Computational Heat Transfer Laboratory · J. Mike Walker '66 Department of Mechanical Engineering

Muhammad Hasnain

PhD Candidate, Mechanical Engineering, Texas A&M University

Scientific machine learning for fluid flow and heat transfer

I develop machine learning models that predict fluid flow and heat transfer directly on engineering meshes and stay accurate when the geometry or operating conditions change. Paired with validated finite-volume solvers, they make design studies, optimization, and safety analysis practical at a fraction of the cost of repeated CFD, with applications in energy storage and fire safety.

Research focus

On the faculty job market. I expect to complete my PhD in May 2027 and am applying for tenure-track positions in computational mechanics, thermal-fluid sciences, and scientific machine learning.

Download CV (PDF) mhasnain5924117@tamu.edu
  • 6Journal articles
  • 96Citations
  • 4h-index
  • 20Manuscript reviews
Portrait of Muhammad Hasnain

About

I am a PhD candidate in the J. Mike Walker '66 Department of Mechanical Engineering at Texas A&M University, working with Prof. N. K. Anand in the Computational Heat Transfer Laboratory. My research sits at the intersection of scientific machine learning and computational transport phenomena: I build graph-based neural surrogates that respect conservation laws, learn from unstructured CFD meshes, and generalize across geometries and operating conditions, and I use them to accelerate design and analysis of thermal-fluid systems without giving up the reliability of first-principles solvers.

Before Texas A&M, I completed an MS in Mechanical Engineering at Georgia Southern University with Dr. Hayri Sezer in the Fire and Energy (FireGY) Laboratory, where I developed finite-volume models of coupled heat and mass transfer in metal hydride hydrogen storage reactors and fire-response models of gypsum board and tree stems that were validated against experiments and supported a National Institute of Justice-funded project. I am a first-generation college graduate, and mentoring students who are new to research is a central part of how I work.

Education

  1. 2024–2027 (expected)
    PhD, Mechanical Engineering, Texas A&M University (GPA 4.0/4.0)
    Advisor: Prof. N. K. Anand. Committee: Profs. Arun Srinivasa, Shuiwang Ji, and Dorrin Jarrahbashi
    Dissertation (anticipated): Development of Generalizable Graph-Based Deep Learning Models for Geometry-Aware Fluid Flow and Heat Transfer Applications
  2. 2022–2024
    MS, Mechanical Engineering, Georgia Southern University (GPA 4.0/4.0)
    Advisor: Dr. Hayri Sezer. Committee: Drs. David Calamas, Hossain Ahmed, and Jerry Hunter Mason
    Thesis: Mathematical Modeling of Coupled Heat and Mass Transfer in Metal-Hydride Hydrogen Storage Systems
  3. 2017–2021
    BS, Mechanical Engineering, Ghulam Ishaq Khan Institute of Engineering Sciences and Technology (GIKI), Pakistan
    Exchange semester at Western Carolina University (Spring 2020) as a U.S. Department of State Global UGRAD scholar

Research

High-fidelity simulation of transport phenomena is accurate but too slow to repeat across the many geometries and operating conditions that design, optimization, and safety analysis demand. My work makes physics-consistent learned models a trusted complement to numerical solvers, and applies validated finite-volume multiphysics models to fire safety and energy storage problems. It is organized in four areas; all figures below are taken from my own papers and presentations, and each opens at full size when clicked.

Area 1

Geometry-aware, physics-regularized graph learning for thermal-fluid systems

I designed graph neural network surrogates that operate directly on unstructured CFD meshes. The residual multilayer-perceptron graph convolutional network (ResMLP-GCN), published in Physics of Fluids (2025), takes Reynolds number and geometric descriptors as inputs and predicts coupled velocity fields for the double lid-driven cavity and backward-facing step. Trained on Re 100–2000, it reproduced the dominant flow structures at Re 3000, well beyond the training range. I then developed a physics-regularized surrogate, now under review in Physics of Fluids, that was trained on a single step height and predicted reattachment lengths and velocity fields for step heights varied by ±40%, the property required for geometry optimization and rapid design screening. I presented this work at WCCM-ECCOMAS 2026 and ASME IMECE 2025.

ResMLP-GCN architecture diagram above OpenFOAM versus GNN velocity fields and absolute error maps for a double lid-driven cavity at Re 2000 and a backward-facing step at Re 200
ResMLP-GCN message-passing architecture (top) and OpenFOAM vs. GNN velocity fields with absolute error for the double lid-driven cavity (Re = 2000) and backward-facing step (Re = 200). From Hasnain et al., Phys. Fluids 2025.

Area 2

Fire safety: thermal response of building materials and vegetation

In the Fire and Energy Laboratory at Georgia Southern, I built finite-volume models of coupled heat and mass transfer with reaction kinetics in porous solids exposed to fire. For gypsum board, the most common wall lining, I developed a three-dimensional dehydration and calcination model under arbitrary heat-flux configurations, validated it against cone-calorimeter measurements at four depths, and showed how calcination depth can be related to the heat-flux history a wall experienced, which gives fire investigators a quantitative tool (Int. J. Thermal Sciences, 2026; project funded by the National Institute of Justice). For vegetation, I co-developed a predictive heat transfer model of tree stems under surface fire that resolves bark and wood layers with radially varying moisture, matched Douglas-fir experiments more closely than FireStem2D, and converted the temperature history into cell-death rate and necrotic depth for symmetric and one-sided exposures and for several species and moisture contents (Int. Commun. Heat Mass Transfer, 2026).

Four panels: schematic of a gypsum slab with imposed heat flux and convective and radiative losses; predicted versus measured temperatures at four depths under 50 kilowatts per square metre; temperature field in a tree stem cross section after one-sided fire exposure; and predicted necrotic depth around the stem
(a) Gypsum slab with imposed heat flux and convective and radiative losses; (b) predicted vs. measured temperatures at 0, 4, 8, and 12 mm depth under 50 kW/m² (Int. J. Therm. Sci. 2026); (c) tree stem temperature at the end of a one-sided fire exposure and (d) the resulting necrotic depth (Int. Commun. Heat Mass Transfer 2026).

Area 3

Energy storage and conversion systems: hydrogen storage and lithium-ion safety

For metal hydride hydrogen storage, I formulated and solved coupled heat, mass, and momentum transfer with absorption and desorption kinetics in finned and jacketed reactors, validated the model against equilibrium-pressure, reacted-fraction, and temperature measurements from three independent experiments, and quantified how supply pressure, coolant temperature, and reactor dimensions set charging time (Int. J. Hydrogen Energy, 2024; MS thesis). I then wrote a comprehensive review that consolidates two decades of reactor-scale modeling and identifies the open problems in coupled kinetics, heat management, and reactor geometry (Renewable and Sustainable Energy Reviews, 2026). For lithium-ion batteries, I co-developed a finite-volume thermal runaway model with four-step decomposition kinetics and inter-cell contact resistance that reproduced oven-test critical ambient temperatures for single cells and four-cell ensembles to within 1 °C of experiment and extended it to a 16-cell module (ASME IMECE 2023).

Four panels: cross-sectional schematic of a metal hydride reactor with heat-transfer-fluid jacket; average reacted fraction versus time compared with experiment; schematic of a stack of prismatic lithium-ion cells; and temperature profiles across a sixteen-cell module at successive times
(a) Cross-section of a jacketed metal hydride reactor; (b) predicted vs. measured average reacted fraction during charging (Int. J. Hydrogen Energy 2024); (c) stack of prismatic lithium-ion cells; (d) temperature across a 16-cell module approaching thermal runaway (ASME IMECE 2023).

Area 4

Scalable, physics-informed PDE learning and hybrid solver-ML workflows

I work on the infrastructure that makes learned PDE models usable at scale. I developed a solver-free, method-of-manufactured-solutions data-generation framework for training and benchmarking neural operators across PDE classes, parameter ranges, and boundary conditions (ASME IMECE 2026, to appear), and built on it to propose MIGONet, a multiple-input graph neural operator trained on solver-free discrete manufactured solutions (Transport Phenomena, 2026). I also studied stable autoregressive rollout of graph surrogates for transient advection-diffusion systems. As part of the ShockCast team, I contributed to a two-phase framework that learns adaptive time-step sizes for supersonic flows with shocks, published at ICLR 2026 with code in the open-source AIRS library. Earlier, I implemented physics-informed neural networks in Julia SciML for transient scalar transport and coupled learned models with OpenFOAM.

Three plots of temperature versus time at different probe locations comparing finite-element solution and GNN autoregressive prediction, with the prediction zone extending beyond the training zone
Autoregressive GNN rollout of a transient advection-diffusion problem with nonlinear convective and radiative sources; predictions remain accurate well past the training window.

Selected projects

Each project below opens with a thirty-second animated summary of the study (illustrative, from a simplified model; captions included). Switch to Paper figure to see the reported result.

Geometry optimization with geometry-generalizable surrogates

A physics-regularized GNN trained on one backward-facing step geometry predicted reattachment lengths across step heights varied by ±40% and Reynolds numbers 125–375, mostly within 10% of OpenFOAM, making shape sweeps and geometry optimization loops feasible at a fraction of CFD cost.

Preprint (SSRN) · under review, Physics of Fluids; WCCM-ECCOMAS 2026 talk.

Full HD (MP4)

Gypsum board under non-uniform fire exposure

The three-dimensional dehydration and calcination model applied to a Gaussian heat-flux footprint on a 12 mm board. Temperature histories at the exposed, middle, and unexposed surfaces show how localized exposure produces steep in-plane gradients, the link between observed calcination patterns and the location and intensity of the exposure.

Int. J. Thermal Sciences 221, 110457 (2026) · Top Eagle Award poster, 2024.

Full HD (MP4)

Fire-induced injury and mortality in tree stems

A two-dimensional heat transfer model of a tree stem with bark and wood layers, radially varying moisture, and a measured surface-fire heat flux. Temperature evolution under one-sided exposure was converted into tissue death rate and necrotic depth, 9.5 mm for uniform exposure and 4.4 mm for one-sided exposure, and compared across species and moisture contents to support prescribed-burn planning and post-fire mortality assessment.

Int. Commun. Heat Mass Transfer 180, 112653 (2026) · ESSCI 2024 presentation.

Full HD (MP4)

Metal hydride hydrogen storage reactors

Reacted-fraction and temperature fields during charging of a finned reactor, with parametric sweeps over supply pressure and coolant temperature. The study quantified how these operating parameters and the reactor dimensions set charging time, informing safer and faster hydrogen storage design.

Int. J. Hydrogen Energy 71 (2024) · IMECE 2023 · RSER review (2026)

Full HD (MP4)

Further projects

Parametric extrapolation with ResMLP-GCN

Mean squared error and mean percentage error of the GNN versus Reynolds number, low in the interpolation range and rising smoothly in extrapolation

Error growth of the ResMLP-GCN surrogate for the double lid-driven cavity as Reynolds number moves from the training range (100–2000) into extrapolation (2000–3000). The surrogate degraded smoothly rather than failing abruptly, a prerequisite for trustworthy use in design.

Physics of Fluids 37, 107138 (2025)

Thermal runaway in lithium-ion batteries

Central cell temperature versus time for a lithium-ion cell in an oven test, comparing the current model with COMSOL, GPYRO, and experiment

A finite-volume model with four-step decomposition kinetics and inter-cell contact resistance reproduced oven-test critical ambient temperatures for single cells and four-cell ensembles to within 1 °C of experiment, matching or improving on COMSOL and GPYRO benchmarks, and predicted the onset time and critical temperature of a 16-cell module.

ASME IMECE 2023 · ESSCI 2024 and U.S. National Combustion Meeting 2023 presentations.

Future directions

  • Graph neural operators with built-in conservation. Discretization-aware architectures whose message passing mirrors finite-volume flux balances, so that learned surrogates conserve mass and energy by construction and can be embedded in geometry optimization loops.
  • Physics-informed digital twins for energy storage and thermal safety. Hybrid models for hydrogen storage reactors and battery packs that assimilate sparse sensor data and flag thermal-runaway precursors in real time.
  • Hybrid SciML-FVM solvers. Learned closures, preconditioners, and adaptive time-stepping coupled with OpenFOAM to accelerate, rather than replace, trusted CFD workflows.

Software and methods

  • Graph and CNN surrogate pipelines in PyTorch and PyTorch Geometric, with OpenFOAM mesh and field ingestion.
  • Contributor to ShockCast in the AIRS open-source library.
  • In-house finite-volume solvers (Python, MATLAB) for coupled heat, mass, and momentum transfer with reaction kinetics in porous media; lattice Boltzmann wildfire models.
  • Method-of-manufactured-solutions data generator for benchmarking neural operators.
  • Physics-informed neural networks in Julia SciML; validation against thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and cone-calorimeter data.
  • OpenFOAM Foundation, Advanced, Essential CFD, and Applied CFD certifications (CFD Direct, 2025).
  • Tools: OpenFOAM, ANSYS (structural and thermo-fluids), MATLAB, Python, Julia, C++; SolidWorks, Creo, and Fusion 360 for geometry; experimental familiarity with TGA, DSC, and PIV.

Collaborations

Co-authors and proposal collaborators come from the following institutions.

  • Texas A&M UniversityMechanical Engineering; Computer Science and Engineering; Aerospace Engineering
  • Georgia Southern UniversityFire and Energy (FireGY) Laboratory
  • Worcester Polytechnic InstituteFire Protection Engineering
  • Eastern Kentucky UniversityFire and forensic thermal modeling
  • West Virginia UniversityMechanical and Aerospace Engineering
  • Idaho National Laboratory and General AtomicsDOE proposal collaborations

Publications

Citation counts are on Google Scholar and ORCID. My name is in bold in the author lists below.

Selected publications

  1. M. Hasnain, N. K. Anand, A. Srinivasa. MIGONet: A multiple-input graph neural operator with solver-free discrete manufactured-solution training. Transport Phenomena, 2026. In print doi:10.1515/tp-2026-0133 · arXiv:2611.05876

    A graph neural operator that takes several input fields at once and learns entirely from manufactured solutions, so no numerical solver is needed to produce its training data.

  2. J. Helwig, S. S. Adavi, X. Zhang, Y. Lin, F. S. Chim, L. T. Vizzini, H. Yu, M. Hasnain, S. K. Biswas, J. J. Holloway, N. Singh, N. K. Anand, S. Guhathakurta, S. Ji. A two-phase deep learning framework for adaptive time-stepping in high-speed flow modeling. International Conference on Learning Representations (ICLR), 2026. OpenReview · arXiv:2506.07969

    First learning framework for shock-dominated high-speed flows with learned adaptive time-stepping; datasets and code released openly.

  3. M. Hasnain, H. Sezer, S. P. Kozhumal. Predicting thermal response of gypsum board under various heat flux configurations: A three-dimensional mathematical model. International Journal of Thermal Sciences, 221, 110457, 2026. doi:10.1016/j.ijthermalsci.2025.110457

    Experimentally validated 3D dehydration and calcination model that lets fire investigators relate observed calcination depth to heat-flux history.

  4. M. Hasnain, H. Sezer, J. H. Mason. Mathematical modeling of heat and mass transfer in metal hydride hydrogen storage systems: A comprehensive review. Renewable and Sustainable Energy Reviews, 226, 116294, 2026. doi:10.1016/j.rser.2025.116294

    Consolidates two decades of reactor-scale modeling and identifies open problems in coupled kinetics, heat management, and reactor geometry.

  5. M. Hasnain, N. K. Anand, A. Srinivasa, P. Kumar. A novel residual multilayer perceptron-based graph convolutional network for modeling heat transfer and fluid flow. Physics of Fluids, 37(10), 107138, 2025. doi:10.1063/5.0292956

    Introduced a residual graph convolutional architecture that predicts coupled velocity, pressure, and temperature fields directly on unstructured CFD meshes and extrapolates in Reynolds number.

Journal articles 6

  1. M. Hasnain, N. K. Anand, A. Srinivasa. MIGONet: A multiple-input graph neural operator with solver-free discrete manufactured-solution training. Transport Phenomena, 2026. In print doi:10.1515/tp-2026-0133 · arXiv:2611.05876
  2. M. U. Khan, M. Hasnain, H. Sezer, S. P. Kozhumal, M. K. Selvaraj, A. Simeoni. Predictive heat transfer model for fire-induced injuries in tree stems. International Communications in Heat and Mass Transfer, 180 (Part 3), 112653, 2026. doi:10.1016/j.icheatmasstransfer.2026.112653
  3. M. Hasnain, H. Sezer, S. P. Kozhumal. Predicting thermal response of gypsum board under various heat flux configurations: A three-dimensional mathematical model. International Journal of Thermal Sciences, 221, 110457, 2026. doi:10.1016/j.ijthermalsci.2025.110457
  4. M. Hasnain, H. Sezer, J. H. Mason. Mathematical modeling of heat and mass transfer in metal hydride hydrogen storage systems: A comprehensive review. Renewable and Sustainable Energy Reviews, 226, 116294, 2026. doi:10.1016/j.rser.2025.116294
  5. M. Hasnain, N. K. Anand, A. Srinivasa, P. Kumar. A novel residual multilayer perceptron-based graph convolutional network for modeling heat transfer and fluid flow. Physics of Fluids, 37(10), 107138, 2025. doi:10.1063/5.0292956
  6. M. Hasnain, H. Sezer, J. H. Mason. Modeling heat and mass transfer in metal hydride hydrogen storage systems: Impact of operating parameters and reactor geometry. International Journal of Hydrogen Energy, 71, 1045–1055, 2024. doi:10.1016/j.ijhydene.2024.05.311

Refereed conference papers 4

  1. M. Hasnain, N. K. Anand, A. Srinivasa. A manufactured-solution-based data generation framework for machine learning models of transport PDEs. Proceedings of the ASME International Mechanical Engineering Congress and Exposition (IMECE 2026), Fluids Engineering, Vancouver, BC, Canada, November 8–12, 2026. To appear
  2. J. Helwig, S. S. Adavi, X. Zhang, Y. Lin, F. S. Chim, L. T. Vizzini, H. Yu, M. Hasnain, S. K. Biswas, J. J. Holloway, N. Singh, N. K. Anand, S. Guhathakurta, S. Ji. A two-phase deep learning framework for adaptive time-stepping in high-speed flow modeling. International Conference on Learning Representations (ICLR), 2026. OpenReview · arXiv:2506.07969
  3. M. Hasnain, S. Khan, M. A. Ezazi, H. Sezer. Modeling heat and mass transfer in metal hydride-based hydrogen storage systems using the finite volume method. Proceedings of the ASME International Mechanical Engineering Congress and Exposition (IMECE 2023), Vol. 10, V010T11A047, New Orleans, LA, 2023. doi:10.1115/IMECE2023-112874
  4. S. Khan, S. Anwar, J. Casa, M. Hasnain, H. Ahmed, H. Sezer. Modeling thermal runaway in prismatic lithium-ion batteries. Proceedings of the ASME International Mechanical Engineering Congress and Exposition (IMECE 2023), Vol. 10, V010T11A048, New Orleans, LA, 2023. doi:10.1115/IMECE2023-113787

Preprints and manuscripts under review 2

  1. M. Hasnain, N. K. Anand, P. Kumar, A. Srinivasa, S. Ji. A physics-regularized graph neural surrogate for parametric and geometric extrapolation in backward-facing step flow. Under review, Physics of Fluids, 2026. SSRN doi:10.2139/ssrn.6446623
  2. M. Hasnain, H. Sezer, J. H. Mason. Modeling heat and mass transfer in metal hydride hydrogen storage reactors: Impact of operating conditions and reactor size on hydrogen desorption. Under review, International Journal of Hydrogen Energy. SSRN 4898120
Conference presentations and abstracts 8
  1. M. Hasnain, N. K. Anand, P. Kumar, A. Srinivasa, S. Ji. A physics-assisted geometry-generalizable graph convolutional network for fluid flow. 17th World Congress on Computational Mechanics and 10th European Congress on Computational Methods in Applied Sciences and Engineering (WCCM-ECCOMAS 2026), CFD and Fluid-Structure Interaction track, Munich, Germany, July 19–24, 2026.
  2. M. Hasnain, N. K. Anand, A. Srinivasa, P. Kumar. Application of graph neural networks for heat transfer and fluid flow problems. ASME IMECE 2025, Machine Learning and Quantum Computing for Fluids track, Memphis, TN, November 2025.
  3. M. Hasnain, R. Paye, T. Borth, G. E. Gorbett, S. P. Kozhumal, H. Sezer. Three-dimensional mathematical modeling of heat and mass transfer during calcination of gypsum board exposed to fire. Eastern States Section of the Combustion Institute (ESSCI) Spring Technical Meeting, Athens, GA, March 2024.
  4. S. Khan, M. Hasnain, J. Casa, A. Said, V. Akkerman, M. Selvaraj, A. Simeoni, H. Sezer. Mathematical modeling of heat-induced decomposition kinetics leading to thermal runaway in lithium-ion batteries. ESSCI Spring Technical Meeting, Athens, GA, March 2024.
  5. M. Usman, M. Hasnain, S. Khan, A. Simeoni, R. Ziazi, H. Sezer. Mathematical model for predicting injuries and temperature distributions in stem exposed to fire. ESSCI Spring Technical Meeting, Athens, GA, March 2024.
  6. A. Idris, S. Khan, M. Hasnain, M. Selvaraj, A. Simeoni, H. Sezer. Numerical modeling of spontaneous ignition in large coal stockpiles using finite volume method. ESSCI Spring Technical Meeting, Athens, GA, March 2024.
  7. M. Hasnain, R. Paye, J. Casa, T. Borth, G. E. Gorbett, S. P. Kozhumal, H. Sezer. 3D mathematical model for heat and mass transfer mechanisms in gypsum board exposed to fire. 13th U.S. National Combustion Meeting, College Station, TX, March 2023. NIJ library record
  8. S. Khan, M. Hasnain, A. Liaqat, V. Akkerman, H. Ahmed, S. P. Kozhumal, H. Sezer. The self-heating ignition of lithium-ion batteries: A comparative study of COMSOL and GPYRO models with finite volume toolbox. 13th U.S. National Combustion Meeting, College Station, TX, March 2023.
Posters 10
  1. M. Hasnain, H. Sezer. Mathematical modeling of heat and mass transfer in metal-hydrides for safer and more efficient hydrogen storage reactors. 9th Annual Texas A&M Conference on Energy, College Station, TX, September 2025.
  2. M. Hasnain, M. U. Khan, H. Sezer. Three-dimensional multiphysics modeling of heat and mass transfer during calcination of gypsum board for forensic fire investigations. Georgia Southern University Student Research Symposium, Statesboro, GA, April 2024. Top Eagle Award, first place among 176 posters.
  3. M. Hasnain, H. Sezer. Mathematical modeling of coupled heat and mass transport in metal-hydrides for safer and more efficient hydrogen storage systems. Georgia Southern University Student Research Symposium, Statesboro, GA, April 2024. Georgia Power Innovation Award, second place.
  4. M. Hasnain, H. Sezer. Solving transient advection-diffusion equations using PINNs and the finite volume method. Georgia Southern University Student Research Symposium, Statesboro, GA, April 2024.
  5. P. D. Castillo, S. Khan, M. Hasnain, H. Sezer. An immersed boundary method for drag coefficient calculations in complex rigid and flexible vegetation. Georgia Southern University Student Research Symposium, Statesboro, GA, April 2024.
  6. J. Kruger, S. Khan, M. Hasnain, H. Sezer. Simulation of two pool fires converging using FDS and applications with wildfires. Georgia Southern University Student Research Symposium, Statesboro, GA, April 2024.
  7. M. Hasnain, H. Sezer. A diffusion-based mathematical modeling of hyperbaric oxygen therapy for chronic wounds. Georgia Southern University Student Research Symposium, Statesboro, GA, April 2023. SALT Research Award, second place.
  8. M. Hasnain, H. Sezer. Modeling and optimization of metal hydride based hydrogen storage systems. Georgia Southern University Student Research Symposium, Statesboro, GA, April 2023. SALT Research Award, third place.
  9. S. Khan, M. Hasnain, H. Sezer. Mathematical modeling of thermal runaway in lithium-ion batteries. Georgia Southern University Student Research Symposium, Statesboro, GA, April 2023. Gulfstream Aerospace Research Award, third place.
  10. S. Khan, M. Hasnain, H. Sezer. A mathematical model for thermal metamaterials. Georgia Southern University Student Research Symposium, Statesboro, GA, April 2023.
Muhammad Hasnain beside his poster on coupled heat and mass transfer in metal hydrides at the Texas A&M Conference on Energy
Texas A&M Conference on Energy poster session.
Muhammad Hasnain beside his award-winning poster on three-dimensional modeling of gypsum board calcination at the 2024 Georgia Southern Student Research Symposium
Georgia Southern Student Research Symposium, April 2024 (Top Eagle Award).
Muhammad Hasnain and Dr. Hayri Sezer beside the hyperbaric oxygen therapy modeling poster at the 2023 Georgia Southern Student Research Symposium
With Dr. Hayri Sezer, Georgia Southern Student Research Symposium, April 2023.
Muhammad Hasnain beside his metal hydride hydrogen storage optimization poster at the 2023 Georgia Southern Student Research Symposium
Metal hydride hydrogen storage poster, April 2023.

Teaching and Mentoring

I teach the way I was taught best: by meeting students where they are, connecting every derivation to a physical consequence they can picture, and building a classroom in which asking a basic question is normal. My goal is for students to leave a course able to set up a problem from first principles, choose a numerical method deliberately, and check whether the answer makes physical sense.

Pedagogical training

  • Academy for Future Faculty Fellow, Texas A&M Center for Teaching Excellence, 2026–2027 (in progress). Year-long program on evidence-based teaching, course design, and a teaching portfolio with philosophy statement, sample syllabus, and course blueprint.
  • Teaching Assistant Institute, Texas A&M Center for Teaching Excellence, August 2024. Classroom management, inclusive instruction, and academic-integrity protocols.
  • Center for the Integration of Research, Teaching and Learning (CIRTL) Network programming.
Muhammad Hasnain with Dr. Tatiana Erukhimova after her Academy for Future Faculty seminar on student engagement
With Dr. Tatiana Erukhimova after her Academy for Future Faculty seminar on student engagement, whose approach to active lecturing informs how I plan my own classes.

Courses

CourseRole and scopeInstitution, term
MEEN 344 Fluid Mechanics Graduate Teaching Assistant for 90+ undergraduates; delivered lectures in the professor's absence, held office hours, and managed grading for all assignments and examinations Texas A&M University, Fall 2024
MENG 7136 Mechatronics I Laboratory Laboratory Instructor; supervised graduate lab sessions on sensors, actuators, instrumentation, and data acquisition Georgia Southern University, 2023–2024
MENG 4210 Energy Science Laboratory Laboratory Instructor; experiments reinforcing fluid mechanics, thermodynamics, and heat transfer; data analysis and report writing Georgia Southern University, 2023–2024
ENGR 2139 Numerical Methods in Engineering Graduate Teaching Assistant; linear systems, regression, error analysis, and MATLAB implementations Georgia Southern University, 2023–2024
ENGR 2112 Solid Modeling and Analysis Graduate Teaching Assistant; SolidWorks modeling, assemblies, basic structural and flow simulation, design for manufacturing Georgia Southern University, 2023–2024
Pre-engineering entrance examination program Instructor; taught physics and mathematics preparation for Pakistan's ETEA engineering entrance examination Orbit Coaching Academy, Pakistan, Summer 2022

Mentoring

  • Research mentor, FireGY Laboratory, Georgia Southern (2022–2024). Trained undergraduate and graduate researchers in finite-volume modeling, running a hands-on workshop series with the open-source FVTool toolbox to solve diffusion and diffusion-advection problems before moving to in-house solvers. Mentees co-authored four posters at the 2024 Student Research Symposium and two conference abstracts.
  • Student mentor, Mentor Collective, Georgia Southern (2023–2024). Guided new university students through academic planning, research opportunities, and campus engagement.
Muhammad Hasnain with his master's thesis committee after his defense at Georgia Southern University
With my MS thesis committee after the defense, Georgia Southern, June 2024.
FireGY Laboratory members with Dr. Hayri Sezer in front of their posters at the 2023 Georgia Southern Student Research Symposium
FireGY Laboratory at the 2023 Student Research Symposium.
FireGY Laboratory members at the 13th U.S. National Combustion Meeting in College Station
FireGY Laboratory at the 13th U.S. National Combustion Meeting, March 2023.

Talks and Presentations

Invited

  • Apr 2026
    Invited workshop, Research Excellence Series: Roadmap to Publication, Undergraduate Research Group (UROG), GIKI, Pakistan. "The Blueprint: Methodology and Experimental Design."
  • Jan 2026
    Use-Inspired Spotlight presentation, RAISE AI Bridge Summit, Texas A&M University, College Station, TX. Graph neural networks for CFD: domain challenges and AI-driven modeling opportunities.

Contributed

  • Jul 2026
    WCCM-ECCOMAS 2026, Munich, Germany. A physics-assisted geometry-generalizable graph convolutional network for fluid flow.
  • Nov 2025
    ASME IMECE 2025, Memphis, TN. Application of graph neural networks for heat transfer and fluid flow problems.
  • Mar 2024
    ESSCI Spring Technical Meeting, Athens, GA. Three-dimensional modeling of gypsum board calcination (presenter), plus three co-authored presentations on lithium-ion thermal runaway, tree-stem fire injury, and coal stockpile self-ignition.
  • Nov 2023
    ASME IMECE 2023, New Orleans, LA. Modeling heat and mass transfer in metal hydride-based hydrogen storage systems using the finite volume method.
  • Mar 2023
    13th U.S. National Combustion Meeting, College Station, TX. 3D mathematical model for heat and mass transfer mechanisms in gypsum board exposed to fire.
Opening slide of Muhammad Hasnain's WCCM-ECCOMAS 2026 talk: High-fidelity CFD is accurate and prohibitively slow to repeat
WCCM-ECCOMAS 2026, Munich: motivating physics-regularized graph surrogates.
Muhammad Hasnain in front of the WCCM-ECCOMAS 2026 banner in Munich
At WCCM-ECCOMAS 2026, Munich.
Muhammad Hasnain presenting at the podium at WCCM-ECCOMAS 2026
Presenting at WCCM-ECCOMAS 2026.
Muhammad Hasnain presenting the gypsum board calcination model at the 2024 ESSCI Spring Technical Meeting
ESSCI Spring Technical Meeting, Athens, GA, March 2024.

Awards and Funding

Honors and awards

  • 2026Research and Presentation Travel Award ($1,000) and Child Care Travel Award ($750), Graduate and Professional School, Texas A&M University, for WCCM-ECCOMAS 2026, Munich.
  • 2025Graduate Student Travel Award ($750), J. Mike Walker '66 Department of Mechanical Engineering, Texas A&M University, for ASME IMECE 2025.
  • 2024Top Eagle Award and Best Graduate Student Award ($500), Georgia Center of Innovation, Georgia Southern University Student Research Symposium: first place in the graduate research category among 176 posters.
  • 2024Innovation Award, second place ($350), Georgia Power, Georgia Southern University Student Research Symposium.
  • 2023Graduate Student Organization Research Award ($750) and Travel Grant for IMECE 2023, Georgia Southern University.
  • 2023SALT Research Awards (second and third place) and Gulfstream Aerospace Research Award (third place), Georgia Southern University Student Research Symposium.
  • 2020Global Undergraduate Exchange Program (Global UGRAD) Scholar, U.S. Department of State; Leadership, Engagement, and Action for Pakistan (LEAP) Institute, George Mason University.
  • 2017–2021Khyber Pakhtunkhwa Chief Minister Merit Scholarship and Dean's Honor Roll in all eight semesters, GIKI.
  • 20177th position nationally in the ETEA engineering entrance examination, Pakistan, with merit prizes from Orbit Coaching Academy and Quaid-e-Azam Group of Schools and Colleges.

Research proposals

Proposals I helped conceive and write. Full titles and amounts are shown only for awarded projects.

  • Awarded (2023). National Institute of Justice, U.S. Department of Justice. Experimental and Numerical Investigations for the Development and Validation of Thermo-chemistry Models and Property Databases for Selected Wall Lining Materials under Fire Exposure ($290,289). PI: Hayri Sezer. My role: concept development, mathematical modeling, and proposal writing. Resulting outputs: Int. J. Thermal Sciences 221 (2026) and two NIJ library records.
  • Submitted (2026). U.S. Department of Energy, Consolidated Innovative Nuclear Research (CINR). Geometry-generalizable graph neural network framework for thermal-hydraulic design optimization. PI: N. K. Anand. My role: concept development, methodology formulation, and proposal writing.
  • Submitted (2026). U.S. Department of Energy, CINR. Efficient large eddy simulation framework. PI: N. K. Anand. My role: literature review, conceptual development, and proposal writing.
  • Submitted (2024). NASA. Multiphysics, multiscale modeling of in-space welding and additive manufacturing. PI: Hayri Sezer. My role: proposal draft preparation and conceptualization.
Muhammad Hasnain and Dr. Hayri Sezer holding the Top Eagle Award certificate and ribbon at Georgia Southern University
Top Eagle Award with Dr. Hayri Sezer, April 2024.
Muhammad Hasnain receiving research awards on stage at the 2024 Georgia Southern Student Research Symposium
Award ceremony, 2024 Student Research Symposium.
Muhammad Hasnain holding two award certificates and ribbons at the 2023 Georgia Southern Student Research Symposium
SALT and Gulfstream Aerospace research awards, April 2023.

Service and Professional Activities

Peer review, memberships, and credentials

  • Reviewer, International Journal of Hydrogen Energy (9 manuscripts, 2024–2026).
  • Reviewer, Physics of Fluids (4 manuscripts, 2025–2026).
  • Reviewer, ASME Journal of Thermal Science and Engineering Applications (3 manuscripts, 2025–2026).
  • Reviewer, International Journal of Thermal Sciences and Computers & Fluids (2026).
  • Member, Texas A&M Energy Research Society, since 2024.
  • Member, American Society of Mechanical Engineers (ASME), since 2023.
  • Member, The Combustion Institute, since 2023.
  • Certified Mechanical Engineer, Pakistan Engineering Council, since 2021.

Outreach and community

  • Invited workshop for the Undergraduate Research Group (UROG), GIKI, April 2026.
  • Volunteer, Texas Science and Engineering Fair, Spark! PK–12 Engineering Education Outreach, Texas A&M Engineering, March 2026.
  • Research mentor, FireGY Laboratory, Georgia Southern University, 2022–2024.
  • Student mentor, Mentor Collective, Georgia Southern University, 2023–2024.
  • Member, Project Topi, GIKI, 2017–2021: educational support for underprivileged children, anti-child-labor awareness, and blood-donation drives with the Pakistan Red Crescent Society.
  • Community volunteer, Community Table, Sylva, NC, Spring 2020 (Global UGRAD service).

Professional development

  • RAISE AI Bridge Summit, Texas A&M University, January 2026. Week-long interdisciplinary summit on use-inspired AI, including physics-informed machine learning, Bayesian learning, and uncertainty quantification.
  • Summer PACES Research Training Workshop, Albuquerque, NM, August 2025. Selected participant; high-performance computing and AI/ML workflows on NSF-supported clusters.
  • OpenFOAM training certifications, CFD Direct, January–February 2025. OpenFOAM Foundation, OpenFOAM Advanced, Essential CFD, and Applied CFD.
  • Machine Learning Specialization, University of Washington via Coursera, 2021. Regression, classification, clustering, and retrieval.
  • Python for data science and machine learning, 2021–2023, including the Digital Skills for KP data science and machine learning training; MATLAB Master Class, IETE Mumbai and Pantech Prolabs, 2020.

Industry and Applied Experience

Alongside research, I have worked in applied settings, from asphalt plant quality assurance to applied machine learning and mathematics education content, that inform how I frame and teach engineering problems.

  1. Engineering Intern, E.R. Snell Contractor, Inc., Summer 2023. Thermal processing and quality-assurance workflows at asphalt plants, including mix sampling and testing; OSHA 10-hour construction safety certification.
  2. Mathematics Subject Matter Expert and Content Reviewer, Photomath Expert Marketplace, Jul 2020–Dec 2022. Peer-reviewed and quality-assured 23,584 step-by-step solutions in algebra, calculus, geometry, statistics, and foundational mathematics for correctness, clarity, and completeness, and authored 1,019 original solutions aligned with international school and early-university curricula.
  3. Artificial Intelligence Research Intern, CureMD, Aug 2021–Feb 2022. Built a TensorFlow CNN for multimodal sentiment classification from speech and text after speaker diarization.
  4. Logistics and Supply Chain Intern, PepsiCo Pakistan, Jun–Jul 2021. Benchmarked health, safety, and environmental standards across multinational food-manufacturing logistics operations.
  5. Technology and Communications Intern, Zigron (Pvt.) Limited, Sep–Nov 2020. Technical research and reports on IoT-based smart-home security systems.
  6. Mechanical Engineering Intern, Gadoon Textile Mills, Jul–Aug 2019. Automated yarn-production machinery and CNC part programming (ISO 6983 G- and M-code).
Muhammad Hasnain in a safety vest standing in front of an asphalt plant at E.R. Snell
E.R. Snell asphalt plant, Summer 2023.
Muhammad Hasnain in a hard hat and safety vest sampling asphalt mix at an E.R. Snell plant
Sampling asphalt mix for quality testing.

News

  • MIGONet, a multiple-input graph neural operator trained on solver-free manufactured solutions, accepted in Transport Phenomena.
  • Tree-stem fire-injury heat transfer model published in International Communications in Heat and Mass Transfer (vol. 180, article 112653).
  • Presented "A physics-assisted geometry-generalizable graph convolutional network for fluid flow" at WCCM-ECCOMAS 2026 in Munich, supported by Texas A&M Graduate and Professional School travel awards.
  • Invited workshop "The Blueprint: Methodology and Experimental Design" for the Undergraduate Research Group at GIKI.
  • Volunteered at the Texas Science and Engineering Fair through Spark! PK–12 outreach; three-dimensional gypsum board thermal response model published in International Journal of Thermal Sciences.
  • ShockCast accepted at ICLR 2026; Use-Inspired Spotlight presentation at the RAISE AI Bridge Summit, Texas A&M; metal hydride modeling review published in Renewable and Sustainable Energy Reviews.
Earlier news 11
  • Presented graph neural networks for heat transfer and fluid flow at ASME IMECE 2025, Memphis, with a departmental Graduate Student Travel Award.
  • ResMLP-GCN paper published in Physics of Fluids.
  • Poster on heat and mass transfer in metal hydride reactors at the 9th Annual Texas A&M Conference on Energy.
  • Selected for the Summer PACES Research Training Workshop on HPC and AI/ML workflows, Albuquerque, NM.
  • Began PhD at Texas A&M University in the Computational Heat Transfer Laboratory with Prof. N. K. Anand; completed the Teaching Assistant Institute.
  • Defended MS thesis at Georgia Southern; metal hydride reactor paper published in International Journal of Hydrogen Energy.
  • Top Eagle Award (first among 176 posters) and Georgia Power Innovation Award at the Georgia Southern Student Research Symposium.
  • Four fire and combustion modeling presentations at the ESSCI Spring Technical Meeting, Athens, GA.
  • Two papers presented at ASME IMECE 2023, New Orleans, with a Graduate Student Organization travel grant.
  • SALT and Gulfstream Aerospace research awards at the Georgia Southern Student Research Symposium.
  • Presented the 3D gypsum board model at the 13th U.S. National Combustion Meeting, College Station.

Contact

I welcome conversations about faculty opportunities, collaborations, and speaking invitations.

References

  • Prof. N. K. Anand (PhD advisor)
    J. Mike Walker '66 Department of Mechanical Engineering, Texas A&M University
  • Dr. Hayri Sezer (MS advisor)
    Department of Mechanical Engineering, Georgia Southern University

Contact details for my advisors and additional professional references are included in my application materials.

Illustrative animation based on a simplified model; reported results are in the linked paper.