cv

Career Highlights

Basics

Name Jayesh M. Dhadphale
PhD Candidate
Email [email protected]
Url https://www.jayeshdhadphale.com
Summary A researcher who works on thermofluids, computational science, machine learning, and nonlinear dynamics.

Education

  • 2019.08 - Present

    Chennai, India

    PhD
    Indian Institute Of Technology Madras
    Aerospace Engineering
    • Aerospace Propulsion
    • Acoustic Instabilities in Aerospace Propulsion
    • Mathematical Physics II
    • Acoustics and Noise Control
    • Dynamical Systems
    • Pattern Recognition and Machine Learning
    • Introduction of Research
  • 2015.08 - 2017.08

    Bengaluru, India

    Master of Engineering
    Indian Institute of Science, Bengaluru
    Aerospace Engineering
    • Fluid Dynamics
    • Mathematics for Aerospace Engineers
    • Flight and Space Mechanics
    • Flight Vehicle Structures
    • Mechanics and Thermodynamics of Propulsion
    • Navigation Guidance and Control
    • Experimental Techniques
    • Aerodynamics
    • Gas Dynamics
    • Computational Gas Dynamics
    • Guidance Theory and Applications
    • Applied Combustion
    • Advanced Combustion
    • Computation of Viscous flows
    • Flight Vehicle Design
  • 2011.07 - 2015.06

    Pune, India

    Bachelor of Engineering
    Savitribai Phule Pune University
    Mechanical Engineering

Work

  • 2018.01 - 2019.07
    Project Associate
    Indian Institute of Science, Bengaluru
    Developed a solver for stability analysis of thermoacoustic systems for extreme pressures using the generalized equation of state.
    • Thermoacoustics
    • Galerkin method
    • Acoustic modes
    • Soave-Redlich-Kwong (SRK) equation of state
    • Wave equation for genral state of equation

Awards

  • 2024.10.01
    Institute Research Award
    Indian Institute of Technology Madras
    To recognize and encourage exceptional research contributions by our scholars.'
  • 2024.10.01
    Prime Minister's Research Fellowship
    Ministry of Education, Government of India
    PMRF Scheme is designed to empower extraordinary talent to tackle the world's toughest research challenges, driving breakthroughs that shape industries and transform lives.

Publications

  •

2024

  1. Chaos
    mapsr.png
    Model adaptive phase space reconstruction
    Jayesh M. Dhadphale, K. Hauke Kraemer, Maximilian Gelbrecht, and 3 more authors
    Chaos: An Interdisciplinary Journal of Nonlinear Science, Jul 2024
    Featured Article DOI
    N/A Google Scholar citations
  2. AIP Adv.
    continuous_and_explosive.png
    Continuous and explosive synchronization transition in turbulent combustors
    Samarjeet Singh, Amitesh Roy, Jayesh M. Dhadphale, and 2 more authors
    AIP Advances, Jun 2024
    DOI
    N/A Google Scholar citations
  3. US patent
    US12025528-20240702-D00000.png
    Device and method to predict the onset of oscillatory instabilities in systems with turbulent flow
    Dhadphale Jayesh, Aguilar Ruiz Eustaquio, Rajasekharan Unni Vishnu, and 2 more authors
    Jul 2024

2023

  1. Chaos
    mean_field_model.png
    Mean-field model of synchronization for open-loop, swirl controlled thermoacoustic system
    Samarjeet Singh, Ankit Kumar Dutta, Jayesh M. Dhadphale, and 3 more authors
    Chaos: An Interdisciplinary Journal of Nonlinear Science, Apr 2023
    DOI
    N/A Google Scholar citations
  2. Chaos
    mitigation_of_tai.png
    Mitigation of limit cycle oscillations in a turbulent thermoacoustic system via delayed acoustic self-feedback
    Ankit Sahay, Abhishek Kushwaha, Samadhan A. Pawar, and 3 more authors
    Chaos: An Interdisciplinary Journal of Nonlinear Science, Apr 2023
    DOI
    N/A Google Scholar citations

2022

  1. Chaos
    neuralODE_paper1.png
    Neural ODE to model and prognose thermoacoustic instability
    Jayesh M. Dhadphale, Vishnu R. Unni, Abhishek Saha, and 1 more author
    Chaos: An Interdisciplinary Journal of Nonlinear Science, Jan 2022
    DOI
    N/A Google Scholar citations

Skills

Machine Learning & Data driven modeling
Neural Networks
Neural ODEs
Phase Space Reconstruction
Bayesian Regression and Classification
Sparse modeling
Combustion and simulation
Thermoacoustics
Thermoacoustics stability analysis for hight pressure conditions
Large eddy simulation (LES)
Navier-Stokes characteristics boundary conditions
Finite difference and Finite volume methods
Computer Tools and Languages
Python
PyTorch
MATLAB
C
C++
C#
GitHub
Linux
Ansys ICEM CFD
SOLIDWORKS
LATEX
Verilog: FPGA programming
Vivado
Unity
TensorFlow
Cuda C

Languages

Marathi
Native speaker
English
Fluent
Hindi
Fluent

Interests

Computational Science
CFD
Numerical Methods
Parallel Computing
GPU programming
High Performance Computing (HPC)
Machine learning
Gaussian Processes
Neural Networks
Neural ODEs
Bayesian methods
Sparse modeling
Generative models

References

Professor R. I. Sujith
Institute Professor and D. Srinivasan Institute Chair Professor,
Department of Aerospace Engineering,
Indian Institute of Technology Madras,
Chennai - 600 036, India
Dr. Vishnu R Unni
Assistant Professor,
Department of Mechanical & Aerospace Engineering,
Room: C-605, Academic Block C,
Indian Institute of Technology Hyderabad,
Kandi-502284, Sangareddy Telangana, India