoils: Machine Learning Enabled Classification and Prediction
Collaborators: Sai Jeevan Puchakayala, Aswathy Ravikumar, (Sustainable Living Lab, India)
Implementation of machine learning models to predict the wake structure behind oscillating airfoils.
Different machine learning models are used to train and test for wake structure prediction.
ADASYN and SMOTE analysis are used to address class imbalance in the data.
Confusion matrix (Random Forest Classifier)
Performance metric (Random Forest Classifier)
Project Outcomes:
Vineeth V K, Sai Jeevan Puchakayala, Aswathy Ravikumar, Arturo Rodriguez, Vinod Kumar, Advancing Wake Structure Classification behind Oscillating Airfoils by Mitigating Class Imbalance with a Novel Data-Driven Machine Learning Framework, 11th Thermal and Fluids Engineering Conference, March, 9-12, 2026 , Arizona State University, Tempe, AZ, USA.
Vineeth V K, Sai Jeevan Puchakayala, Aswathy Ravikumar, Devendra Kumar Patel, Arturo Rodriguez, Vinod Kumar, Unsteady Aerodynamic Wake Modes in Pitching Airfoils: Machine Learning Enabled Classification and Prediction, APS Division of Fluid Dynamics Annual Meeting, Nov 23-25, 2025, Houston, TX, United States.
Sai Jeevan Puchakayala, Vineeth V K, Aswathy Ravikumar, Devendra Kumar Patel, Machine Learning-Driven Classification and Prediction of Wake Structures in Pitching Airfoils for Enhanced Aerodynamic Analytics, 4th International Conference on Machine Learning and Data Engineering, Nov 6-8, 2025, Dehradun, India.
Completed Projects 3:
TITLE:
Toward Digital Twin-Enabled Venous Flow Modelling: Interactive Valve Geometry and Lab-on-Chip Generation Framework
U.S. Department of Defense under Grant No. W911NF-24-1-0267.
Completed Projects 3:
TITLE:
Toward Digital Twin-Enabled Venous Flow Modelling: Interactive Valve Geometry and Lab-on-Chip Generation Framework
Project Summary
The present work introduces a web-based framework that provides real-time generation, visualization and meshing of venous valve geometry using analytically defined constructional parameters.
The interface allows manipulation of physiological parameters, including vein radius, sinus bulge, sinus length, leaflet spacing, leaflet thickness, and leaflet extension. This enables the modeling of both healthy and pathological valve morphologies and ensures reproducibility.
Based on the parameter values, the framework generates a two-dimensional (2D) outline of the geometry and a three-dimensional (3D) lab-on-a-chip-style geometry. It supports the direct export of stereolithography (STL) files, numerical simulation, or micro-channel fabrication.
The framework also generates high-quality meshes suitable for computational fluid dynamics (CFD) simulations using a hexagonal lattice-based discretization strategy, combined with Delaunay triangulation and masking.
Project Outcome:
V K Vineeth, Chris Harris, Vinod Kumar, Toward Digital Twin-Enabled Venous Flow Modelling: Interactive Valve Geometry and Lab-on-Chip Generation Framework, Computers in Biology and Medicine (2026) Vol. 212, p. 111755.
Vinod Kumar, Vineeth V K, Christopher Harris, Arturo Rodriguez, Herb Janssen, Digital Twin Framework: Integrating Experimentation, Simulation, and AI for Patient-Specific Hemodynamics in Venous Valves, APS Division of Fluid Dynamics Annual Meeting, Nov 23-25, 2025, Houston, TX, United States.
Vyom Kumar, Aryan Singh, Vineeth V K, Arturo Rodriguez, Jeffrey H. Farris, Andrew R. Ybarra, Christopher Harris, Assimilated Physical Digital Twin of Venous Valve for Biological Flows, APS Division of Fluid Dynamics Annual Meeting, Nov 23-25, 2025, Houston, TX, United States.
Completed Projects 4:
TITLE:
A Web-Enabled Interface of the Coupled Tank Process for Monitoring and Control
U.S. Department of Energy through the Grande CARES Project (Award No. DE-NA0004108
Project Summary
This project develops a twin model of a coupled tank apparatus, enabling seamless integration between physical hardware and web-enabled user interaction.
The platform synchronizes live sensor measurements, control inputs, and computational models to create a cyber-physical environment where monitoring and experimentation occur simultaneously.
The physical system consists of interconnected water tanks instrumented with level sensors, pumps, and data-acquisition hardware.
These measurements are streamed to a web interface that mirrors the evolving hydraulic state of the system.
Completed Projects: 5
A Web-Based Digital Twin for Monitoring and Control of the UFactory Lite 6
Student Collaborator: Swetha Mandangi
U.S. Department of Energy through the Grande CARES Project (Award No. DE-NA0004108
Project Summary
This project develops a real-time digital twin and web-based control interface for the UFactory Lite 6, enabling seamless interaction between physical robotic hardware, computational models, and remote users.
The framework establishes a cyber-physical environment in which sensing, actuation, visualization, and prediction are unified within a single digital infrastructure.
RESULTS: Under-development
Current Project:
Title: Agentic AI for DVT Understanding and Risk Assessment
Details: Coming soon
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