CV

Curriculum vitae, generated from _data/cv.yml.

Contact Information

Name Dr. Krunal R. Panchal
Professional Title PhD, Mechanical Engineering — Computational Methods for Complex Physical Systems
Email krunalpanchal1995@gmail.com
Location Dept. of Mechanical Engineering, IIT Madras, Chennai, Tamil Nadu 600036

Professional Summary

I develop fair multi-objective optimization, uncertainty-quantification and reduced-order/scientific-ML methods for expensive, stiff physical simulations, using combustion chemical kinetics and mechanism reduction as a primary proving ground. My PhD produced MOSIAC, an open-source workbench for uncertainty-aware combustion mechanism optimization, alongside hands-on experimental and numerical combustion work: pool-flame characterization (with computer-vision-driven video post-processing), downdraft gasification, and CFD.

Experience

  • 2026 - 2026

    Chennai, India

    Project Associate, Department of Mechanical Engineering
    Indian Institute of Technology Madras
    Shell-funded combustion project (PIs: Prof. V. Raghavan and Prof. Krithika Narayanaswamy), through 30 November 2026.
  • 2018 - 2026

    Chennai, India

    Research Scholar (PhD)
    Indian Institute of Technology Madras
    Developed MOSIAC (formerly RMIP), an open-source multi-objective optimization workbench for combustion kinetic-mechanism development, integrating uncertainty-quantified rate-constant calibration, stratified sampling and response-surface surrogates, alongside multi-stage kinetics-informed optimization and a Hölder/power-mean objective function for multi-dataset calibration.
    • Led design of the MUQ-SAC joint-Arrhenius uncertainty-quantification methodology (Combustion Theory and Modelling, 2024)
    • Joint pool-flame characterization work with Gagan Verma (rig: design → outsourced fabrication → commissioning → operation)
    • Decarbonisation Technology course project (Aug–Dec 2022, team of six): ANSYS Fluent study of H2/CH4 co-injection with pulverised coal in blast-furnace tuyeres — CO2 intensity fell from 0.121 to 0.067 g/kJ at 80% H2 substitution
    • Built flamelab, a computer-vision instrument measuring flame length, width and flicker from pool-flame video in physical units with propagated uncertainty — eight-run ensemble campaign, Hopf-sequence regime classification, thirteen analysis methods (~300 tests passing)
  • 2025 - 2026

    Chennai, India

    Project Associate — AI/ML for chess game analysis
    Indian Institute of Technology Madras
  • 2024 - 2025

    Chennai, India

    Project Assistant
    Indian Institute of Technology Madras
  • 2016 - 2018

    Ahmedabad, India

    Graduate Research Assistant (M.Tech)
    Nirma University

Education

  • 2018 - 2026

    Chennai, India

    PhD
    Indian Institute of Technology Madras
    Mechanical Engineering
    • Thesis: Development of a Fast, Robust, and Kinetics-Based Optimization Framework for Combustion Kinetic Models
    • Advisor: Prof. Krithika Narayanaswamy
    • Thesis submitted Oct 2025 · viva 12 May 2026 · degree conferred 16 Jul 2026
  • 2016 - 2018

    Ahmedabad, India

    M.Tech
    Nirma University, Institute of Technology
    Mechanical Engineering (Thermal Engineering)
    • Thesis: Effect of Steam and Catalyst with Lignite Feedstock on the Performance of Downdraft Gasifier
    • Awarded the ISTE National Award for Best M.Tech Thesis 2018 (First Prize)
  • 2012 - 2016

    Gujarat, India

    B.E.
    Government Engineering College, Modasa
    Mechanical Engineering

Teaching

Awards

  • 2018
    ISTE National Award for Best M.Tech Thesis 2018 — First Prize
    Indian Society for Technical Education

    Awarded for the M.Tech thesis on steam and catalytic downdraft gasification of lignite.

  • 2018
    MHRD (Government of India) PhD Scholarship
    Government of India

    PhD fellowship, IIT Madras.

Publications

Skills

Fair Multi-Objective Optimization (): Genetic algorithms, CMA-ES, gradient/NLLS (Levenberg-Marquardt, trust-region), Bayesian & GP optimization, surrogate/response-surface optimization
Uncertainty Quantification & Sensitivity Analysis (): Correlated-parameter UQ, local & Sobol global sensitivity analysis, Latin hypercube / Sobol / Monte Carlo sampling
Reduced-Order Modelling & Scientific ML (): Physics-informed neural networks, neural ODEs, ANN/response-surface surrogate and reduced-order models, PyTorch, scikit-learn
Simulation, Chemical Kinetics & Mechanism Reduction (): Cantera, ANSYS CHEMKIN-PRO, FlameMaster, OpenFOAM, ANSYS Fluent/Workbench, kinetic mechanism reduction
Programming (): Python (NumPy, SciPy, Matplotlib), MATLAB, C++, LaTeX/Beamer, Git
Quantum Chemistry (developing) (): Avogadro, Gaussian — geometry optimization, frequencies, partition functions, rate constants

Interests

Combustion Kinetics & Mechanism Reduction: Chemical kinetic mechanism development, mechanism reduction, ignition-delay and flame-speed validation
Fair Multi-Objective Optimization & Uncertainty: Multi-objective and multi-stage optimization, Bayesian uncertainty quantification
Reduced-Order Modelling & Scientific ML: Neural and response-surface surrogates for stiff dynamical systems
Experimental & Numerical Combustion: Pool-flame characterization, computer-vision flame measurement (flamelab), CFD and chemical-kinetics simulation of the same systems
Gasification: Steam/catalyst-assisted downdraft fixed-bed gasification, rig commissioning, syngas analysis
CFD: In-house CFD/multiphysics solver, reacting-flow and rig-design studies

Projects

  • 2018 - present
    MOSIAC

    Open-source, uncertainty-quantified workbench for combustion kinetic mechanism optimization (developed during the PhD; formerly named RMIP). Software paper in preparation for JOSS.

    • github.com/KrunalPanchal1995 — MOSIAC, MUQ-SAC, mechanism-optimization-suite