Nikolas Karefyllidis, Ph.D.

Nikolas Karefyllidis, Ph.D.

Senior Engineer · Energy, Aerospace & Process Systems

ASME IGTI John P. Davis Award, 2025
Nikolas Karefyllidis, Ph.D.

About

Oxford PhD engineer and 2025 ASME IGTI John P. Davis Award recipient. I work across thermofluids, reacting-flow simulation, and scientific ML — and I take first-of-a-kind hardware the whole way: from concept and analysis through live pilot validation and patents to industrial deployment.

  • Scientific ML & AI
  • Multiphysics Simulation
  • Thermofluids & Reacting Flows
  • Aerospace & Propulsion
  • Chemical & Process Engineering
  • Energy Systems & Decarbonisation
  • Digital Twins & HPC
  • Uncertainty Quantification
  • Product Definition
  • Patents & IP

Experience

Senior Aerodynamics Engineer

Coolbrook Technologies

Aug 2023 – present

PhD-to-product on first-of-a-kind turbo-reactor platforms — technical product definition, live pilot validation, and patent filings on next-generation hardware. Built the simulation and evidence base (TB-scale HPC CFD, surrogates, Monte Carlo UQ) used for pilot investment and scale-up decisions with leadership and major petrochemical partners.

  • Took first-of-a-kind turbo-reactor hardware from design through live petrochemical pilot — reconciled models against real plant data.
  • Developed reduced-order and neural-network surrogates validated against high-fidelity CFD and pilot results — faster design iteration for product decisions.
  • Built Monte Carlo UQ across coupled mechanical, process, and controls subsystems — quantified operating-envelope risk before scale-up.
  • Co-led product definition with Product Manager; drafted patents on next-generation turbo-reactor platforms.
Sep 2024 – Sep 2025

Built hydrAI as independently developed scientific-ML IP — a proprietary framework for physics-informed surrogates on reacting flows. Extended the in-house multi-stage meanline toolchain with Cantera chemistry and holdout-validated models.

  • Built hydrAI — GeneralizedPFR Cantera data pipeline and NESP neuro-symbolic pyrolysis surrogates with symbolic rate closures.
  • Extended in-house multi-stage aerodynamics meanline code with reacting-flow chemistry and holdout-validated surrogates.
  • Co-supervised a DPhil researcher on experimental supersonic aerodynamics and heat transfer.
Sep 2019 – Aug 2023

Industry-sponsored PhD on novel turbomachine architectures for hydrocarbon cracking — proven in TB-scale simulation before product handoff.

  • Designed axial, radial, mixed-flow, and regenerative turbo-heaters/reactors; ran TB-scale HPC campaigns on ARC, CSD3, and Rescale.
  • Implemented a hybrid Spalart–Allmaras turbulence model (LES/URANS) in in-house CFD; calibrated coefficients via Bayesian optimisation.
  • Developed holdout-validated reduced-order aero-chemistry models linking flow states to reaction yields.
  • Co-supervised MSc students on CFD and turbomachinery projects.

Testing Engineer

Ansys, Inc.

Sep 2018 – Apr 2019

Shipped production-grade QA for commercial CFD — automated regression at scale for Ansys CFX and the turbomachinery toolchain.

  • Built automated regression test suites (>500 cases) for new CFX solver features; designed failure detection and triage workflows.

Spacecraft Propulsion Researcher

Surrey Space Centre (AAReST mission)

Sep 2016 – Jun 2017

Delivered propulsion engineering for the AAReST spacecraft with Caltech and NASA JPL — BEng thesis work and cross-institution milestone coordination across Surrey, Caltech, and JPL.

Education

Professional Development

  • 2026 Professional Certificate in Machine Learning and AI Imperial College London
  • 2024 AI/ML for Fluids FlowThermoLab

Awards

  • ASME IGTI John P. Davis Award (2025) — Lead author — 2025 recipient for novel turbo-heater aerodynamic design paper, recognised by ASME International Gas Turbine Institute
  • ASME Turbomachinery Committee Best Paper Award (2024) — Lead author — Journal of Turbomachinery
  • GPPS Conference Best Paper Award (2024) — Second author — turbo-reactor feed variability study

Patents

  • Next-Generation Turbo-Reactor Architecture for High-Temperature Industrial Processes Patent pending · Coolbrook Technologies · filed 2024

Selected Publications

  1. ASME JT

    A Novel Axial Energy-Imparting Turbomachine for High-Enthalpy Gas Heating: Robustness of the Aerodynamic Design ASME IGTI John P. Davis Award, 2025 · ASME Turbomachinery Best Paper, 2024

    Nikolas Karefyllidis, Dylan Rubini, Budimir Rosic, Liping Xu, Veli-Matti Purola

    ASME Journal of Turbomachinery, 2023

    Abs

    Demonstrates a novel repeating-stage axial turbo-heater architecture for high-temperature gas heating, presenting multistage CFD that confirms robust aerodynamic design despite uniform blade geometry and compact vaneless spacing.

    Bib 
    @article{Karefyllidis2023,
  author = {Karefyllidis, Nikolas and Rubini, Dylan and Rosic, Budimir and Xu, Liping and Purola, Veli-Matti},
  title = {A Novel Axial Energy-Imparting Turbomachine for High-Enthalpy Gas Heating: Robustness of the Aerodynamic Design},
  journal = {ASME Journal of Turbomachinery},
  volume = {146},
  number = {3},
  pages = {031005},
  year = {2023},
  doi = {10.1115/1.4063928},
}
    Award DOI HTML
  2. GPPS

    Decarbonisation of High-Temperature Endothermic Chemical Reaction Processes using a Novel Turbomachine: Robustness of the Concept to Feed Variability GPPS Best Paper Award, 2024

    Dylan Rubini, Nikolas Karefyllidis, Budimir Rosic, Liping Xu, Elina Nauha

    Journal of the Global Power and Propulsion Society, May 2024

    Abs

    Presents comprehensive analysis of turbo-reactor robustness and controllability across feeds, reaction stages, Mach regimes, and operating points for decarbonising high-temperature endothermic processes.

    Bib 
    @article{Rubini2024,
  author = {Rubini, Dylan and Karefyllidis, Nikolas and Rosic, Budimir and Xu, Liping and Nauha, Elina},
  title = {Decarbonisation of High-Temperature Endothermic Chemical Reaction Processes using a Novel Turbomachine},
  journal = {Journal of the Global Power and Propulsion Society},
  volume = {8},
  year = {2024},
  doi = {10.33737/jgpps/185623},
}
    DOI HTML
  3. Thesis

    The Aerodynamics of Turbomachines for High–Enthalpy Gas Heating

    Nikolas Karefyllidis

    University of Oxford (PhD Thesis), 2024

    Thesis
  4. GPPS

    A New Robust Regenerative Turbo-Reactor Concept for Clean Hydrocarbon Cracking

    Dylan Rubini, Nikolas Karefyllidis, Liping Xu, Budimir Rosic, Harri Johannesdahl

    Journal of the Global Power and Propulsion Society, 2022

    Abs

    Introduces a regenerative turbo-reactor concept to replace gas-fired radiant furnaces, achieving multistage heating within a compact toroidal vaneless configuration.

    DOI HTML
  5. Turbo Expo

    Accelerating the Development of a New Turbomachinery Concept in an Environment with Limited Resources and Experimental Data: Challenges

    Dylan Rubini, Nikolas Karefyllidis, Liping Xu, Budimir Rosic, Harri Johannesdahl

    Turbo Expo: Power for Land, Sea, and Air, 2022

    DOI HTML

Projects

PhD Research

Oxford PhD, 2019–2024

Novel Turbo-Heater & Turbo-Reactor Aerodynamics

Aerothermal design of axial, radial, mixed-flow, and regenerative turbo-heaters/reactors for hydrocarbon cracking — the core DPhil thesis on high-enthalpy gas heating for industrial decarbonisation. PhD work underpinned the next-generation turbo-reactor platform later validated at industrial pilot scale.

  • Turbomachinery
  • Supersonic Flows
  • Reacting Flows
PhD Thesis
Oxford PhD

PhD Simulation & Design Stack

In-house Fortran/MPI CFD with parallel LES on ARC and CSD3; hybrid SAS Spalart–Allmaras turbulence model calibrated via Bayesian optimisation; supersonic rotor and stator design codes using the method of characteristics for ultra-high-loading stages.

  • Fortran / OpenMPI
  • LES
  • HPC (ARC, CSD3, Rescale)
  • Method of Characteristics
Proprietary — details on reasonable request
Oxford PhD

Reduced-Order Aero-Chemistry Models

Coupled flow-field and yield prediction linking turbomachinery aerodynamics to pyrolysis chemistry; holdout-validated reduced-order models for rapid design screening.

  • Cantera
  • Surrogate Modelling
  • Reacting Flows
Proprietary — details on reasonable request

University of Oxford — Applied Research

Oxford (Visiting Researcher)

hydrAI

Proprietary scientific ML workspace — GeneralizedPFR (Cantera PFR training-data pipeline, HPC/SLURM) and NESP (neuro-symbolic pyrolysis surrogates and symbolic rate closures from physics-informed neural networks). PINN/RNN training, symbolic regression, and per-output holdout evaluation.

  • PyTorch
  • PINN / RNN
  • Symbolic Regression
  • Cantera
Proprietary — details on reasonable request
Oxford (Visiting Researcher)

Multi-Stage Meanline Design Code with Integrated Chemistry

Extended in-house multi-stage aerodynamics meanline code with integrated Cantera reacting-flow chemistry for rapid performance screening.

  • Meanline Methods
  • Cantera
  • Performance Screening
Proprietary — details on reasonable request

Open Source

Personal project

Bayesian Optimisation of Unknown Functions — NeurIPS 2020 BBO

GP–Bayesian optimisation of 8 unknown functions in the NeurIPS 2020 BBO challenge format; improved all 8 objectives.

  • Python
  • Bayesian Optimisation
GitHub

Contact

Based in Oxford, UK.

karefyllidis@gmail.com