2 citations · 5 across the 7 of their papers we have counts for
9 papers
Decoding Extrahepatic Targeting of Lipid Nanoparticles with Interpretable Machine Learning
Asal Mehradfar, Mohammad Shahab Sepehri, Owen Antholine +4
Lipid nanoparticles (LNPs) have transformed RNA medicine, yet their clinical utility remains constrained by predominant hepatic accumulation after systemic administration. Redirect…
ATHENA: Adaptive Test-Time Steering for Improving Count Fidelity in Diffusion Models
Mohammad Shahab Sepehri, Asal Mehradfar, Berk Tinaz +2
Text-to-image diffusion models achieve high visual fidelity but surprisingly exhibit systematic failures in numerical control when prompts specify explicit object counts. To addres…
EM-Aware Physical Synthesis: Neural Inductor Modeling and Intelligent Placement & Routing for RF Circuits
Yilun Huang, Asal Mehradfar, Salman Avestimehr +1
This paper presents an ML-driven framework for automated RF physical synthesis that transforms circuit netlists into manufacturable GDSII layouts. While recent ML approaches demons…
A Machine Learning Benchmarking Framework for Lipid Nanoparticle Transfection Efficiency Prediction
Asal Mehradfar, Mohammad Shahab Sepehri, Jose Miguel Hernandez-Lobato +4
The discovery of new ionizable lipids for efficient lipid nanoparticle (LNP)-mediated RNA delivery remains a major bottleneck in RNA therapeutics development. Recent advances demon…
FALCON: An ML Framework for Fully Automated Layout-Constrained Analog Circuit Design
Asal Mehradfar, Xuzhe Zhao, Yilun Huang +5
Designing analog circuits from performance specifications is a complex, multi-stage process encompassing topology selection, parameter inference, and layout feasibility. We introdu…
Leveraging Uncertainty Estimation for Efficient LLM Routing
Tuo Zhang, Asal Mehradfar, Dimitrios Dimitriadis +1
Deploying large language models (LLMs) in edge-cloud environments requires an efficient routing strategy to balance cost and response quality. Traditional approaches prioritize eit…
Supervised Learning for Analog and RF Circuit Design: Benchmarks and Comparative Insights
Asal Mehradfar, Xuzhe Zhao, Yue Niu +4
Automating analog and radio-frequency (RF) circuit design using machine learning (ML) significantly reduces the time and effort required for parameter optimization. This study expl…
CryptoMamba: Leveraging State Space Models for Accurate Bitcoin Price Prediction
Mohammad Shahab Sepehri, Asal Mehradfar, Mahdi Soltanolkotabi +1
Predicting Bitcoin price remains a challenging problem due to the high volatility and complex non-linear dynamics of cryptocurrency markets. Traditional time-series models, such as…
AICircuit: A Multi-Level Dataset and Benchmark for AI-Driven Analog Integrated Circuit Design
Asal Mehradfar, Xuzhe Zhao, Yue Niu +4
Analog and radio-frequency circuit design requires extensive exploration of both circuit topology and parameters to meet specific design criteria like power consumption and bandwid…