Ahmad A. Rushdi — Projects

LLM Evaluation: Uncertainty & Trust

Recent work stress-testing large language and vision-language models — whether they genuinely reason about numerical functions or merely recall, and whether a model's stated confidence stays warranted as its perceptual evidence degrades.

Reasoning or recall? A blind protocol hides the identity of a function and asks LLMs to predict, integrate, and optimize it from sampled points alone — separating genuine numerical reasoning from memorized recall.

blind numerical-function protocol — Blind protocol across three tasks (multifidelity, integration, optimization): sampled points → LLM → predicted function, integral, or optimum.

recall vs reasoning spectrum — Responses span a spectrum — recall, code, genuine reasoning, or no capability — by error metric and sample budget. paper

Confidence as testimony. As perceptual evidence decays under noise and occlusion, a faithful model should lose confidence — yet some confabulate a confident, wrong class instead.

VLM class and confidence across six images under increasing noise and occlusion — Six items × seven defeater levels (noise + occlusion): the model's class (*italic* = wrong) and verbalized confidence. Faithful items abstain; others confabulate (cup→“tambourine”, clock→“mirror”). paper

AI Ethics & Governance

Where regulation meets the pace of AI — measuring how governance actually works, and where it stalls.

Bridging AI development and regulation. Only 4.23% of U.S. AI bills (2017–2025) reach a terminal outcome; a position paper argues for adaptive, anticipatory legislation with independent oversight. position paper

bill-flow funnel — Flow of 1,419 state AI bills (2017–2025) from introduction through committee, floor vote, and final outcome. paper

High-d sampling & visualization

A library of high-dimensional test functions for optimization, uncertainty quantification, and numerical integration problems.

Model evaluation & UQ for AI/ML

Quantifying uncertainty in AI/ML predictive estimates, decomposing it into aleatoric and epistemic components, and using it to guide active learning. Applications across vision, image classification, regression, and time-series.

Vision. Uncertainty in object detection, segmentation, and image generation/captioning workflows.

DALL·E 3 generation — Text-to-image generation with DALL·E 3 (prompt: "A nature reserve with giraffe, elephant, zebra, lion, faceted style.")

YOLO detection — Object detection with YOLOv3 (COCO).

SAM segmentation — Image segmentation using Meta's Segment Anything (SAM).

BLIP captioning — Image captioning with BLIP (via Hugging Face inference API).

Image classification. Accuracy & uncertainty impact of rotation and AWGN on NN classifiers (MNIST / CIFAR).

MNIST under rotation.

MNIST under additive Gaussian noise.

1-d regression. Uncertainty bands with deep ensembles, MC dropout, and conformal prediction over limited noisy observations.

Uncertainty bands across methods.

Multifidelity fusion. Convolutional encoder/decoder networks that fuse many cheap low-fidelity samples with a few expensive high-fidelity ones to reconstruct full fields and their predictive uncertainty.

multifidelity field predictions — True vs. predicted pressure fields with error and uncertainty maps (Poiseuille flow), reconstructed mostly from low-fidelity data. paper

Voronoi Piecewise Surrogate (VPS) models

Leveraging Voronoi diagrams and Delaunay graphs for global surrogate modeling in high-dimensional UQ and adaptive sampling under limited sample budgets (multifidelity / costly / high-stakes simulations).

VPS neighbors — Finding significant Voronoi neighbors in high dimension. paper

VPS surrogate — A global high-d surrogate stitching local patches in Voronoi cells. paper

gradients — Gradient samples for local active subspaces.

POF darts — Adaptive sampling for probability-of-failure estimation. paper

Meshing & mesh tuning

Creating and tuning 2-d / 3-d meshes with guaranteed quality properties.

VoroCrust: unclipped Voronoi mesh conforming to a high-quality surface mesh. paper

All-quad mesh — Robust all-quad meshing of domains with connected regions, with angle & edge-length guarantees. paper

Fourier & signal processing in bio / bioinformatics

Feature extraction (e.g., period-3 in DNA), object localization (e.g., echoes in ultrasound), and spectral analysis of high-d sampling techniques via Nd-FFT.

persistence spectrum — Persistence spectrum: a narrowband interference signal embedded in broadband.

Digital notch filtering to detect wideband ultrasound contrast echoes in blood.

Spoke-darts spectrum — Fourier spectrum of high-d sample patterns. paper

From computational methods to engineering applications

Extending mesh-tuning methods (e.g., non-obtuse triangulation, paper) to model fiber-reinforced polymers for elastic & failure simulations; and ML for collision detection and motion planning.

fiber simulation — Cross-section of a fiber micrograph and model at peak load; simulated tensile response of different packings. paper

Collision detection phase model.