Dr. Shahadat Hussain

// 01. ABOUT

The lab bench is a terminal.

Modern materials engineering lives at the intersection of geometry, physics, and data. My computational work spans the full loop: generating triply periodic minimal surface (TPMS) fields, discretizing them into printable meshes, simulating their mechanical response, and closing the loop with machine-learning models trained on real laser powder bed fusion (LPBF) process data.

This approach lets me do things that are impractical experimentally — sweep hundreds of lattice parameters overnight, predict where balling or spattering will occur before a single laser fires, and quantify microstructural features directly from SEM imagery instead of eyeballing them.

"For industry partners in aerospace and defense, this translates to three things: faster iteration, lighter parts, and qualified processes."

PhD - AcSIR / CSIR Postdoc - Khalifa Univ NYU Abu Dhabi IBM Data Science Cert

QUALIFIED

ASSOCIATE RESEARCH SCIENTIST

Additive Manufacturing & Metamaterials

ORCID: 0000-0002-4355-2169

6+ YEARS_R&D_EXP

3+ TPMS_TOPOLOGIES

10+ PUBLICATIONS

∞ PARAM_SWEEPS

// 02. LIVE TPMS GEOMETRY & TELEMETRY SIMULATOR

2D_ISOFIELD_PREVIEW

FIELD: GYROID ISO-LEVEL CELLS: 128 x 128

TPMS LATTICE PARAMETER CONTROL

Adjust parameters in real-time to simulate relative density and iso-surface threshold offsets for laser powder bed fusion (LPBF).

ISO THRESHOLD (t) 0.35

CELL FREQUENCY (ω) 2.5

EST. RELATIVE DENSITY 28.4 %

POROSITY 71.6 %

PRINTABILITY OPTIMAL

// 03. TECH_STACK

Tools of the trade

A scientific-computing stack purpose-built for computational materials design and manufacturing analytics.

LANGUAGE / CORE

▸Python (NumPy, SciPy, pandas)
▸MATLAB / Numerical Methods
▸C++ for Performance Kernels
▸Bash & Linux HPC Workflows

ML / INFORMATICS

▸scikit-learn · Defect Classify
▸PyTorch · Surrogate Models
▸OpenCV · SEM Quantification
▸Materials Pipelines & EDA

GEOMETRY / FEA

▸Implicit Surfaces & Marching Cubes
▸nTopology Lattice Design
▸FEA Scripting (Abaqus/ANSYS)
▸STL / 3MF Mesh Processing

ENGINEERING / OPS

▸Git, Actions, Reproducibility
▸LaTeX & Scientific Reporting
▸LPBF Telemetry Analysis
▸Data-Driven AM Parameters

// 04. CODE_SHOWCASE

From equation to print file

The heart of the lattice generator — a gyroid is just three lines of trigonometry until you discretize it, threshold it, and hand it to a printer.

tpms_generator.py — computational-materials

PYTHON 3.10 // NUMPY

import numpy as np

def gyroid(x, y, z):
    """Implicit gyroid surface — F(x, y, z) = t."""
    return (np.sin(x) * np.cos(y)
          + np.sin(y) * np.cos(z)
          + np.sin(z) * np.cos(x))

def sample_field(level_fn, n=160, threshold=0.35):
    """Sample the level-set field on a regular grid.
    The resulting scalar field feeds marching-cubes
    to produce a watertight, LPBF-ready mesh.
    """
    grid = np.linspace(0, 2 * np.pi, n)
    x, y, z = np.meshgrid(grid, grid, grid)
    return (level_fn(x, y, z) - threshold).astype(np.float32)

# One unit cell, ready for laser powder bed fusion
field = sample_field(gyroid, n=160, threshold=0.35)
print(f"field sampled: {field.shape} · ready for meshing")

// 05. RESEARCH & PUBLICATIONS

Published work, backed by pipelines

Every study below is supported by reproducible analysis code — from raw process logs to final figures.

YEAR: 2026 // LATEST PUBLICATION PEER-REVIEWED

Do chopped fibers matter? Process–structure–property relationships and thermal annealing effects in fiber-reinforced TPMS lattices

Investigated the effect of carbon fiber reinforced composite and annealing on mechanical properties of TPMS gyroid cubes.

Progress in Additive Manufacturing · Vol. xxx · pp. xxx–xxx

YEAR: 2023 JOURNAL ARTICLE

Microstructural and surface analysis of NiTi TPMS lattice sections fabricated by laser powder bed fusion

Built the image-analysis and statistical pipeline used to quantify Ni evaporation, oxide- and Ti-rich phase formation across Primitive and Gyroid topologies — linking geometry and laser parameters to solid-phase distribution.

Journal of Manufacturing Processes · Vol. 102 · pp. 375–386

YEAR: 2022 JOURNAL ARTICLE

Imperfections formation in thin layers of NiTi TPMS lattices fabricated using LPBF

Designed the experimental-parameter sweep and defect-classification workflow that isolated the effects of relative density and scan strategy on balling and intergranular cracking in thin Schwarz TPMS layers.

Materials · 15(22), 7950

YEAR: 2022 CONFERENCE PROCEEDINGS

Inhomogeneous microstructure due to non-uniform solidification rate in NiTi TPMS structures

Developed the SEM feature-mapping workflow used to document ten distinct microstructural regimes across lattice struts, providing the quantitative basis for solidification-rate hypotheses in architected AM parts.

ASME IMECE · Columbus, Ohio, USA

// CONTACT_INTERFACE

Let's build something precise.

Open to R&D and advanced-manufacturing roles in aerospace, defense, and high-performance engineering — especially where computation meets the melt pool.

✉ GET IN TOUCH GITHUB LINKEDIN MAIN SITE

ENGINEERING MATERIALS WITH CODE, SIMULATION & DATA.

PROCESS TELEMETRY LPBF-NITI-01

The lab bench is a terminal.