Pioneering topological acoustics and quantum-inspired technologies at the NSF-funded New Frontiers of Sound Center. Transforming how we harness sound for computing, telecommunications, and environmental sensing.
PhD Mechanical & Aerospace Engineering · US Patent Holder · NASA Collaborator
Two browser-deployed design suites I wrote from the physics up: a phononic-plate bandgap engine and a generative car-design studio with neural aerodynamic surrogates. Both run entirely in the browser, no install, no API keys.
AeroPhon in two minutes: a car described in plain English becomes a point cloud, a graph neural network reads it, and drag, surface pressure and crash response come back in seconds — sound on for the score, then try it live → · watch in 1440p →
Inverse-design phononic-plate bandgaps from a chat prompt. PINN + CNN surrogates trained on 10 000+ FEM simulations across eight engineering materials, with on-device Llama-3.2-1B for free-form natural language.
Describe or sketch a car and get a 3D model you can edit part by part, plus an AI concept render. Then test it like an engineer: drag, surface pressure, wall shear and 3D crash response, from neural surrogates trained on 5k+ CFD cars (DrivAerNet).
The same case as the film: 424 × 636 × 141, so 38 million cells at 8° angle of attack, on one laptop GPU. Drawn as isosurfaces of the Q-criterion coloured by velocity, which isolates where rotation dominates strain, so these are the vortices rather than the whole velocity field. Tubes shed from the slat gaps, the nacelle and the wing tip. The first 1.6 flow-throughs are discarded, so this is the developed wake and not the starting transient.
Three views: top-down, where the wing and slat wakes separate most
cleanly; a wide three-quarter; and a close pass on the slat and
nacelle. Solver: FluidX3D, D3Q19, FP16C with a Smagorinsky subgrid
model, RTX 5070 Laptop. The force path is validated against the
closed-form Stokes drag to 3.9 %.
On what this is and is not.
The cell is 152 mm, so the vortices cannot be finer than roughly
half a metre and the surface staircase is the voxelised geometry, not
the flow. The 4th AIAA High-Lift Prediction Workshop puts the
requirement above 250 million degrees of freedom, which this is
6.6× short of, and the grid Reynolds number of 105
sits 331× below flight. This grid resolves separation but not
attachment: the wing wake is many cells across and genuinely captured,
while anything attached to a surface is not. It is a real solve at a
resolution chosen so hundreds of riggings fit in the cost of one
high-fidelity case, and it is not a prediction of high-lift
coefficients.
Mechanical & Aerospace Engineer and Research Scientist with over 7 years of experience specializing in AI-driven acoustic metamaterial design, topological acoustics, thermoacoustic systems, quantum analogies in acoustics, RF device engineering, and neural network-optimized acoustic metastructures.
I am a Research Scientist at the University of Arizona's New Frontiers of Sound (NewFoS) Science & Technology Center, an NSF-funded multi-institutional research hub. My work sits at the intersection of topological acoustics, quantum-inspired systems, and AI-driven computational simulation.
I hold a PhD in Mechanical & Aerospace Engineering from Oklahoma State University with a proven track record of successful NASA collaborations on Thermoacoustic Metastructures (TAMS). Expert in advanced computational modeling using COMSOL Multiphysics, ANSYS, DeltaEC, and AI frameworks including TensorFlow, PyTorch, and physics-informed neural networks (PINNs).
My research demonstrates the ability to translate complex AI-acoustic research into practical aerospace, semiconductor, telecommunications, and energy applications. I collaborate with leading institutions including Caltech, UCLA, Georgia Tech, UC Boulder, CUNY, Wayne State, Spelman College, and University of Alaska-Fairbanks.
Recognized leader in mentoring next-generation engineers (7+ researchers mentored) and fostering innovation through cross-disciplinary collaborations spanning mechanical engineering, aerospace engineering, and artificial intelligence domains.
"The only way to discover the limits of the possible is to go beyond them into the impossible."— Arthur C. Clarke
Leading breakthrough research at the $30M NSF-funded NewFoS Science & Technology Center, developing next-generation acoustic technologies that bridge classical sound waves and quantum mechanics.
Pioneering research on GST (Ge2Sb2Te5) phase-change materials that enable frequency-selective wave routing without geometric reconfiguration. My work demonstrates anti-resonance driven directional wave propagation, where specific frequencies create unidirectional transport while others enable bidirectional propagation.
This research establishes a new paradigm for reconfigurable phononic systems by leveraging the reversible crystalline-to-amorphous phase transition in GST. Unlike traditional approaches requiring physical modification of lattice geometry, our PCM-based method achieves dynamic tunability through thermal or electrical stimuli, enabling real-time control of acoustic wave pathways at frequencies up to ~200 MHz.
Developing robust acoustic qubits using topologically protected edge states operating at room temperature—eliminating the need for expensive cryogenic cooling systems that currently limit quantum computing accessibility.
Our approach exploits the mathematical equivalence between acoustic wave propagation in phononic crystals and electron behavior in quantum systems. By engineering Su-Schrieffer-Heeger (SSH) model analogs in mechanical lattices, we create protected edge modes that are inherently immune to backscattering from disorder and defects—a critical requirement for maintaining quantum coherence.
This classical-to-quantum mapping enables proof-of-concept demonstrations of topological phenomena at macroscale before transitioning to true quantum implementations, dramatically reducing development costs and accelerating the path to practical quantum devices.
Creating one-way acoustic waveguides for next-generation 5G/6G telecommunications with 75% faster AI-driven optimization cycles. Our Surface Acoustic Wave (SAW) devices leverage topological protection to achieve unprecedented signal isolation and frequency selectivity.
Traditional RF filters suffer from crosstalk and signal degradation at high frequencies. By implementing topologically protected channels in piezoelectric substrates, we create filters with sharp frequency cutoffs and minimal insertion loss—critical for the dense spectrum allocation required by emerging 6G standards.
Our AI-accelerated design pipeline combines physics-informed neural networks with high-throughput COMSOL simulations, reducing the typical 6-month design cycle to under 6 weeks while achieving performance metrics that exceed conventional approaches by 15-20%.
Implementing physics-informed neural networks (PINNs) achieving 75% reduction in design iteration cycles for complex metamaterial systems. Our deep learning frameworks encode fundamental physical laws directly into network architectures, ensuring physically consistent predictions.
Traditional finite element simulations for phononic crystal optimization require hours per configuration. Our neural surrogate models, trained on carefully curated datasets from COMSOL Multiphysics, deliver real-time predictions with less than 3% error relative to full-physics simulations.
Beyond acceleration, our AI systems enable inverse design—specifying desired acoustic properties and automatically generating optimal geometries. This capability has produced novel metamaterial configurations that human designers would not have conceived, pushing beyond conventional design spaces.
Pushing the boundaries of computing, AI, and space technology through interdisciplinary research and innovation.
Vision-Language-Action models bridging artificial intelligence with embodied robotics. Humanoid systems that perceive, reason, and act in the real world.
Explore Documentary →Brain-inspired silicon architectures utilizing spiking neural networks. Ultra-low power computing mimicking biological neural dynamics.
Explore Documentary →Space-based computing infrastructure leveraging orbital mechanics. Distributed processing systems beyond Earth's atmosphere for next-gen applications.
Explore Documentary →Revolutionary concepts for deploying data center infrastructure in space. Leveraging vacuum cooling and solar power for sustainable hyperscale computing.
Explore Documentary →Pioneering breakthroughs in topological acoustics, quantum analogies, and sustainable energy solutions.
My PhD research represents a relentless pursuit of excellence in acoustic and thermoacoustic metamaterials—advancing sustainable and efficient energy solutions through innovative engineering.


















Perfect marriage of form and function—highly directional acoustic propagation, optimizing energy efficiency while minimizing cross-mode interferences.
Grace and power of continuous curvature—helical pathways excel in uniform distribution of acoustic energy with cascading reflective surfaces.
Zenith of acoustic metamaterial design—spatial compactness with spiral efficiency, enabling precise control over wave propagation and heat transfer.
Witness the thermoacoustic technology in action—from test rigs to flow simulations.
Witness how TAMS revolutionizes urban landscapes, enhances aviation by converting noise into energy, and extends to space, exploiting extreme temperature gradients for sustainable solutions.
Experience the elegant interplay of sound and energy as sound waves transform into vibrant colors, symbolizing their conversion into thermal gradients. Heat exchangers capture temperature differences, and thermopiles turn heat into electricity—transforming ambient noise into renewable power.
Exploring complex physics and engineering concepts through interactive documentaries and in-depth articles.
Experience these visualizations running live — click to interact or expand to fullscreen.
Topological edge states and bulk-boundary correspondence
Open Fullscreen →Interactive simulation built with Three.js and WebGL using RK4 Integration. Modeling GW170817 parameters from Abbott et al. 2019.
Phi-bits (phase-bits) as classical acoustic analogs to quantum bits. Goal: 50 phi-bit quantum-inspired platform accessing 65,536 dimensional Hilbert space.
Thermoacoustic Meta-Structures (TAMS) achieving 5+ dB noise reduction. Patent WO2025128348A1. Tested at DFW Airport.
Comprehensive expertise spanning acoustic engineering, computational modeling, AI/ML, and advanced manufacturing technologies.
Building breakthroughs together — research team moments, conferences, and cross-institutional collaboration.














Open to research collaborations, industry partnerships, and opportunities in topological acoustics, AI-driven metamaterial design, quantum-inspired technologies, aerospace applications, and semiconductor/telecommunications R&D.