6 citations · 22 across the 35 of their papers we have counts for
17 papers · 1 filter
From Probabilities to Decisions: Search and Multi-Teacher Distillation with Jev
Mohamad Yazan Sadoun, Sarah Sharif, Yaser Mike Banad
Probability-only models, which TypeSafe calls System One models, return calibrated probabilities for fixed choices in milliseconds and generate no text. We study one such model, Je…
Event Cameras for Melt-Pool Monitoring in Additive Manufacturing: A Benchmark and a Cross-Machine Transfer Analysis
Mohamad Yazan Sadoun, Sarah Sharif, Yingtao Liu +2
Melt-pool monitoring is central to qualifying metal additive manufacturing (AM), yet no public event-camera benchmark exists for this domain. Event cameras report per-pixel brightn…
Machine Learning Framework for Magnetic Candidate Discovery in Cerium-Based Compounds
Joshua A. Torres, Yaser M. Banad, Benjamin O. Tayo +1
Cerium (Ce), the most abundant lanthanide, offers significant potential for addressing shortages in high-performance magnetic materials, particularly through the discovery of compo…
Physics adapted generative AI for metal insulator transition materials under label scarcity
Gourab Datta, Sarah Sharif, Zhisheng Shi +1
Metal-insulator-transition (MIT) materials are promising candidates for switchable electronics, neuromorphic hardware, and reconfigurable photonics, yet experimentally verified exa…
Unified Complex-valued Neural Network: A Magnitude-Phase Computational Model for Event-Driven Neuromorphic Learning
Reza Ahmadvand, Sarah Safura Sharif, Yaser Mike Banad
Artificial neural networks (ANN) provide accurate continuous-valued representation, whereas spiking neural networks (SNN) offer event-driven temporal processing, yet both paradigms…
Validation-Gated Causal Interventions for Interpreting High-Stakes Large Language Model Behavior: A Case Study in Suicidality Detection
Nafiz Ahmed, Sarah Sharif, Dingjing Shi +1
Large language models are proposed to flag suicidal content, but representing a concept and acting on it are distinct. A suicidality feature is decodable from 0.5B parameters upwar…
Physics-informed generative AI for semiconductor manufacturing: Enforcing hard physical constraints in generative models by construction
Yaser Mike Banad, Sarah Sharif
Generative models are increasingly used to propose designs, data, and control actions for physical systems, yet many such systems are governed by hard physical constraints rather t…
Brain-inspired spike-timing plasticity for reliable label-efficient event-camera vision
Mohamad Yazan Sadoun, Sarah Sharif, Yaser Mike Banad
Deploying event-camera object detectors is constrained by per-frame labeling requirements and GPU compute demands. This work introduces three local spike-timing-dependent plasticit…
Memristor Technologies for Dynamic Vision Sensors: A Critical Assessment and Research Roadmap
Mohamad Yazan Sadoun, Edris Zaman Farsa, Sarah Sharif +1
Edge-AI deployment is bottlenecked by data-movement energy; pairing event-driven vision sensors with in-memory analog compute could lift that ceiling by orders of magnitude. Both t…
Emerging 2D Materials for Beyond von Neumann Computing: A Perspective
Yaser Banad
The end of conventional Dennard scaling and the widening gap between memory bandwidth and arithmetic throughput have made the von Neumann partition a structural bottleneck rather t…
Enhanced LLM Reasoning by Optimizing Reward Functions with Search-Driven Reinforcement Learning
Arash Ahmadi, Sarah Sharif, Yaser +1
Mathematical reasoning is a key benchmark for large language models. Reinforcement learning is a standard post-training mechanism for improving the reasoning capabilities of large…
IoT-Enhanced CNN-Based Labelled Crack Detection for Additive Manufacturing Image Annotation in Industry 4.0
Mohsen Asghari Ilani, Yaser Mike Banad
This paper presents an IoT-enhanced deep learning framework for automated crack detection in Additive Manufacturing (AM) surfaces using convolutional neural networks (CNNs). By int…
A Unified Phase-native Computational Principle Governs Hippocampal Spike Timing and Neural Coding
Reza Ahmadvand, Sara Safura Sharif, Yaser Mike Banad
Hippocampal neurons exhibit precise phase locking to network oscillations, but the computational principle governing this temporal precision is still unclear. Neural information is…
SparseVoxelDet: Fully Sparse Voxel Networks for Efficient Event-Based Drone Detection
Mohamad Yazan Sadoun, Sarah Sharif, Yaser Mike Banad
Event cameras excel at detecting small, fast drones, but today's detectors give away their key advantage: they convert the sparse event stream into dense grids and pay dense-proces…
Toward Digital Twins in 3D IC Packaging: A Critical Review of Physics, Data, and Hybrid Architectures
Gourab Datta, Sarah Safura Sharif, Yaser Mike Banad
Three-dimensional integrated circuit (3D IC) pack-aging and heterogeneous integration have emerged as central pillars of contemporary semiconductor scaling. Yet, the multi-physics…
Event-based Heterogeneous Information Processing for Online Vision-based Obstacle Detection and Localization
Reza Ahmadvand, Sarah Safura Sharif, Yaser Mike Banad
This paper introduces a novel framework for robotic vision-based navigation that integrates Hybrid Neural Networks (HNNs) with Spiking Neural Network (SNN)-based filtering to enhan…
Machine learning model for predicting surface wettability in laser-textured metal alloys
Mohammad Mohammadzadeh Sanandaji, Danial Ebrahimzadeh, Mohammad Ikram Haider +3
Surface wettability, governed by both topography and chemistry, plays a critical role in applications such as heat transfer, lubrication, microfluidics, and surface coatings. In th…