Doctoral research portfolio

Dr. Krunal R. Panchal

PhD, Mechanical Engineering, IIT Madras (2026) Process engineering for reacting systems: chemistry, uncertainty, CFD, and machine-learning surrogates

I try to understand the structure of a problem before optimizing it. A rate constant is a range, not a value — uncertainty is a first-class citizen in everything I build, not an afterthought bolted on at the end. I value methods that are accurate and interpretable, reproducible, and computationally honest about their own cost. When something doesn’t work, I’d rather document why than quietly move on — the clearest example is a 115-run statistical audit of my own scientific-ML results that found a supposed “10× improvement” was mostly seed noise. That finding is now part of the record, not something I buried.

How the work fits together

One loop, from building a model to using it

The same six steps run through everything here, in the order of Bloom's revised taxonomy: remember the chemistry, understand what controls it, apply it in simulation, analyse the uncertainty, evaluate it against experiments, and create something new from it. MOSIAC is that loop for combustion chemistry; the last step, running the calibrated model inside CFD and teaching a neural network to stand in for it, is current research.

  1. Construct build or import the reaction mechanism
  2. Explain which reactions control which measurements
  3. Simulate reactors, flames, cross-checked solvers
  4. Quantify and reduce how sure are we; keep only what matters
  5. Calibrate tune against experiments with honest error bars
  6. Use CFD and Neural-ODE surrogates (current research)

Work

Projects

MOSIAC An open-source, uncertainty-quantified workbench for combustion kinetic mechanism optimization PANSOPHIA — In-House CFD & Multiphysics Solver A from-scratch Julia CFD/multiphysics library, with a Python frontend and a cross-engine geometry kernel, aimed at closing the gap between commerci... vZero — A Neural ODE Research Playground An interactive Neural ODE research environment unifying 44 hand-cloned training-script versions, with a live FastAPI+React GUI, a widened optimizer... flamelab A computer-vision instrument that measures flame length, width and flicker from pool-fire video in physical units with propagated uncertainty — reg... PAN-IIT-OSS — Openfirststeps A family of small, open teaching repositories, one per real-world goal, each built to show the path and leave the building to the learner dokimazo — A PIDO Optimization Workbench A dependency-light process-integration-and-design-optimization workbench with a plug-and-play graph IR, closed by a reinforcement-learning conforme... Math Visual Studio A local web app for visualising multivariable calculus, transformations, ODEs and PDEs, mechanisms, deformation and molecules PANSOPHIA numerics teaching figures Fifteen teaching figures on schemes, stability and accuracy, generated from the PANSOPHIA numerics stack PANSOPHIA geometry kernel A from-scratch signed-distance-field geometry kernel cross-checked against Gmsh and a PicoGK-compatible engine, with the GeoStudio GUI PANSOPHIA multiphysics test cases Cavity, conjugate heat transfer, boiling, FSI, structural, ignition and stochastic/UQ test figures from the PANSOPHIA solver

Papers

Selected publications

  1. CTM2024
    A fast uncertainty quantification methodology and sampling technique for joint probability distribution of the Arrhenius rate expression: a case study applied to H2/CO kinetic mechanism
    Krunal Panchal, Vaisakh Vasudavan, Sivaram Ambikasaran, and 1 more author
    Combustion Theory and Modelling, 2024
    DOI BibTeX
  2. 2023
    A multi-stage kinetic reaction optimization strategy applied to n-heptane combustion mechanism
    Krunal Panchal, Vaisakh Vasudavan, and Krithika Narayanaswamy
    In 14th Asia-Pacific Conference on Combustion (ASPACC), 2023
    BibTeX
  3. Accepted2026
    A Power-Mean (Hölder) Objective Function for Balancing Unequal Datasets in Combustion Kinetic Mechanism Optimization: Case Studies on Methyl Butanoate and n-Heptane
    Krunal R. Panchal and Krithika Narayanaswamy
    In 64th Symposium (Japanese) on Combustion, 2026
    Accepted